Human Brain/Cloud Interface
Open accessAbstract
The internet comprises a decentralized global system that serves humanity’s collective effort to generate, process, and store information. A significant portion of this data is currently processed and stored in the cloud, and the last few years have witnessed the doubling of cloud storage and cloud computing. Given such tremendous growth there is an urgent need to create a stable, secure, and continuous real-time system for interfacing the human brain with the cloud. One promising strategy for the creation of human brain/cloud interface (B/CI) technologies may be referred to as “neuralnanorobotics.” Neuralnanorobotic technology might well emerge from efforts to comprehensively address cognitive disorders and is expected to facilitate the accurate diagnoses and eventual cures for the ~400 conditions that affect the human brain. Neuralnanorobotics is also anticipated to have numerous non-medical applications -- for example, serving as a platform to enable a robust, ultrahigh-resolution interface between the human brain and the cloud. Neuralnanorobotics may permit a safe, secure, and stable real-time whole-human brain interface with the cloud, allowing for controlled connectivity between neural activity and external data storage and data processing. This strategy may involve direct and comprehensive monitoring of the estimated ~86 x 109 neurons of the human brain, along with its estimated ~2 x 1014 synapses, through the use of nanometric medical nanorobotics. Subsequent to navigating the human vasculature, three species of neuralnanorobots (endoneurobots, gliabots, and synaptobots) would traverse the blood-brain barrier, enter the brain parenchyma, ingress into individual human brain cells, and autoposition themselves at the axon initial segments of neurons (endoneurobots), within glial cells (gliabots), and in intimate proximity to every synapse or group of synapses (synaptobots). A neuralnanorobotically assisted human B/CI is expected to give rise to an extensive panoply of applications, among which would be the application of serving as a personalized conduit for individuals to obtain direct, instantaneous access to any facet of cumulative human knowledge available in the cloud. Other anticipated applications include a myriad of opportunities for improving education, intelligence, entertainment, traveling, and other interactive experiences.
AI snapshot
Written from the paper’s full text.
TL;DR
The paper proposes a human brain/cloud interface (B/CI) enabled by neuralnanorobots that would monitor and transmit brain activity to cloud supercomputers. It argues this could provide real-time access to cumulative human knowledge and enable applications such as transparent shadowing, while acknowledging the technology is speculative and 20–30 years away.
Key findings
- Three neuralnanorobot classes are proposed: endoneurobots at axon initial segments, gliabots within glial cells, and synaptobots near synapses, to monitor the brain’s ∼86 × 10⁹ neurons, ∼2 × 10¹⁴ synapses, and ∼84 × 10⁹ glial cells.
- The brain is estimated to process ∼5.52 × 10¹⁶ bits/sec via ∼4.31 × 10¹⁵ spikes/sec; a proposed 30 cm³ nanorobotic fiber-optic system could handle up to 10¹⁸ bits/sec for cloud transfer.
- Neuralnanorobotics is claimed to potentially treat ∼400 brain disorders and enable B/CI applications including education, intelligence enhancement, VR/AR, and “transparent shadowing”; a three-human BrainNet BTBI achieved average accuracy of 0.813.
- Volume displacement estimates: endoneurobots plus gliabots would occupy ∼0.12% of brain volume, while synaptobots would occupy ∼0.9–9%, described as just within a 1–10% “safe” intrusiveness limit.
Methods
- Conceptual/review article, not an empirical study; no new experimental data, human subjects, or clinical sample are reported.
- Synthesizes prior literature and engineering estimates—neuron/synapse counts, data rates, volumes, latency, and biocompatibility—to argue feasibility of a neuralnanorobotic B/CI.
- Proposes an architecture and protocols for nanorobot ingress, blood–brain barrier traversal, synaptic/neuronal monitoring, data transmission, biocompatibility, and FDA/ethics review.
Limitations
- Stated: further study is required to quantify the population, dimensions, and distribution of naturally occurring BBB perijunctional gaps; a comprehensive ethical analysis is expected before implementation; some display modes are beyond the paper’s scope.
- Evident: no experimental validation of neuralnanorobots is presented; the proposal depends on future technologies such as diamondoid nanofactories, advanced 5G, and cloud supercomputers.
- Evident: safety, efficacy, and biocompatibility claims are projections rather than demonstrated outcomes, and the 20–30-year timeline is speculative.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
56 of 175 cited sources checked · 33 supported · 0 flagged · accuracy not yet measured
- Interpretationcitation
The application of nanorobots to the human brain (neuralnanorobotics) may allow for the monitoring, recording, and even manipulation of many types of brain-related information at cellular and organellar levels.
“The application of nanorobots to the human brain is denoted here as “neuralnanorobotics.” This technology may allow for the monitoring, recording, and even manipulation of many types of brain-related information at cellular and organellar levels”
Quote in the paperSubstantial claim1 of 3 sources checked- cites Martins et al., 2012 source
- cites Martins et al., 2015
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Martins et al., 2016 source
The Abstract defines neuronanorobotics as applying medical nanorobots to the human brain and describes mapping, monitoring, and recording brain information. Section 1 extends the proposed monitoring to cellular and subcellular information, and Section 2 mentions monitoring neuronal organelles. Our copy does not say these nanorobots can manipulate brain-related information. (LLM, conf=0.87)
Experimental — accuracy not yet measured
- Premisecitation
Advanced nanomedicine - specifically, medical nanorobotics - is expected to serve as a dynamic tool toward addressing most human brain disorders.
“The pursuit of ever smaller tools to treat patients is approaching a pivotal juncture in medical history as advanced nanomedicine — specifically, medical nanorobotics — is expected to serve as a dynamic tool toward addressing most human brain disorders.”
Quote in the paperNot a substantial claim1 of 3 sources checked- cites Freitas, 1998 source
The FREITAS section says medical nanorobots have been proposed to repair brain damage, supporting a possible role in a brain-related condition. It does not say they are expected to address most human brain disorders; the paper instead develops a preliminary design for an artificial red blood cell. No page number is available in our copy. (LLM, conf=0.85)
Experimental — accuracy not yet measured - cites Freitas, 1999b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Freitas, 2003 source
- Interpretationcitation
The most promising long-term future technology for non-destructive, real-time human-brain-computer interfaces and brain-to-brain communications may be neuralnanorobotics.
“The most promising long-term future technology for non-destructive, real-time human–brain–computer interfaces and brain-to-brain communications may be neuralnanorobotics”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Martins et al., 2016 source
The Introduction proposes neuronanorobots for in-vivo, real-time whole-brain monitoring, and Section 4 says the approach appears uniquely able to provide non-destructive whole-brain scanning at nanometric resolution. The paper does not establish the further claim that neuronanorobotics is the most promising long-term technology for brain–computer interfaces or brain-to-brain communication. (LLM, conf=0.86)
Experimental — accuracy not yet measured
- Premisecitation
Crossing the BBB is a challenging process for ∼98% of all small molecules.
“However, fluorescing carbon nanodots might be problematic, since crossing the BBB is a challenging process for ∼98% of all small molecules”
Quote in the paperSubstantial claim1 of 2 sources checked - Premisecitation
Magnetoelectric nanoparticles may be employed to enhance coupling between external magnetic fields and localized electric fields that emanate from neural networks.
“One promising near-term technology that may enable an interface with brain-based neural networks is magnetoelectric nanoparticles, which may be employed to enhance coupling between external magnetic fields and localized electric fields that emanate from neural networks”
Quote in the paperSubstantial claim2 of 2 sources checked
- Premisecitation
Magnetoelectric nanoparticles might also induce nanoparticles to traverse the blood-brain barrier by applying a direct-current magnetic field gradient to the cranial vault.
“Magnetoelectric nanoparticles might also induce nanoparticles to traverse the blood–brain barrier (BBB) by applying a direct-current magnetic field gradient to the cranial vault.”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites Yue et al., 2012 source
The Introduction (page not specified) proposes that magnetoelectric nanoparticles smaller than approximately 20 nm can penetrate the blood–brain barrier. It does not say that a direct-current magnetic field gradient applied to the cranial vault drives that crossing; the magnetic fields discussed are used to control nanoparticles or stimulate brain activity. (LLM, conf=0.88)
Experimental — accuracy not yet measured - cites Guduru et al., 2015 source
- Findingcitation
Neural dust technology currently employs thousands of independent free-floating 10-100 μm scale sensor nodes.
“This technology currently employs thousands of independent free-floating 10–100 μm scale sensor nodes referred to as “neural dust.””
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Seo et al., 2013 source
The System Concept (p. 1) describes neural dust as thousands of independent, free-floating 10–100 μm sensor nodes. But it says the authors “propose” this system; it does not establish that the technology currently employs those nodes. (LLM, conf=0.91)
Experimental — accuracy not yet measured
- Interpretationcitation
Each individual neuron within the human brain is at most 2-3 neurons away from a microcapillary.
“Hence, each individual neuron within the human brain is at most 2–3 neurons away from a microcapillary (Pardridge, 2011).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Pardridge, 2011 source
- Findingcitation
Quantum dots can function as voltage-sensitive probes for real-time visualization of cellular membrane potential in neurons.
“For example, one recent study has found that quantum dots can function as voltage-sensitive probes for real-time visualization of cellular membrane potential in neurons (Nag et al., 2017).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Nag et al., 2017 source
- Findingcitation
A human brain guided the movements of a Madagascar hissing cockroach along an S-shape track, controlling the cockroach antennae via electrical stimulation.
“In another example of interspecies BTBI, a human brain guided the movements of a Madagascar hissing cockroach along an S-shape track, controlling the cockroach antennae via electrical stimulation (Li and Zhang, 2016).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Li and Zhang, 2016 source
- Findingcitation
Early 'neural dust' proposals for providing BCI access to specific human-brain regions had several inherent limitations.
“Early “neural dust” proposals for providing BCI access to specific human–brain regions (e.g., neocortex) had several inherent limitations (Seo et al., 2013).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Seo et al., 2013 source
- Interpretationcitation
Neuralnanorobotics is expected to provide a non-destructive, real-time, secure, long-term, and virtually autonomous in vivo system that can realize the first functional human B/CI.
“Neuralnanorobotics is expected to provide a non-destructive, real-time, secure, long-term, and virtually autonomous in vivo system that can realize the first functional human B/CI (Martins et al., 2012, 2015, 2016).”
Quote in the paperSubstantial claim1 of 3 sources checked- cites Martins et al., 2012 source
- cites Martins et al., 2015
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Martins et al., 2016 source
The Introduction and Conclusions propose non-destructive, real-time, in vivo monitoring of the human brain using neuronanorobots. The paper does not establish that the proposed system would be secure, long-term, virtually autonomous, or capable of realizing the first functional human brain–computer interface. (LLM, conf=0.88)
Experimental — accuracy not yet measured
- Findingcitation
An array of nanowire transistors can detect, stimulate, or inhibit nerve impulses and their propagation along individual neurites.
“An array of nanowire transistors can detect, stimulate, or inhibit nerve impulses and their propagation along individual neurites (Freitas, 1999b; Zeck and Fromherz, 2001; Patolsky et al., 2006).”
Quote in the paperNot a substantial claim1 of 3 sources checked- cites Freitas, 1999b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Zeck and Fromherz, 2001 source
The Abstract and Results and Discussion describe capacitive stimulation of snail neurons and transistor recording of their action potentials. But the Abstract says the study does not pursue array recording; its contacts are beneath neuron cell bodies, not individual neurites. The cited passages do not establish nanowire transistors or inhibition of nerve impulses. (LLM, conf=0.89)
Experimental — accuracy not yet measured - cites Patolsky et al., 2006 source
- Findingcitation
Intercapillary distances in the brain are typically ∼40 μm.
“Intercapillary distances in the brain are typically ∼40 μm.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Pardridge, 2011 source
- Findingcitation
Activities of individual neurons and localized neural circuits can be monitored and stimulated over timelines of eight months or more.
“This group also showed that the activities of individual neurons and localized neural circuits could be monitored and stimulated over timelines of eight months or more, for applications such as recording of alterations in the activities of specific neurons as the brain ages (Dai et al., 2018).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Dai et al., 2018 source
In “Mesh Nanoelectronics in Live Animals” (page unavailable), the paper reports tracking the same neurons and local circuits for eight months. Although it broadly describes recording and stimulation on a year time scale, its specific evidence for stable responses to chronic stimulation spans nearly three months, not eight or more. The Conclusions and Outlook identifies studying changes during brain aging as an application. (LLM, conf=0.86)
Experimental — accuracy not yet measured
- Interpretationcitation
Monitoring the intracellular structural and functional connectome may be enabled by three classes of neuralnanorobots: endoneurobots, synaptobots, and gliabots.
“Monitoring the intracellular structural and functional connectome may be enabled by three classes of neuralnanorobots, introduced here as endoneurobots, synaptobots, and gliabots (Martins et al., 2016).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Martins et al., 2016 source
- Findingcitation
Mesh nanoelectronics can integrate stably within brain tissue for at least 1 year without evidence of chronic immune response or glial scarring characteristic of conventional implants.
“Dai et al. (2018) also demonstrated “stable integration of mesh nanoelectronics within brain tissue on at least 1 year scales without evidence of chronic immune response or the glial scarring characteristic of conventional implants.””
Quote in the paperSubstantial claim1 of 1 sources checked- cites Dai et al., 2018 source
- Findingcitation
Recently demonstrated Brainet systems have verified potential direct communications between the brains of two rats located on different continents, after the rats had been permanently implanted with microelectrodes in the sensorimotor cortex.
“While not yet particularly sophisticated, recently demonstrated Brainet systems have already provided several interesting insights, including verification of potential direct communications between the brains of two rats located on different continents, after the rats had been permanently implanted with microelectrodes in the sensorimotor cortex (Pais-Vieira et al., 2013).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Pais-Vieira et al., 2013 source
- Findingcitation
High-density arrays of nanowire FETs enabled mapping signals at the subcellular level, a functionality not possible with conventional microfabricated devices.
“High-density arrays of nanowire FETs enabled mapping signals at the subcellular level – a functionality that is not possible with conventional microfabricated devices (Timko et al., 2010).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Timko et al., 2010 source
- Findingcitation
Experiments have tested three different control systems using 2-3 implanted monkeys that shared BMI-mediated control of a virtual arm.
“Experiments have tested three different control systems using 2–3 implanted monkeys that shared BMI-mediated control of a virtual arm (Ramakrishnan et al., 2015).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Ramakrishnan et al., 2015 source
- Findingcitation
BTBI systems were initially implemented in humans using non-invasive recordings and brain stimulation.
“BTBI systems were initially implemented in humans (Figure 2) using non-invasive recordings and brain stimulation.”
Quote in the paperNot a substantial claim2 of 2 sources checked - Findingcitation
Information was transferred from the sensorimotor cortex of one participant (recorded via EEG) to the visual or motor cortex of the second participant (delivered via transcranial magnetic stimulation).
“Information was transferred from the sensorimotor cortex of one participant (recorded via EEG) to the visual (Grau et al., 2014) or motor (Rao et al., 2014) cortex of the second participant (delivered via transcranial magnetic stimulation, or TMS).”
Quote in the paperSubstantial claim2 of 2 sources checked - Findingcitation
The BBB may also be opened using intravenous mannitol and ultrasound, externally delivered.
“The BBB may also be opened using intravenous mannitol (an old method) and ultrasound, externally delivered (Samiotaki et al., 2017; Wang et al., 2017).”
Quote in the paperNot a substantial claim1 of 2 sources checked- cites Samiotaki et al., 2017 source
The Introduction says focused ultrasound can open the BBB, and Methods §2.2 describes transcranial ultrasound in rhesus macaques. The intravenously administered agent in that procedure was microbubbles, not mannitol; our copy does not support the mannitol part of the citing sentence. Page numbers were not available in the indexed passages. (LLM, conf=0.88)
Experimental — accuracy not yet measured - cites Wang et al., 2017 source
- Findingcitation
Human brains have been connected to cell cultures, experimentally demonstrating that brain activity can control gene expression using an EEG-based BMI to trigger optogenetic stimulation of designer cells.
“Human brains have also been connected to cell cultures, experimentally demonstrating that brain activity can control gene expression, using an EEG-based BMI to trigger optogenetic stimulation of designer cells, thereby mediating their genetic expression (Folcher et al., 2014).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Folcher et al., 2014 source
- Premisecitation
Certain axonal and dendritic domains are less than 0.50 μm in diameter.
“For example, certain axonal and dendritic domains are less than 0.50 μm in diameter (Shepherd and Harris, 1998), and myelinated axons at three different sites of the corpus callosum in the human brain are estimated to have axon diameters of ≥0.50 μm, in 70–90% of cases (range 0.16–3.73 μm, mean 0.73 ± 0.55 μm) (Liewald et al., 2014).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Shepherd and Harris, 1998 source
The Axonal shafts section and Table 3 report shaft diameters averaging 0.17 μm, with a range of 0.11–0.30 μm, supporting the axonal part of the claim. The paper compares these narrow shafts to dendritic spine necks but does not give a dendritic diameter measurement below 0.50 μm. Page numbers are unavailable in our copy. (LLM, conf=0.85)
Experimental — accuracy not yet measured
- Premisecitation
Myelinated axons at three different sites of the corpus callosum in the human brain are estimated to have axon diameters of ≥0.50 μm, in 70-90% of cases (range 0.16-3.73 μm, mean 0.73 ± 0.55 μm).
“For example, certain axonal and dendritic domains are less than 0.50 μm in diameter (Shepherd and Harris, 1998), and myelinated axons at three different sites of the corpus callosum in the human brain are estimated to have axon diameters of ≥0.50 μm, in 70–90% of cases (range 0.16–3.73 μm, mean 0.73 ± 0.55 μm) (Liewald et al., 2014).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Liewald et al., 2014 source
The Discussion (page unavailable) confirms that the authors sampled three corpus-callosum locations in two human brains, but the Results give a diameter range of 0.17–5.13 μm and averages of 0.64–0.74 μm for those samples. Table 1 (page unavailable) assigns 0.73 ± 0.55 μm and a 3.73 μm maximum to the left superior longitudinal fascicle of brain 1, not the corpus callosum. The passages found do not substantiate the claimed 70–90% at or above 0.50 μm. (LLM, conf=0.91)
Experimental — accuracy not yet measured
- Findingcitation
The BrainNet experiment was repeated with five groups with an average accuracy of 0.813.
“The experiment was repeated with five groups with an average accuracy of 0.813.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Jiang et al., 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Findingcitation
BMI technology is currently pursued via invasive neural interfaces composed of neural microchip sensor arrays that contain a plurality of electrodes that can detect multicellular signals, available for several brain areas.
“Brain–machine interface technology is currently being pursued via invasive neural interfaces composed of neural microchip sensor arrays that contain a plurality of electrodes that can detect multicellular signals. These are available for several brain areas (e.g., visual cortex, motor cortex neuroprosthetics, hippocampus, and others) (Berger et al., 2005; BrainGate, 2009).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Berger et al., 2005 source
- cites BrainGate, 2009
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Findingcitation
The loss of synapses, as occurs in Alzheimer's patients, is intimately related to cognitive decline.
“The loss of synapses, as occurs in Alzheimer’s patients, is intimately related to cognitive decline (Dekosky and Scheff, 1990; Terry et al., 1991; Scheff and Price, 2006).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Findingcitation
Plug-and-play input/output neural interfacing has been achieved using platinum electrodes and silicon nanowire field-effect transistors, exhibiting a low interface contact resistance of ∼3 Ω.
“Plug-and-play input/output neural interfacing has also been achieved using platinum electrodes and silicon nanowire field-effect transistors, which exhibited a low interface contact resistance of ∼3 Ω (Schuhmann et al., 2017).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Schuhmann et al., 2017 source
- Findingcitation
Neural electrodes can be implanted without producing any detectable damage beyond the initial trauma and brief phagocytosis, typically limited to the edges of the electrode insertion pathway.
“Neural electrodes can be implanted without producing any detectable damage beyond the initial trauma and brief phagocytosis, which are typically limited to the edges of the electrode insertion pathway (Babb and Kupfer, 1984) (Freitas, 2003).”
Quote in the paperSubstantial claim0 of 2 sources checked - Findingcitation
A three-human BTBI system called 'BrainNet' allowed three human subjects to collaboratively solve a task using non-invasive, direct brain-to-brain communication.
“A three-human BTBI system, called “BrainNet,” has been recently developed, which allowed three human subjects to collaboratively solve a task using non-invasive, direct brain-to-brain communication (Jiang et al., 2018).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Jiang et al., 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Findingcitation
Nanoelectronics devices utilizing carbon nanotubes and silicon nanowires can detect and identify neuronal biomolecular chemical secretions and their bioelectrical activities.
“Currently, nanoelectronics devices utilizing carbon nanotubes and silicon nanowires can detect and identify neuronal biomolecular chemical secretions and their bioelectrical activities (Veliev, 2016).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Veliev, 2016
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationcitation
Autonomous nanomedical devices are expected to be biocompatible, primarily due to their structural materials, which would enable extended residency within the human body.
“Furthermore, autonomous nanomedical devices are expected to be biocompatible, primarily due to their structural materials, which would enable extended residency within the human body”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites Freitas, 1999a
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Freitas, 2002
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Freitas, 2003 source
- Interpretationcitation
Medical neuralnanorobots might be fabricated in sufficient therapeutic quantities to treat individual patients, using diamondoid materials, as these materials may provide the greatest strength, resilience, and reliability in vivo.
“Medical neuralnanorobots might also be fabricated in sufficient therapeutic quantities to treat individual patients, using diamondoid materials, as these materials may provide the greatest strength, resilience, and reliability in vivo”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Freitas, 2010 source
- Interpretationcitation
Non-destructive neuralnanorobotically mediated whole-brain monitoring coupled with single-cell repair capabilities is anticipated to provide a powerful medical capability to effectively treat most, or all of the ∼400 known brain disorders, including Parkinson's and Alzheimer's, addiction, dementia, epilepsy, and spinal cord disorders.
“Non-destructive neuralnanorobotically mediated whole-brain monitoring coupled with single-cell repair capabilities (Freitas, 2007) is anticipated to provide a powerful medical capability to effectively treat most, or all of the ∼400 known brain disorders, including, most notably: Parkinson’s and Alzheimer’s (Freitas, 2016), addiction, dementia, epilepsy, and spinal cord disorders (NINDS, 2017).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Freitas, 2007
- cites Freitas, 2016
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites NINDS, 2017
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Premisecitation
Experimental results have been reported using the injection and unfolding of sub-micrometer-thick, centimeter-scale macroporous mesh nanoelectronics through needles with diameters as small as 100 μm, which were injected into cavities with a >90% device yield.
“Experimental results have been reported using the injection and unfolding of sub-micrometer-thick, centimeter-scale macroporous mesh nanoelectronics through needles with diameters as small as 100 μm, which were injected into cavities with a >90% device yield”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Liu et al., 2015 source
- Interpretationcitation
The delivery of nanoparticles into the human brain will pose a formidable challenge.
“The delivery of nanoparticles into the human brain will indeed pose a formidable challenge.”
Quote in the paperNot a substantial claim - Premisecitation
Fluorescing carbon nanodots (synthesized using D-glucose and L-aspartic acid) with uniform diameters of 2.28 ± 0.42 nm have been employed to target and image C6 glioma cells in mouse brains.
“Fluorescing carbon nanodots (synthesized using D-glucose and L-aspartic acid) with uniform diameters of 2.28 ± 0.42 nm have been employed to target and image C6 glioma cells in mouse brains.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Zheng et al., 2015 source
- Interpretationreasoning
The challenge of connecting brain data to cloud supercomputers includes the bottleneck of the bandwidth required to transmit data worldwide.
“This challenge includes, in particular, the bottleneck of the bandwidth required to transmit data worldwide.”
Quote in the paperSubstantial claim - Interpretationcitation
Neural lace would introduce minimally invasive three-dimensional mesh nanoelectronics, via syringe-injection, into living brain tissue to allow for continuous monitoring and stimulation of individual neurons and neuronal networks.
“This would introduce minimally invasive three-dimensional mesh nanoelectronics, via syringe-injection, into living brain tissue to allow for continuous monitoring and stimulation of individual neurons and neuronal networks.”
Quote in the paperSubstantial claim - Interpretationreasoning
This finding may challenge the long-held belief that spikes in the soma are the primary means through which perception, learning, and memory formation occur.
“This finding may challenge the long-held belief that spikes in the soma (body of the neuron) are the primary means through which perception, learning, and memory formation occur.”
Quote in the paperSubstantial claim - Interpretationreasoning
Due to the immense volume of data involved, data transfer to and from living human brains and the cloud may likely require the use of supercomputers with artificial intelligence algorithms.
“Due to the immense volume of data involved, data transfer to and from living human brains and the cloud may likely require the use of supercomputers with artificial intelligence algorithms.”
Quote in the paperNot a substantial claim - Interpretationreasoning
Emulation of biological synapses is a prerequisite for the development of brain-like computational systems.
“This suggests that emulation of biological synapses is a prerequisite for the development of brain-like computational systems”
Quote in the paperSubstantial claim - Interpretationcitation
Excellent biocompatibility, tunable full-color emission, and the capacity to freely penetrate the BBB might make fluorescing carbon nanodots viable candidates as tagging agents to facilitate the implementation of nanomedical B/CI technologies.
“Excellent biocompatibility, tunable full-color emission, and the capacity to freely penetrate the BBB might make fluorescing carbon nanodots viable candidates as tagging agents to facilitate the implementation of nanomedical B/CI technologies”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Zheng et al., 2015 source
- Premisecitation
Estimates for whole-brain electrical data processing rates range from 1.48 × 10^11 bits/sec to a high of 3.2 × 10^29 bits/sec.
“Estimates for whole-brain electrical data processing rates range from 1.48 × 1011 bits/sec. to a high of 3.2 × 1029 bits/sec”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Sandberg and Bostrom, 2008
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Martins et al., 2012 source
- Interpretationcitation
Once brain data is interfaced with supercomputers in near real-time, the connection to supercomputers in the cloud will be the ultimate bottleneck between the cloud and the human brain.
“However, once brain data is interfaced with supercomputers in near real-time, the connection to supercomputers in the cloud will be the ultimate bottleneck between the cloud and the human brain”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Knapp, 2013
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Premisecitation
Steering nanoparticles to selected brain regions may also be achieved using external magnetic fields.
“Steering nanoparticles to selected brain regions may also be achieved using external magnetic fields”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Li et al., 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Premisecitation
Several centralized and distributed supercomputers have processing speeds that are significantly higher than this estimate.
“Several centralized and distributed supercomputers have processing speeds that are significantly higher than this estimate”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Martins et al., 2012 source
- Interpretationreasoning
As dendrites are ∼100 times larger by volume than neuronal bodies, the immense number of firing dendritic spikes would suggest that the brain may indeed possess significantly higher computational power than earlier estimated.
“As dendrites are ∼100 times larger by volume than neuronal bodies, the immense number of firing dendritic spikes would suggest that the brain may indeed possess significantly higher computational power than earlier estimated.”
Quote in the paperSubstantial claim - Premisecitation
One estimate of maximum computational speed required to handle the electrical data in the human brain is 5.52 × 10^16 bits/sec.
“One estimate of maximum computational speed required to handle the electrical data in the human brain is 5.52 × 1016 bits/sec”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Martins et al., 2012 source
- Interpretationcitation
All three types of neuralnanorobots would monitor action potential-based electrical information using the same types of FET-based nanosensors embedded in their surfaces.
“All three types of neuralnanorobots (endoneurobots, gliabots, and synaptobots) would monitor action potential-based electrical information using the same types of FET-based nanosensors embedded in their surfaces (Martins et al., 2015).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Martins et al., 2015
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationreasoning
For the purposes of a B/CI, interfacing with neuronal and synaptically processed action-potential-based electrical brain activity alone (without monitoring chemically based information) may be sufficient to facilitate robust human B/CI systems.
“For the purposes of a B/CI, interfacing with neuronal and synaptically processed action-potential-based electrical brain activity alone (without monitoring chemically based information) may be sufficient to facilitate robust human B/CI systems.”
Quote in the paperNot a substantial claim - Interpretationreasoning
Two synaptobots placed at the sites of action potential initiation would ensure proper waveform detection of all action potentials.
“Two synaptobots placed at these sites would ensure proper waveform detection of all action potentials.”
Quote in the paperNot a substantial claim - Interpretationcitation
To achieve a safe, reliable, high-performance B/CI system, a critical mission requirement is the initial establishment of intimate and stable connections to monitor the electrical firing patterns and waveforms of the ∼86 × 10^9 neurons and the ∼2 × 10^14 synapses of the human brain at a suitable repetition rate (400-800 Hz is the reported average maximum range).
“To achieve a safe, reliable, high-performance B/CI system, a critical mission requirement is the initial establishment of intimate and stable connections to monitor the electrical firing patterns and waveforms of the ∼86 × 109 neurons and the ∼2 × 1014 synapses of the human brain at a suitable repetition rate (400–800 Hz is the reported average maximum range) (Wilson, 1999; Contreras, 2004).”
Quote in the paperSubstantial claim0 of 2 sources checked- Rests on an assumption: The human brain contains approximately 86 × 10^9 neurons and 2 × 10^14 synapses.
- Interpretationreasoning
Gliabots would utilize the same probing strategy as endoneurobots and synaptobots.
“For their part, gliabots would utilize the same probing strategy.”
Quote in the paperNot a substantial claim - Interpretationcitation
In cases where there is a complete absence of large BBB junctional gaps, mission-designed strategies, including a combination of cytopenetration, cytolocomotion, and histonatation, would likely permit access to the neuropil.
“However, in cases where there is a complete absence of large BBB junctional gaps, mission-designed strategies, including a combination of cytopenetration, cytolocomotion, and histonatation, would likely permit access to the neuropil (Freitas, 1999b, 2003, 2016).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Freitas, 1999b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Freitas, 2003 source
- cites Freitas, 2016
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationcitation
Optical interrogation of individual cells and organelles with a spatial resolution of ∼100 nm might be enabled through the use of carbon-nanotube-based endoscopes that project from B/CI nanorobots.
“Optical interrogation of individual cells and organelles with a spatial resolution of ∼100 nm might be enabled through the use of carbon-nanotube-based endoscopes that project from B/CI nanorobots (Singhal et al., 2011).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Singhal et al., 2011 source
- Premisecitation
The geometry of the spine neck determines the rate of calcium efflux into the dendrite shaft and hence the degree of elevation of calcium concentrations within the spine head, following NMDAR activation.
“The geometry of the spine neck determines the rate of calcium efflux into the dendrite shaft and hence the degree of elevation of calcium concentrations within the spine head, following n-methyl-D-aspartate receptor (NMDAR) activation (Bloodgood and Sabatini, 2005; Alvarez and Sabatini, 2007; Sheng and Hoogenraad, 2007).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Interpretationreasoning
Total volume displaced by endoneurobots and gliabots would be ∼0.12% of a "typical" ∼14,000 μm3 neuron volume, which is orders of magnitude below the total 1-10% "safe" tissue and organ intrusiveness limit for nanorobots that has been recommended elsewhere.
“Thus, total volume displaced by endoneurobots and gliabots would be ∼0.12% of a “typical” ∼14,000 μm3 neuron volume, which is orders of magnitude below the total 1–10% “safe” tissue and organ intrusiveness limit for nanorobots that has been recommended elsewhere (Freitas, 2003).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Freitas, 2003 source
- Interpretationreasoning
Monitoring all dendritic spine organelles and molecular components is likely unnecessary.
“This provides some level of information redundancy and suggests that monitoring all dendritic spine organelles and molecular components is likely unnecessary.”
Quote in the paperSubstantial claim - Premisecitation
LTD causes AMPA receptor internalization with spine elongation and/or shrinkage of spine heads, due to actin depolymerization.
“LTD causes α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor internalization with spine elongation and/or shrinkage of spine heads, due to actin depolymerization (Bourne and Harris, 2008).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Bourne and Harris, 2008 source
- Interpretationreasoning
Synaptobots may deduce a great deal of useful information subsequent to scanning the gross volume and shape of the spine.
“Synaptobots may deduce a great deal of useful information subsequent to scanning the gross volume and shape of the spine.”
Quote in the paperSubstantial claim - Premisecitation
Events involving LTP and LTD structural changes to dendritic spines can alter spine number, size, shape, and subcellular composition in both immature and mature spines.
“Events involving LTP and LTD structural changes to dendritic spines can alter spine number, size, shape, and subcellular composition in both immature and mature spines (Bourne and Harris, 2008).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Bourne and Harris, 2008 source
- Interpretationreasoning
This information redundancy is expected to significantly reduce synaptobot monitoring tasks.
“This information redundancy is expected to significantly reduce synaptobot monitoring tasks.”
Quote in the paperSubstantial claim - Interpretationreasoning
The synaptobot population represents a more significant neuralnanorobot intrusion on the volume of the human brain.
“The synaptobot population represents a more significant neuralnanorobot intrusion on the volume of the human brain.”
Quote in the paperSubstantial claim - Interpretationcitation
A small percentage of the 0.5 μm3 synaptobots might encounter difficulty in accessing distal axonic and dendritic regions via strictly intracellular navigation.
“Thus, a small percentage of the 0.5 μm3 synaptobots might encounter difficulty in accessing distal axonic and dendritic regions via strictly intracellular navigation.”
Quote in the paperSubstantial claim - Interpretationcitation
A similar volume will be displaced by gliabots, given one 10 μm3 gliabot within each of the 84.6 × 10^9 brain-resident glial cells, displacing another ∼0.06% of brain volume.
“A similar volume will be displaced by gliabots, given one 10 μm3 gliabot within each of the 84.6 × 109 brain-resident glial cells (Azevedo et al., 2009), displacing another ∼0.06% of brain volume.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Azevedo et al., 2009 source
- Premisecitation
The PSD dynamically regulates its components through protein phosphorylation, palmitoylation, local protein translation, the ubiquitin-proteasome system for protein degradation, and redistribution of specific proteins (e.g., CaMKIIα, AMPARs) both entering and leaving the PSD.
“The PSD dynamically regulates its components through protein phosphorylation, palmitoylation, local protein translation, the ubiquitin-proteasome system for protein degradation, and redistribution of specific proteins (e.g., CaMKIIα, AMPARs) both entering and leaving the PSD (Kim and Ko, 2006; Sheng and Hoogenraad, 2007).”
Quote in the paperNot a substantial claim0 of 2 sources checked
- Classified as probably not a substantial claim. 117
- May combine two claims. 67
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.
InterpretationcitationSuch human B/CI systems may dramatically alter human/machine communications, carrying the promise of significant human cognitive enhancement.
“Such human B/CI systems may dramatically alter human/machine communications, carrying the promise of significant human cognitive enhancement”
Quote in the paperNot a substantial claim1 of 2 sources checked- cites Kurzweil, 2014
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Swan, 2016 source
May combine two claims.
InterpretationcitationMedical neuralnanorobots are expected to have the capacity for real-time, non-destructive monitoring of single-neuron and single-synapse neuroelectric activity, local neuropeptide traffic, and other relevant functional data, while also allowing the acquisition of fundamental structural information from neuron surfaces, to enhance the connectome map of a living human brain.
“Medical neuralnanorobots are expected to have the capacity for real-time, non-destructive monitoring of single-neuron and single-synapse neuroelectric activity, local neuropeptide traffic, and other relevant functional data, while also allowing the acquisition of fundamental structural information from neuron surfaces, to enhance the connectome map of a living human brain”
Quote in the paperSubstantial claim1 of 3 sources checked- cites Sporns et al., 2005 source
Split into 2 atoms — 0 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 1 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measured - cites Lu et al., 2009
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Anderson et al., 2011
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationProper synapse formation during childhood provides a substrate for cognition, whereas improper formation or functionality leads to neuro-developmental disorders including mental retardation and autism.
“Proper synapse formation during childhood provides a substrate for cognition, whereas improper formation or functionality leads to neuro-developmental disorders including mental retardation and autism”
Quote in the paperNot a substantial claim1 of 3 sources checked- cites Rollenhagen and Lübke, 2006 source
- cites Mcallister, 2007 source
- cites Rollenhagen et al., 2007 source
The Introduction (pp. 10434–10444) links hippocampal mossy fiber synapses to processing, storage, and recall of spatial information, supporting a general connection between synapses and cognition. It does not establish that synapse formation during childhood provides that substrate or that improper formation or function leads to mental retardation or autism; searches for those developmental and disorder terms found no supporting passage. (LLM, conf=0.79)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThe average number of glial cells in the human brain is estimated to be 84.61 ± 9.83 × 10^9, with the population of glial cells in the neocortex estimated at from 18.2 to 38.6 × 10^9.
“The average number of glial cells in the human brain is estimated to be 84.61 ± 9.83 × 109 (Herculano-Houzel, 2009), with the population of glial cells in the neocortex estimated at from 18.2 to 38.6 × 109”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites Herculano-Houzel, 2009 source
In “The cellular composition of the human brain” (page not provided), the paper reports about 85 billion non-neuronal cells in the adult male human brain, close to the cited estimate. It does not give the stated ±9.83 billion uncertainty there, and non-neuronal cells are not identified specifically as glial cells. The citation is attached to the whole-brain estimate, not the subsequent neocortex range. (LLM, conf=0.85)
Experimental — accuracy not yet measured - cites Karlsen and Pakkenberg, 2011 source
The Results (page unavailable) estimate 18.2 × 10^9 neocortical glial cells in the control group, supporting the lower figure. They do not give 38.6 × 10^9 or an 18.2–38.6 × 10^9 range; the reported range for controls is 15.0–21.8 × 10^9. The whole-brain estimate is explicitly attributed to Herculano-Houzel (2009) in the citing sentence, not to this paper. (LLM, conf=0.87)
Experimental — accuracy not yet measured
May combine two claims.
PremisecitationMagnetoelectric nanoparticles have already been utilized to control intrinsic fields deep within the mouse brain and have permitted the coupling of external magnetic fields to neuronal electric fields.
“Magnetoelectric nanoparticles have already been utilized to control intrinsic fields deep within the mouse brain and have permitted the coupling of external magnetic fields to neuronal electric fields.”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites Yue et al., 2012 source
The Introduction describes how ME nanoparticles could couple externally controlled magnetic fields to local electric activity deep in the brain. But the Abstract and Conclusions identify this as a computational study modeling brain stimulation in a patient with Parkinson’s disease, not an experimental use in mouse brains. The claim overstates the work as an accomplished application and assigns it a mouse setting the paper does not report. (LLM, conf=0.91)
Experimental — accuracy not yet measured - cites Guduru et al., 2015 source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
InterpretationcitationThis computational model may be questionable, however, as computers are based on von Neumann architecture, whereas brain circuits are not; and brains operate in a massively parallel manner, whereas computers do not.
“This computational model may be questionable, however, as computers are based on von Neumann architecture, whereas brain circuits are not; and brains operate in a massively parallel manner, whereas computers do not”
Quote in the paperNot a substantial claim1 of 2 sources checked- cites Nagarajan and Stevens, 2008 source
- cites Whitworth and Ryu, 2008
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationVan den Bosch et al. (2016) estimate that the storage capacity of the World Wide Web doubles every 3 years, with its computational capacity doubling every 1.5 years.
“Van den Bosch et al. (2016) estimate that the storage capacity of the World Wide Web doubles every 3 years, with its computational capacity doubling every 1.5 years.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Van den Bosch et al. (2016) source
The Introduction and the section on estimating search-engine size describe estimates of indexed Web pages, not storage or computational capacity. Searches for both capacities and the claimed three-year and 1.5-year doubling intervals found no passage addressing them in our copy. (LLM, conf=0.75)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe first reported direct transmission of information between two human brains without intervention of motor or peripheral sensory systems occurred in 2014, using a brain-to-brain communication technique referred to as "hyperinteraction".
“The first reported direct transmission of information between two human brains without intervention of motor or peripheral sensory systems occurred in 2014, using a brain-to-brain communication technique referred to as “hyperinteraction””
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Grau et al., 2014 source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationIn 2016, much of the world's Internet traffic was transmitted via undersea fiber-optic cables; the 6,600 km-long MAREA Facebook/Microsoft-owned cable was estimated to carry 160 Tb/sec of data across the Atlantic Ocean.
“In 2016, much of the world’s Internet traffic was transmitted via undersea fiber-optic cables; the 6,600 km-long MAREA Facebook/Microsoft-owned cable was estimated to carry 160 Tb/sec of data across the Atlantic Ocean”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Hecht, 2016 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThere is currently a consensus that neurons and synapses constitute the fundamental electrochemical processing units of the human brain.
“However, there is currently a consensus that neurons and synapses constitute the fundamental electrochemical processing units of the human brain”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites Gkoupidenis et al., 2017 source
- cites Jackman and Regehr, 2017 source
The Abstract (page not provided) says brain information processing relies on connections between neurons, and the section “Information transfer at synapses” describes synapses transmitting information to postsynaptic neurons. This supports their central role in neural processing, but the paper does not specifically characterize neurons and synapses as the fundamental electrochemical processing units of the human brain. The Introduction’s reference to a growing consensus concerns the mechanisms of long-term potentiation, not that characterization. (LLM, conf=0.82)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationQuantum dot fullerenes have been employed for in vitro and in vivo cellular membrane potential measurements.
“For example, quantum dot fullerenes have been employed for in vitro and in vivo cellular membrane potential measurements”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Nag et al., 2017 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationA recently developed ultra-low-power artificial synapse for neural computing has demonstrated the capacity to provide 500 distinct states.
“A recently developed ultra-low-power artificial synapse for neural computing has demonstrated the capacity to provide 500 distinct states”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Van de Burgt et al., 2017 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe use of carbon-nanotube-based electrical stimulation of targets deep within the brain has been proposed as a novel treatment modality for patients with Parkinson's disease and other CNS disorders.
“The use of carbon-nanotube-based electrical stimulation of targets deep within the brain has been proposed as a novel treatment modality for patients with Parkinson’s disease and other CNS disorders”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Srikanth and Kessler, 2012 source
The Parkinson disease section proposes carbon-nanotube-based deep brain stimulation as a possible treatment for Parkinson disease, based on neuronal stimulation findings. It does not propose that specific method for other CNS disorders; its broader discussion concerns nanotechnology generally. Page numbers are unavailable in our copy. (LLM, conf=0.88)
Experimental — accuracy not yet measured
May combine two claims.
PremisecitationThe BBB forms a dynamic, blood-and-brain-regulated, strict physical, transport, metabolic, and immunologic barrier while it is permeable to O2 and CO2 and other gaseous molecules, as well as water and other lipid soluble substances; the barrier is very restrictive to large molecules.
“This is primarily due to the BBB forming a dynamic, blood-and-brain-regulated, strict physical, transport, metabolic, and immunologic barrier while it is permeable to O2 and CO2 and other gaseous molecules, as well as water and other lipid soluble substances (Serlin et al., 2015), the barrier is very restrictive to large molecules.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Serlin et al., 2015 source
May combine two claims.
InterpretationcitationThe human brain might even have more than 100 times higher computational capacity than previously thought, based on the discovery that dendrites may generate nearly 10 times as many electrochemical spikes as do neuron soma, and are hybrids that process both analog and digital signals.
“The human brain might even have more than 100 times higher computational capacity than previously thought, based on the discovery that dendrites may generate nearly 10 times as many electrochemical spikes as do neuron soma, and are hybrids that process both analog and digital signals”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Moore et al., 2017 source
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
FindingcitationNon-invasive neural BMI interface strategies include EEG, MEG, fMRI, and optical strategies including fNIRS.
“Non-invasive neural BMI interface strategies include the use of EEG, magnetoencephalography (MEG), fMRI (Miyawaki et al., 2008) and optical strategies, including fNIRS (Naseer and Hong, 2015).”
Quote in the paperNot a substantial claim2 of 2 sources checkedMay combine two claims.
FindingcitationThe human brain microvasculature is composed of an estimated ∼100 billion capillaries, with a combined surface area of ∼20 m2 and a total length of ∼400 miles.
“Once injected, the neuralnanorobots would have access to the dense microvasculature of human brain, which is composed of an estimated ∼100 billion capillaries, with a combined surface area of ∼20 m2 and a total length of ∼400 miles.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Pardridge, 2011 source
The Introduction’s “Anatomical considerations” section reports more than 100 billion capillaries in the human brain with a total length of approximately 400 miles. It says the capillary endothelium has a much larger surface area than the choroid plexus, but does not give the claimed figure of approximately 20 m². No page number is available in our copy. (LLM, conf=0.88)
Experimental — accuracy not yet measured
May combine two claims.
FindingcitationA four-brain Brainet system dubbed an 'organic computer' always outperformed single-brain computation performance, particularly for discrimination tasks, in which the four brains 'voted' to generate the response.
“A four-brain Brainet system was dubbed an “organic computer” for mimicking simple computer-like operations, such as information-input retention, in a memory-like buffer composed of four serially connected rat brains (Pais-Vieira et al., 2015). This experimental Brainet system always outperformed single-brain computation performance, particularly for discrimination tasks, in which the four brains “”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Pais-Vieira et al., 2015 source
The Results (Brainet for stimulus classification; page unavailable) report that a four-rat Brainet outperformed individual rats on stimulus discrimination and produced an overall classification vote. But the Methods (Adaptive decoding algorithm; page unavailable) describe votes calculated from individual neurons, not a vote cast by each brain. The Discussion says performance was “equal or superior” in all cases, so “always outperformed” overstates the finding. (LLM, conf=0.88)
Experimental — accuracy not yet measured
May combine two claims.
InterpretationcitationA 10 μm3 volume of endoneurobots would egress the bloodstream, traverse the BBB, enter the brain parenchyma, navigate within the neuropil, enter the neuron cell soma, and position themselves intracellularly within the AIS.
“A 10 μm3 volume of endoneurobots (Figure 3) would subsequently egress the bloodstream, traverse the BBB by methods that have been extensively reviewed elsewhere (Freitas, 2016), enter the brain parenchyma, and begin to navigate within the neuropil. Subsequently, they would enter the neuron cell soma and position themselves intracellularly within the AIS (Martins et al., 2016).”
Quote in the paperSubstantial claim1 of 2 sources checked- cites Freitas, 2016
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Martins et al., 2016 source
May combine two claims.
FindingcitationNeural dust power transmission is accomplished ultrasonically, enabling low-efficiency (7%, 11.6 dB) links, yielding ∼500 μW of received power with a 1 mm2 interrogator.
“Power transmission is accomplished ultrasonically to enable low-efficiency (7%, 11.6 dB) links, yielding ∼500 μW of received power (>107 higher than the ∼40 pW EM transmission available at a similar-size scale) with a 1 mm2 interrogator, which may eventually provide ∼10 μm sensing nodes.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Seo et al., 2013 source
The Power Delivery section (p. 5) models an ultrasonic link for a 100 µm node embedded 2 mm into the brain and reports 7% efficiency and approximately 500 µW received with a 1 mm² interrogator. It gives the link efficiency as −11.6 dB, not the claim’s positive 11.6 dB; these are modeled results, not a demonstrated transmission. (LLM, conf=0.88)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
FindingcitationThere are two types of BMI systems: one samples neural activity of a single brain and unidirectionally controls an external device; the other (sensory BMI) includes sensory feedback from the device to the brain.
“There are currently two different types of BMI systems. One type samples the neural activity of a single brain and unidirectionally controls an external device (Lebedev, 2014), while the other type (sensory BMI) includes sensory feedback from the device to the brain (O’Doherty et al., 2011).”
Quote in the paperNot a substantial claim2 of 2 sources checkedMay combine two claims.
FindingcitationSynapses play a crucial role in brain information processing and are involved in learning and memory, long-term and short-term memory storage and deletion, and temporal information processing.
“They play a crucial role in brain information processing (IBM, 2008) and are involved in learning and memory (Black et al., 1990; Bliss and Collingridge, 1993; Holtmaat and Svoboda, 2009; Liu et al., 2012), long-term and short-term memory storage and deletion (Kandel, 2001; Lee et al., 2008), and temporal information processing (Fuhrmann et al., 2002).”
Quote in the paperSubstantial claim0 of 3 sources checkedMay combine two claims.
FindingcitationNeuron-silicon junctions were spontaneously formed using nerve cells of a mammalian brain, permitting direct stimulation of nerve cells.
“Neuron-silicon junctions were spontaneously formed using the nerve cells of a mammalian brain, which permitted direct stimulation of nerve cells (Fromherz and Stett, 1995; Offenhausser, 1996; Vassanelli and Fromherz, 1997; Schätzthauer and Fromherz, 1998).”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
FindingcitationSynapses are either of the 5-25% electrical or 75-95% chemical variety.
“Synapses (either of the 5–25% electrical or 75–95% chemical variety (DeFelipe and Fariñas, 1992) are key components of the neural network that processes information.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites DeFelipe and Fariñas, 1992 source
May combine two claims.
FindingcitationThe BBB is not a perfect barrier, and perijunctional gaps of 0.5 μm have been reported.
“The BBB is not a perfect barrier, and perijunctional gaps of 0.5 μm have been reported (Stewart et al., 1987; Fraser and Dallas, 1993).”
Quote in the paperSubstantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenIt is conceivable that within the next 20-30 years, neuralnanorobotics may be developed to enable a safe, secure, instantaneous, real-time interface between the human brain and biological and non-biological computing systems, empowering brain-to-brain interfaces (BTBI), brain-computer interfaces (BCI), and sophisticated brain/cloud interfaces (B/CI).
“It is conceivable that within the next 20–30 years, neuralnanorobotics may be developed to enable a safe, secure, instantaneous, real-time interface between the human brain and biological and non-biological computing systems, empowering brain-to-brain interfaces (BTBI), brain-computer interfaces (BCI), and, in particular, sophisticated brain/cloud interfaces (B/CI).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based). May combine two claims.
Interpretationnone givenThree species of neuralnanorobots (endoneurobots, gliabots, and synaptobots) could traverse the blood-brain barrier, enter the brain parenchyma, ingress into individual human brain cells, and autoposition themselves at axon initial segments of neurons, within glial cells, and in intimate proximity to synapses.
“Subsequent to navigating the human vasculature, three species of neuralnanorobots (endoneurobots, gliabots, and synaptobots) could traverse the blood–brain barrier (BBB), enter the brain parenchyma, ingress into individual human brain cells, and autoposition themselves at the axon initial segments of neurons (endoneurobots), within glial cells (gliabots), and in intimate proximity to synapses (syn”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenNeuralnanorobotics may enable a B/CI with controlled connectivity between neural activity and external data storage and processing, via direct monitoring of the brain's ∼86 × 10^9 neurons and ∼2 × 10^14 synapses.
“Neuralnanorobotics may also enable a B/CI with controlled connectivity between neural activity and external data storage and processing, via the direct monitoring of the brain’s ∼86 × 109 neurons and ∼2 × 1014 synapses.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenOne promising strategy for enabling a human brain/cloud interface (B/CI) would be based on neuralnanorobotics.
“One promising strategy for enabling such a system, denoted here as a “human brain/cloud interface” (“B/CI”), would be based on technologies referred to here as “neuralnanorobotics.””
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenA stable, secure, real-time system may allow for interfacing the cloud with the human brain.
“A stable, secure, real-time system may allow for interfacing the cloud with the human brain.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenFuture neuralnanorobotics technologies are anticipated to facilitate accurate diagnoses and eventual cures for the ∼400 conditions that affect the human brain.
“Future neuralnanorobotics technologies are anticipated to facilitate accurate diagnoses and eventual cures for the ∼400 conditions that affect the human brain.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenA neuralnanorobotically enabled human B/CI might serve as a personalized conduit, allowing persons to obtain direct, instantaneous access to virtually any facet of cumulative human knowledge.
“A neuralnanorobotically enabled human B/CI might serve as a personalized conduit, allowing persons to obtain direct, instantaneous access to virtually any facet of cumulative human knowledge.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenThrough TS, individuals might experience episodic segments of the lives of other willing participants (locally or remote) to encourage and inspire improved understanding and tolerance among all members of the human family.
“Through TS, individuals might experience episodic segments of the lives of other willing participants (locally or remote) to, hopefully, encourage and inspire improved understanding and tolerance among all members of the human family.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAn ongoing international "Nanofactory Collaboration" headed by Robert Freitas and Ralph Merkle has the primary objective of constructing the world's first nanofactory, which will permit the mass manufacture of advanced autonomous diamondoid neuralnanorobots for both medical and non-medical applications.
“An ongoing international “Nanofactory Collaboration” headed by Robert Freitas and Ralph Merkle has the primary objective of constructing the world’s first nanofactory, which will permit the mass manufacture of advanced autonomous diamondoid neuralnanorobots for both medical and non-medical applications”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites Freitas and Merkle, 2004
- cites Freitas and Merkle, 2006
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Freitas, 2009 source
Probably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenNeuralnanorobots are expected to empower non-medical paradigm-shifting applications, including significant human cognitive enhancement, by providing a platform for direct access to supercomputing storage and processing capabilities and interfacing with artificial intelligence systems.
“Neuralnanorobots are also expected to empower many non-medical paradigm-shifting applications, including significant human cognitive enhancement, by providing a platform for direct access to supercomputing storage and processing capabilities and interfacing with artificial intelligence systems.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenA specialized application of B/CI might be the capacity to engage in fully immersive experiential/sensory experiences, including transparent shadowing (TS).
“A specialized application might be the capacity to engage in fully immersive experiential/sensory experiences, including what is referred to here as “transparent shadowing” (TS).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenWhen intended for use as a component of a B/CI system, carbon-nanotube-based electrical stimulation would also require a two-way information pathway at single-neuron resolution for neuronal electrochemical information recording.
“When intended for use as a component of a B/CI system, carbon-nanotube-based electrical stimulation would also require a two-way information pathway at single-neuron resolution for neuronal electrochemical information recording.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationThe role of synapses as processing units of the human brain is reinforced by the results of computational simulation, which indicate that the computational power of a network is increased using dynamic synapses.
“The role of synapses as processing units of the human brain is reinforced by the results of computational simulation, which indicate that the computational power of a network is increased using dynamic synapses.”
Quote in the paperSubstantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenCurrent commercial 4G networks provide broadband speeds of up to 100 Mbits/sec.
“Current commercial 4G networks provide broadband speeds of up to 100 Mbits/sec.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenA neuralnanorobotics-mediated human B/CI, potentially available within 20-30 years, will require broadband Internet access with extremely high upload and download speeds, compared to today's rates.
“A neuralnanorobotics-mediated human B/CI, potentially available within 20–30 years, will require broadband Internet access with extremely high upload and download speeds, compared to today’s rates.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationSynapses are elements of the neural network that play a critical role in processing information in the brain, being involved in learning, long-term and short-term memory storage and deletion, and temporal information processing.
“Synapses are elements of the neural network that play a critical role in processing information in the brain, being involved in learning, long-term and short-term memory storage and deletion, and temporal information processing”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationUnited States carriers have stated that they plan to deploy 5G technology in 2020 that will eventually bring speeds of around 10 gigabits per second to your phone, more than 600 times faster than typical 4G speeds and 10 times faster than Google Fiber's standard home broadband service.
“United States carriers have stated that they plan to deploy 5G technology in 2020 that will eventually “bring speeds of around 10 gigabits per second to your phone. That’s more than 600 times faster than typical 4G speeds of today’s mobile phones, and 10 times faster than Google Fiber’s standard home broadband service””
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Finley, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
PremisecitationFor intravenous injection, at least 90% of nanoparticles have been observed to be sequestered within tissues and organs prior to reaching the brain, so intra-arterial injections might be more reliable.
“For intravenous injection, at least 90% of nanoparticles have been observed to be sequestered within tissues and organs prior to reaching the brain (Calvo et al., 2001), so intra-arterial injections might be more reliable.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Calvo et al., 2001 source
May combine two claims.
PremisecitationCarbon-nanotube-based electrical stimulation utilizes unidirectional electrical stimulation, which is more precise and avoids the surgical risks associated with deep macroelectrode insertion used with current methods of deep brain stimulation.
“This strategy utilizes unidirectional electrical stimulation, which is more precise and avoids the surgical risks associated with deep macroelectrode insertion, used with current methods of deep brain stimulation”
Quote in the paperSubstantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisenone givenCurrently, invasive and non-invasive brain-computer interfaces and non-invasive brain-to-brain communication systems have already been experimentally demonstrated and are the subject of serious research worldwide.
“Currently, invasive1 and non-invasive brain–computer interfaces and non-invasive brain-to-brain communication systems have already been experimentally demonstrated and are the subject of serious research worldwide.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe human cerebellum and cerebral cortex together hold the vast majority (99.2%) of brain neurons.
“The human cerebellum and cerebral cortex together hold the vast majority (99.2%) of brain neurons”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Azevedo et al., 2009 source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThe average human brain is estimated to contain (86.06 ± 8.2) × 10^9 neurons, with ∼80.2% located in the cerebellum, ∼19% located in the cerebral cortex, and only ∼0.8% located throughout the rest of the brain.
“At the cellular level, the average human brain is estimated to contain (86.06 ± 8.2) × 109 neurons, with ∼80.2% (69.03 ± 6.65 × 109 neurons) located in the cerebellum, ∼19% (16.34 ± 2.17 × 109 neurons) located in the cerebral cortex, and only ∼0.8% (0.69 ± 0.12 × 109 neurons) located throughout the rest of the brain”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Azevedo et al., 2009 source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationAccording to one study, global Internet traffic in 2021 will be equivalent to 127 times the volume of the entire global Internet in 2005; globally, Internet traffic will reach 30 GB per capita by 2021, up from 10 GB per capita in 2016.
“According to one study, “Global Internet traffic in 2021 will be equivalent to 127 times the volume of the entire global Internet in 2005. Globally, Internet traffic will reach 30 GB per capita by 2021, up from 10 GB per capita in 2016””
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Cisco, 2017
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
PremisecitationSynapses, numbering (2.42 ± 0.29) × 10^14 in the average human brain, are collectively estimated to process information at spiking rates of (4.31 ± 0.86) × 10^15 spikes/sec, empowering the human brain to process data at (5.52 ± 1.13) × 10^16 bits/sec.
“In addition, synapses, numbering (2.42 ± 0.29) × 1014 in the average human brain, are collectively estimated to process information at spiking rates of (4.31 ± 0.86) × 1015 spikes/sec, empowering the human brain to process data at (5.52 ± 1.13) × 1016 bits/sec”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Martins et al., 2012 source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisenone givenThe human brain comprises a remarkable information storage and processing system that possesses an extraordinary computation-per-volume efficiency, with an average weight of 1400 g and a volume of ∼1350 cm3, contained within an "average" intracranial volume of ∼1,700 cm3.
“The human brain comprises a remarkable information storage and processing system that possesses an extraordinary computation-per-volume efficiency, with an average weight of 1400 g and a volume of ∼1350 cm3, contained within an “average” intracranial volume of ∼1,700 cm3.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationAs of October 2018, the average Internet peak connection speed was 189.33 Mbps in Singapore and 100.07 Mbps in the United States.
“As of October 2018, the average Internet peak connection speed was 189.33 Mbps in Singapore and 100.07 Mbps in the United States”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Kemp, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenThe primary challenge for worldwide global cloud-based information processing technologies is the speed of access to the system, or latency.
“However, the primary challenge for worldwide global cloud-based information processing technologies is the speed of access to the system, or latency.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationThe human brain's functional action potential based information is estimated as 5.52 × 10^16 bits/sec, with a brain power output estimated at 15-25 W and a power density of 1.1-1.8 × 10^4 W/m3 at an operating temperature of 37.3°C.
“The human brain’s functional action potential based information is estimated as 5.52 × 1016 bits/sec (Martins et al., 2012), with a brain power output estimated at 15–25 W and a power density of 1.1–1.8 × 104 W/m3 at an operating temperature of 37.3°C”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Martins et al., 2012 source
- cites Freitas, 1999b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationWhile the whole-brain glia/neuron ratio is ∼1:1, there are significant differences between brain domains: the glia/neuron ratio of the cerebral cortex is 3.72:1, but only 0.23:1 in the cerebellum; the basal ganglia, diencephalon, and brainstem have a combined ratio of 11.35:1.
“While the whole-brain glia/neuron ratio is ∼1:1, there are significant differences between brain domains. For example, the glia/neuron ratio of the cerebral cortex is 3.72:1 (60.84 billion glia; 16.34 billion neurons) but only 0.23:1 (16.04 billion glia; 69.03 billion neurons) in the cerebellum; the basal ganglia, diencephalon, and brainstem have a combined ratio of 11.35:1”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Azevedo et al., 2009 source
Probably not a substantial claim: may not pass S1 (asserted), S2 (checkable), S3 (load-bearing).
InterpretationcitationSince it has been shown that certain customized nanoparticles may damage dopaminergic and serotoninergic systems, a further detailed analysis of the biodistribution and metabolism of nanoparticles will be required.
“Since it has been shown that certain customized nanoparticles may damage dopaminergic and serotoninergic systems, a further detailed analysis of the biodistribution and metabolism of nanoparticles will be required.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Cupaioli et al., 2014 source
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenReal-time monitoring of the whole human brain (by placing neuralnanorobots within each neuron and nearby synaptic connections to record/transmit data from localized neuron and synapse spiking) may provide redundant data that might be employed in the development of validation protocols.
“Real-time monitoring of the whole human brain (by placing neuralnanorobots within each neuron and nearby synaptic connections to record/transmit data from localized neuron and synapse spiking) may provide redundant data that might be employed in the development of validation protocols.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAnother approximation, based on combining estimates for the different brain regions, produced a similar value of 94.2 ± 11.3 × 10^9 neurons for the whole human brain.
“Another approximation, based on combining estimates for the different brain regions, produced a similar value of 94.2 ± 11.3 × 109 neurons for the whole human brain”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Martins et al., 2012 source
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenSmall peptides may cross the BBB by either non-specific fluid-phase endocytosis or receptor-mediated transcytosis (RMT) mechanisms.
“However, small peptides may cross the BBB by either non-specific fluid-phase endocytosis or receptor-mediated transcytosis (RMT) mechanisms.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationThe ratio of glia to neurons likely has functional relevance and varies between different brain regions.
“The ratio of glia to neurons likely has functional relevance (Nedergaard et al., 2003) and varies between different brain regions.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Nedergaard et al., 2003 source
May combine two claims.
PremisecitationSeveral neuronal noise sources influence the reliability and precision of neuronal signaling, so stimulus-response functions are sometimes unreliable and are dissociated from what is being encoded via spike activity.
“However, several neuronal noise sources influence the reliability and precision of neuronal signaling, so stimulus-response functions are sometimes unreliable and are dissociated from what is being encoded via spike activity”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Bialek and Rieke, 1992 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationSynapse loss, as occurs in Alzheimer's patients, is intimately associated with cognitive decline.
“Synapse loss, as occurs in Alzheimer’s patients, is intimately associated with cognitive decline”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe global storage capacity of Internet data centers in 2018 was 1450 exabytes.
“The global storage capacity of Internet data centers in 2018 was 1450 exabytes”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Statistica, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
InterpretationcitationThe global economic impact of cloud-based information processing over the next few decades may be at least an order of magnitude higher once cloud services are combined in previously unimagined ways, disrupting entire industries.
“The global economic impact of cloud-based information processing over the next few decades may be at least an order of magnitude higher once cloud services are combined in previously unimagined ways, disrupting entire industries”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Miraz et al., 2015
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationA brief quantification of the brain's constituents includes ∼1,350 cm3 (∼75%) brain cells, ∼200 cm3 (15%) blood, and up to ∼150 cm3 (10%) of cerebrospinal fluid.
“A brief quantification of the brain’s constituents and operational parameters includes ∼1,350 cm3 (∼75%) brain cells, ∼200 cm3 (15%) blood, and up to ∼150 cm3 (10%) of cerebrospinal fluid”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Rengachary and Ellenbogen, 2005
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe raw computational power of the human brain has been estimated to range from 10^13 to 10^16 operations/sec.
“The raw computational power of the human brain has been estimated to range from 1013 to 1016 operations/sec”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Merkle, 1989
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
InterpretationreasoningDendrites comprise more than 90% of neural tissue, so knowing that they are much more active than the soma would fundamentally alter our understanding of how the brain processes information.
“Dendrites comprise more than 90% of neural tissue, so knowing that they are much more active than the soma would fundamentally alter our understanding of how the brain processes information.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenConventional fiber-optic cables transfer trillions of bits/sec between massive data centers.
“Conventional fiber-optic cables transfer trillions of bits/sec between massive data centers.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe current round-trip latency rate for transatlantic loops between New York and London is ∼90 ms.
“For example, the current round-trip latency rate for transatlantic loops between New York and London is ∼90 ms”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Verizon, 2014
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
Premisenone givenAs of November 2018, the fastest supercomputer worldwide was Summit, developed at the United States Oak Ridge National Laboratory (Tennessee), with 122.3 petaflops on the High Performance Linpack (HPL) benchmark.
“As of November 2018, the fastest supercomputer worldwide was Summit, developed at the United States Oak Ridge National Laboratory (Tennessee), with 122.3 petaflops on the High Performance Linpack (HPL) benchmark.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenWithin the next few decades, neuralnanorobotics may enable a non-destructive, real-time, ultrahigh-resolution interface between the human brain and external computing platforms such as the "cloud."
“Within the next few decades, neuralnanorobotics may enable a non-destructive, real-time, ultrahigh-resolution interface between the human brain and external computing platforms such as the “cloud.””
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenThe monitoring of synapses is expected to be essential for a stable and robust fully functional real-time B/CI.
“The monitoring of synapses is expected to be essential for a stable and robust fully functional real-time B/CI.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based). May combine two claims.
Interpretationnone givenThese data would be transferred from the synaptobots to corresponding endoneurobots, then to the previously installed in vivo high-speed nanofiber-optic network, for subsequent transfer to the central units responsible for transmitting data to an external supercomputer.
“These data would be transferred from the synaptobots to corresponding endoneurobots (in some cases, with communications and other support from nearby gliabots). Once the data is received by the endoneurobots, it would proceed to the previously installed in vivo high-speed nanofiber-optic network, for subsequent transfer to the central units that are responsible for transmitting data to an external”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationnone givenNeuralnanorobotics may be massively distributed, whereas surgically introduced neural implants must be positioned in one or several specific locations.
“Neuralnanorobotics may also be massively distributed, whereas surgically introduced neural implants must be positioned in one or several specific locations.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenCurrent technological trajectories appear to be converging toward the creation of systems that will have the capacity to empower a human B/CI.
“Current technological trajectories appear to be converging toward the creation of systems that will have the capacity to empower a human B/CI.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenAn optimal ingress strategy for all species of neuralnanorobots may employ the most rapid route to the human brain through the vasculature.
“An optimal ingress strategy for all species of neuralnanorobots may employ the most rapid route to the human brain through the vasculature.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenEndoneurobots are autonomous neuron-resident neuralnanorobots that interface with all ∼86 × 10^9 human-brain neurons at the AIS to directly monitor and interact with action-potential-based electrically processed information.
“More specifically, endoneurobots are autonomous neuron-resident neuralnanorobots that interface with all ∼86 × 109 human–brain neurons at the AIS to directly monitor and interact with action-potential-based electrically processed information.”
Quote in the paperNot a substantial claim- Rests on an assumption: The human brain contains approximately 86 × 10^9 neurons and 2 × 10^14 synapses.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
InterpretationreasoningA process akin to diapedesis might be employed by B/CI neuralnanorobots to traverse the BBB.
“A process akin to “diapedesis” (the movement of leukocytes out of the circulatory system and toward the site of tissue damage or infection) might be employed by B/CI neuralnanorobots to traverse the BBB.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based). May combine two claims.
InterpretationreasoningNeuralnanorobotics technologies may possess the appropriate scale for optimally enabling BCI, exhibiting suitable mobility, being minimally invasive, imparting negligible localized tissue damage, and possessing robust monitoring capabilities over distinct information channels without requiring conventional surgical implantation.
“Conversely, neuralnanorobotics technologies may possess the appropriate scale for optimally enabling BCI, exhibiting suitable mobility, being minimally invasive, imparting negligible localized tissue damage, and possessing robust monitoring capabilities over distinct information channels without requiring conventional surgical implantation.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based). May combine two claims.
InterpretationreasoningAll these data would be continually processed at sub-millisecond resolution, enabling a virtually real-time data stream between the human brain and the cloud.
“All these data would be continually processed at sub-millisecond resolution, enabling a virtually real-time data stream between the human brain and the cloud.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
InterpretationreasoningAny technology capable of establishing a long-term and non-destructive, real-time human interface with the cloud must embody: (1) ultrahigh-resolution mobility, (2) autonomous or semi-autonomous activity, (3) non-intrusive ingress/egress into/from the human body, and (4) supplying sufficient and robust information transfer bandwidth for interfacing with external supercomputing systems.
“However, since the human brain possesses cellular (neuron) and sub-cellular (synapse) processing elements, any technology that is capable of establishing a long-term and non-destructive, real-time human interface with the cloud must embody the following capabilities: (1) ultrahigh-resolution mobility, (2) autonomous or semi-autonomous activity, (3) non-intrusive (ideally, physiologically impercept”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenOne of the other potential applications of syringe-injectable mesh nanoelectronics is in vivo multiplexed neural network recording.
“One of the other potential applications of syringe-injectable mesh nanoelectronics is in vivo multiplexed neural network recording.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationNeuralnanorobots could monitor relevant functional and structural connectome data, functional action-potential-based electrical information processing within synapses and neurons, and synaptic and neuronal structural changes associated with processing such electrolytic-based functional data.
“Neuralnanorobots could monitor relevant functional and structural connectome data, functional- action-potential-based electrical information processing that occurs within synapses and neurons, and synaptic and neuronal structural changes associated with processing such electrolytic-based functional data (Seung, 2011).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Seung, 2011 source
Probably not a substantial claim: may not pass S4 (based). May combine two claims.
Interpretationnone givenSynaptobots would reside in the proper monitoring position within the neurons, in close proximity to presynaptic or postsynaptic structures, and monitor the action potentials and the structural changes initiated by the action-potential-based functional data.
“The synaptobots would reside in the proper monitoring position within the neurons, in close proximity to presynaptic or postsynaptic structures. Once in place, these neuralnanorobots would monitor the action potentials and the structural changes initiated by the action-potential-based functional data.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
Interpretationnone givenSynaptobots would enter the human body via the bloodstream, cross the BBB, enter the brain parenchyma, navigate within the neuropil, enter the neuron cell soma, and proceed intracellularly into the pre-synaptic or post-synaptic structure of a synapse.
“The synaptobots would also enter the human body via the bloodstream, cross the BBB (possibly assisted by auxiliary transport nanorobots), enter the brain parenchyma, commence navigation within the neuropil, enter the neuron cell soma, and then proceed intracellularly into the pre-synaptic or post-synaptic structure of a synapse.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationnone givenSynaptobots, the most diminutive (0.5 μm3) of the three types of neuralnanorobots, are responsible for monitoring synapses.
“Synaptobots (Figure 5), the most diminutive (0.5 μm3) of the three types of neuralnanorobots, are responsible for monitoring synapses, which are relevant sub-cellular structures of the human brain.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenSynaptobots are autonomous neuron-resident neuralnanorobots that might employ multiple flexible stalk-mounted nanosensors to interface with each of the ∼2 × 10^14 synapses of the human brain to directly monitor and interact with synaptically processed and stored information.
“Synaptobots are autonomous neuron-resident neuralnanorobots that might employ multiple flexible stalk-mounted nanosensors to interface with each of the ∼2 × 1014 synapses of the human brain to directly monitor and interact with synaptically processed and stored information.”
Quote in the paperNot a substantial claim- Rests on an assumption: The human brain contains approximately 86 × 10^9 neurons and 2 × 10^14 synapses.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenNeuralnanorobots might be transdermally injected, after which they would navigate the vasculature and anchor to the endothelial cells of the BBB.
“Neuralnanorobots might be transdermally injected, after which they would navigate the vasculature and anchor to the endothelial cells of the BBB.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
InterpretationreasoningCurrent techniques, whether in present-day or extrapolated future forms, appear to be unscalable and incapable of fulfilling all of the temporal or spatial resolution requirements necessary for a properly comprehensive fully functional human B/CI.
“Current techniques, whether in present-day or extrapolated future forms, appear to be unscalable and incapable of fulfilling all of the temporal or spatial resolution requirements necessary for a properly comprehensive fully functional human B/CI.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenOnce arrived at their designated neurons, the endoneurobots would autolocate and settle into their monitoring positions, intimately yet unobtrusively.
“Once arrived at their designated neurons, the endoneurobots would autolocate and settle into their monitoring positions, intimately yet unobtrusively.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based). May combine two claims.
Interpretationnone givenSynaptobots would detect virtually all of the synaptically processed action potentials and their waveforms and report synaptically processed spikes into the data handling system.
“Synaptobots would detect virtually all of the synaptically processed action potentials and their waveforms and report synaptically processed spikes into the data handling system.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningThese shortcomings suggest that neuralnanorobotics may be a preferred solution to the formidable challenges ahead in the development of B/CI technologies.
“These shortcomings suggest that neuralnanorobotics may be a preferred solution to the formidable challenges ahead in the development of B/CI technologies.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenShould large BBB junctional gaps be detected by the neuralnanorobots, they may be exploited to penetrate within the neuropil.
“Should large BBB junctional gaps be detected by the neuralnanorobots, they may be exploited to penetrate within the neuropil.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationThe PSD consists of a disk-like structure with an average diameter of 300-400 nm (range 200-800 nm), a thickness of 30-60 nm, volume of ∼7.5 × 10^6 nm3, and mass of ∼1.1 GDa.
“The “typical” PSD consists of a disk-like structure with an average diameter of 300–400 nm (range 200–800 nm), a thickness of 30–60 nm (Baude et al., 1993; Rácz et al., 2004; Okabe, 2007; Sheng and Hoogenraad, 2007), volume of ∼7.5 × 106 nm3, and mass of ∼1.1 GDa (Chen et al., 2005).”
Quote in the paperNot a substantial claim0 of 3 sources checkedMay combine two claims.
InterpretationreasoningSince action potentials might be initiated in different subcellular compartments, the endoneurobots would be anchored at the AIS, where they would monitor most action potentials.
“Since action potentials might be initiated in different subcellular compartments, the endoneurobots would be anchored at the AIS (the most likely location for the initiation of action potentials), where they would monitor most action potentials.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationnone givenEach of the neural electrodes presently employed interfaces with very diminutive and specific brain regions, and are always confined to the surface areas of highly localized domains.
“Each of these electrodes interface with very diminutive and specific brain regions, and are always confined to the surface areas of highly localized domains.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
Interpretationnone givenGliabots are glia-resident autonomous neuralnanorobots that are endowed with the capacity to monitor human-brain glial cells and may serve as supportive infrastructure elements of the system.
“Gliabots are glia-resident autonomous neuralnanorobots that are endowed with the capacity to monitor human–brain glial cells and may further serve as supportive infrastructure elements of the system.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationEndoneurobots and synaptobots might employ a tactile scanning probe to image the surrounding membrane surface area of (1.4 μm)2 in ∼2 sec at ∼1 nm2 resolution, or ∼50 s to ∼0.2 nm resolution, assuming a scan rate of ∼10^6 pixels/s.
“For the monitoring of neuronal structural changes (some of these triggered by the processing of action potentials), once they are securely anchored to the internal neuron membrane surface (with “typical” neurons having a “volume of 14,000 μm3 or (∼24 μm)3), endoneurobots and synaptobots might employ a tactile scanning probe to image the surrounding membrane surface area of (1.4 μm)2 in ∼2 sec at ∼”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Freitas, 1999b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S4 (based).
InterpretationreasoningNeuralnanorobots would assist with the prediction of neurotransmitter bursts that traverse each synaptic gap.
“Consequently, neuralnanorobots would assist with the prediction of neurotransmitter bursts that traverse each synaptic gap.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationcitationSuch a capacity may elevate human collaboration, understanding, respect, and empathy to previously unimaginable levels.
“Such a capacity may be anticipated to elevate human collaboration, understanding, respect, and empathy to previously unimaginable levels (Domschke and Boehm, 2014).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Domschke and Boehm, 2014
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
InterpretationreasoningTS capability might eventually lead to the minimization or elimination of most armed conflict.
“perhaps eventually leading to the minimization or elimination of most armed conflict.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThe degradation of PSD proteins via the ubiquitin-proteasome system also sculpts the PSD structure and plays a primary role in synaptic plasticity.
“The degradation of PSD proteins via the ubiquitin-proteasome system (Bingol and Schuman, 2006) also sculpts the PSD structure and plays a primary role in synaptic plasticity.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Bingol and Schuman, 2006 source
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenUnder strict protocols, accredited spatial hosts would agree to allow single or multiple attendees, conceivably numbering in the millions, to literally experience portions of their life experiences over a predetermined timeline or schedule.
“Under strict protocols, accredited spatial hosts would agree to allow single or multiple attendees (conceivably numbering in the millions) to literally experience portions of their life experiences over a predetermined timeline/schedule.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.
InterpretationreasoningTS may hold potential to facilitate understanding of the experiences of other people and to significantly increase empathy.
“TS may hold potential to facilitate understanding of the experiences of other people and to significantly increase empathy.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenThe full sensorial realm, including physical presence, tactile sensations, olfactory, visual, tastes, and auditory, would be experienced by TS attendees as if they inhabited the body of the spatial host.
“The full sensorial realm (e.g., physical presence, tactile sensations, olfactory, visual, tastes, and auditory) would be experienced by the attendees, as if they inhabited the body of the spatial host.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
InterpretationreasoningThis may translate to the establishment of a very brief, approximately millisecond, latency from spatial host to attendee to allow for virtually instantaneous self-speak screening.
“This may translate to the establishment of a very brief (∼millisecond) latency, from spatial host to attendee, to allow for this virtually instantaneous self-speak screening.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.
InterpretationreasoningThese enhancements may assist humanity to adapt emergent artificial intelligence systems as human-augmentation technologies, facilitating the mitigation of new challenges to the human species.
“These enhancements may assist humanity to adapt emergent artificial intelligence systems as human-augmentation technologies, facilitating the mitigation of new challenges to the human species.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenThe host will have no mental or physical perception that they are being shadowed by the attendees.
“The host will have no mental or physical perception that they are being “shadowed” by the attendees.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningTagging all 2.42 × 10^14 synapses in the human brain with one robot each would require 24-242 × 10^12 synaptobots at 0.5 μm3 per robot, giving a total fleet volume of 1.2-12 × 10^13 μm3 or 12-120 cm3 and representing ∼0.9-9% of total brain volume-just within the "safe" tissue and organ intrusiveness limits.
“Tagging all 2.42 × 1014 synapses in the human brain with one robot each would require 24–242 × 1012 synaptobots at 0.5 μm3 per robot, giving a total fleet volume of 1.2–12 × 1013 μm3 or 12–120 cm3 and representing ∼0.9–9% of total brain volume-just within the “safe” tissue and organ intrusiveness limits.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationLonger-term changes in the PSD structure and composition (from hours to days) involve altered protein synthesis, either within the neuronal cell body, or dendrites.
“Longer-term changes in the PSD structure and composition (from hours to days) involve altered protein synthesis, either within the neuronal cell body, or dendrites (Sheng and Hoogenraad, 2007).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Sheng and Hoogenraad, 2007 source
Probably not a substantial claim: may not pass S4 (based). May combine two claims.
Interpretationnone givenTS attendees would retain their own identities and experience real-time live-feed full immersion into a portion of the host's life experiences.
“Although the attendees would retain their own identities and experience real-time live-feed full immersion into a portion of the host’s life experiences”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenTS sessions would offer exponentially higher resolution in every respect than today's seminars or lecture series.
“However, these TS sessions would offer exponentially higher resolution in every respect.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenThese display modes may include optional text, imagery, and streaming video displays superimposed at customizable locations within the user's field of vision.
“These may include optional text, imagery, and streaming video displays that are superimposed at customizable locations within the user’s field of vision.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
InterpretationreasoningVia TS, all knowledge-based queries and responses, as well as fully immersive experiences within avatars and other users, could include an optional toggle mode.
“It may be likely that via TS, all knowledge-based queries and responses, as well as fully immersive experiences within avatars and other users, could include an optional toggle mode.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
InterpretationreasoningCross-gender TS experiences might impact real-life relationships between genders, due to increased empathy and understanding.
“Cross-gender experiences might impact real-life relationships between genders, due to increased empathy and understanding.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenThere will likely be several display modes available to B/CI users once the technology matures.
“Although beyond the scope and space constraints of this paper, we acknowledge that there will likely be several “display modes” available to B/CI users once the technology matures.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationcitationBy default, TS attendees might be completely blocked from any access to the thoughts, emotions, or self-speak of their spatial hosts for privacy.
“Although they would perceive the vocal instructions of the host, to temporally experience exactly what the spatial host is experiencing, for the sake of personal privacy, attendees might, by default, be completely blocked from any access to the thoughts, emotions, or self-speak of their spatial hosts (Ford, 2010).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Ford, 2010
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
InterpretationreasoningMajority ethnic groups might be more sensitized to racism against minority ethnic groups after experiencing it through TS sessions.
“For example, perhaps those of majority ethnic groups might be more sensitized with the issue of racism against those of minority ethnic groups, once they “experience” it for themselves through TS sessions.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
InterpretationreasoningWhen this mode is engaged, internalized visualizations might be projected onto a float screen superimposed within the user's field of vision, where the float screen can be made more prominent via dynamic fading.
“When this mode is engaged, internalized visualizations might be projected as on to a “float screen” that can be superimposed within the user’s field of vision, where the float screen can be made more prominent in the user’s experience via dynamic fading.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.
InterpretationreasoningFor AI assessment of self-speak, the self-speak would have to be processed in real time or on the fly, because records of such self-speak would most likely be considered highly unethical.
“For this assessment to take place via AI, the self-speak in question would have to somehow be processed in real time/on the fly, as any records of such in any form, would most likely be considered as highly unethical.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
InterpretationreasoningOnce established and potentially utilized by a growing demographic, TS capability might have strong potential for conveying profound beneficial implications for human advancement across multiple domains.
“Once established and potentially utilized by a growing demographic, this capability might have strong potential for conveying profound beneficial implications for human advancement across multiple domains”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
InterpretationreasoningIn cases of unpleasant pain, the attendee might activate an instantaneous default auto-disengagement protocol once a particular physiological threshold is perceived by the B/CI system.
“For example, in cases of unpleasant pain, the attendee might activate an instantaneous default auto-disengagement protocol once a particular physiological threshold is perceived by the B/CI system.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.
InterpretationreasoningHuman B/CI systems mediated by neuralnanorobots might also upgrade mutual human understanding and collaboration by making it possible to engage humans in TS experiences, which could enable considerably improved understanding and tolerance among all members of our diverse human family.
“Human B/CI systems mediated by neuralnanorobots might also upgrade mutual human understanding and collaboration by making it possible to engage humans in TS experiences, which could enable considerably improved understanding and tolerance among all members of our diverse and amazing human family.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenIt is likely that any self-speak of a spatial host will include their most private and intimate thoughts.
“However, it is likely that any self-speak of a spatial host will include their most private and intimate thoughts.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based). May combine two claims.
Premisenone givenNeuralnanorobotics strategies involve direct, comprehensive monitoring of the approximately 86 × 10^9 neurons of the human brain, as well as its approximately 2 × 10^14 synapses and approximately 84 × 10^9 glial cells.
“Neuralnanorobotics strategies involve the direct, comprehensive monitoring of the ∼86 × 109 neurons of the human brain, as well as its ∼2 × 1014 synapses and ∼84 × 109 glial cells.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenThere exists a clear and strong association between synapse bouton size/shape and the organellar and macromolecular changes that occur within the bouton.
“There exists a clear and strong association between synapse bouton size/shape and the organellar and macromolecular changes that occur within the bouton.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationExperimental data has provided a wide range of measured human intracranial volumes (1152-1839 cm3) and total average cerebral spinal fluid (CSF) volume (82-125.3 cm3), with a total brain-cell parenchyma volume of 1319 cm3, including 489 cm3 of white matter and 786 cm3 of gray matter.
“Experimental data has provided a wide range of measured human intracranial volumes (1152–1839 cm3) and total average cerebral spinal fluid (CSF) volume (82–125.3 cm3), with a total brain-cell parenchyma volume of 1319 cm3, including 489 cm3 of white matter and 786 cm3 of gray matter (Vaidyanathana et al., 1997; Nopoulos et al., 2000).”
Quote in the paperSubstantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenNeuralnanorobotically empowered B/CI technologies accompanied by supercomputing might permit users to experience fully immersive, real-time episodes of any willing human participant's life via non-intrusive Transparent Shadowing (TS).
“Neuralnanorobotically empowered B/CI technologies accompanied by supercomputing technologies might permit users to experience fully immersive, real-time episodes of the lives of any willing human participant on the planet, via non-intrusive “Transparent Shadowing (TS).””
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
InterpretationreasoningAnyone on the planet who is B/CI enabled might be engaged as either a spatial host or an attendee.
“Hence, in essence, anyone on the planet (who is B/CI enabled) might be engaged as either a spatial host or an attendee.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenTS capability might assist with the further development of human collaboration and empathy.
“possibly assisting with the further development of human collaboration and empathy”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.
InterpretationreasoningExperiencing episodes of the lives of those in other cultures and ethnic groups could promote cross-cultural understanding and tolerance, improving prospects for the reduction of hatred and racism.
“Experiencing episodes of the lives of those in other cultures and ethnic groups could promote cross-cultural understanding and tolerance, improving prospects for the reduction of hatred and racism.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenNeuralnanorobotic entities would transmit the nominal approximately 5 × 10^16 bits/sec of synaptically processed electronic information, encoded in approximately 4 × 10^15 spikes/sec flowing within the entire living human brain, wirelessly via a nanorobotic auxiliary 30 cm3 volume nanoscale fiber-optic system capable of handling approximately 10^18 bits/sec.
“Neuralnanorobotic entities would transmit the nominal ∼5 × 1016 bits/sec of synaptically processed electronic information, encoded in ∼4 × 1015 spikes/sec flowing within the entire living human brain, wirelessly via a nanorobotic auxiliary 30 cm3 volume nanoscale fiber-optic system that is capable of handling ∼1018 bits/sec.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenTS guests would have no capacity to control any aspect of the host.
“these guests would have no capacity to control any aspect of the host.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenPotential physiological transference issues may arise when two or more individuals are engaged in shared TS activities.
“Potential physiological transference issues may arise when two or more individuals are engaged in shared TS activities.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe activity-dependent modification of PSD proteins occurring over timescales of seconds to hours is believed to underlie plasticity processes such as LTP and LTD.
“For instance, the activity-dependent modification of PSD proteins occurring over timescales of seconds to hours is believed to underlie plasticity processes such as LTP and LTD (Sheng and Hoogenraad, 2007).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Sheng and Hoogenraad, 2007 source
Probably not a substantial claim: may not pass S4 (based).
Interpretationnone givenThree proposed classes of neuralnanorobots (endoneurobots, gliabots, and synaptobots) may employ approximately 3375 nm3 FET-based neuroelectric nanosensors to detect and monitor virtually all individual action potentials and their waveforms.
“Three proposed classes of neuralnanorobots (endoneurobots, gliabots, and synaptobots) may employ ∼3375 nm3 FET-based neuroelectric nanosensors to detect and monitor virtually all individual action potentials and their waveforms.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationSystems have performed well during acute recordings, but failed to function reliably over clinically relevant timelines, the result of brain tissue reaction against implants.
“Systems have performed well during acute recordings, but failed to function reliably over clinically relevant timelines, the result of brain tissue reaction against implants, making biocompatibility of implanted BCI systems a primary concern in current device design (Polikov et al., 2005; Winslow and Tresco, 2010; Tresco and Winslow, 2011).”
Quote in the paperSubstantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S4 (based).
InterpretationreasoningIn TS, an individual might literally experience another person's life, through their own eyes, for a predetermined duration via an "extra life" session.
“In TS, an individual might literally experience another person’s life, through their own eyes, for a predetermined duration via an “extra life” session.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.
InterpretationreasoningIt might transition totally immersive virtual and augmented realities to unprecedented levels, allowing for more meaningful experiences and fuller or richer expression for, and between, users.
“Further, it might transition totally immersive virtual and augmented realities to unprecedented levels, allowing for more meaningful experiences and fuller/richer expression for, and between, users.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationIn experimental work, dendritic spines that received LTP induction increased in volume, from 50 to 200%, with this increase persisting for more than 1 h following stimulation.
“In experimental work, dendritic spines that received LTP induction increased in volume, from 50 to 200% (Alvarez and Sabatini, 2007), with this increase persisting for more than 1 h following stimulation (Alvarez and Sabatini, 2007).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Alvarez and Sabatini, 2007 source
Probably not a substantial claim: may not pass S2 (checkable), S4 (based).
InterpretationreasoningGiven biologically constrained cognitive abilities, the human mind cannot keep pace with the increasingly rapid generation of human knowledge.
“Given our biologically constrained cognitive abilities, the impossibility of the human mind to keep pace with the increasingly rapid generation of human knowledge is evident.”
Quote in the paperNot a substantial claim- Rests on an assumption: Human knowledge is being digitized at an accelerated exponential pace for storage and processing in the cloud.
May combine two claims.
InterpretationreasoningDuring B/CI operations, one ∼10 μm3 endoneurobot would reside within every brain resident neuron, giving a total endoneurobot volume of 0.86 cm3, or only ∼0.06% of total brain volume.
“During B/CI operations, one ∼10 μm3 endoneurobot would reside within every brain resident neuron, giving a total endoneurobot volume of 0.86 cm3, or only ∼0.06% of total brain volume.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
InterpretationreasoningWith neuralnanorobotically enabled B/CI, individuals might engage in TS of voluntary or remunerated spatial hosts.
“With neuralnanorobotically enabled B/CI, individuals might engage in the TS of voluntary or remunerated “spatial hosts.””
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.
InterpretationreasoningA human B/CI system mediated by neuralnanorobotics could empower individuals with instantaneous access to all cumulative human knowledge available in the cloud and significantly improve human learning capacities and intelligence.
“A human B/CI system mediated by neuralnanorobotics could empower individuals with instantaneous access to all cumulative human knowledge available in the cloud and significantly improve human learning capacities and intelligence.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThis may permit real-time brain-state monitoring and data extraction into an external supercomputer that communicates directly with the cloud.
“This may permit real-time brain-state monitoring and data extraction into an external supercomputer that communicates directly with the cloud.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S4 (based).
InterpretationreasoningAn eventual shift in gender attitudes could lead to decreased gender-related and domestic violence.
“It might be possible that an eventual shift in gender attitudes could lead to decreased gender-related and domestic violence.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
InterpretationreasoningMinorities who experience a majority host might come to realize that many actions perceived by them as purposeful racism were entirely unintentional.
“Similarly, minorities who experience a majority host might come to realize that many actions perceived by them as purposeful racism were entirely unintentional.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationRecent evidence points toward the rapid exchange of PSD proteins, such as AMPARS and PSD-95, even between neighboring synapses under steady-state conditions.
“Remarkably, recent evidence points toward the rapid exchange of PSD proteins, such as AMPARS and PSD-95, even between neighboring synapses under steady-state conditions (Sheng and Hoogenraad, 2007).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Sheng and Hoogenraad, 2007 source
The paper relies on this without support.
The human brain contains approximately 86 × 10^9 neurons and 2 × 10^14 synapses.
“More specifically, endoneurobots are autonomous neuron-resident neuralnanorobots that interface with all ∼86 × 109 human–brain neurons at the AIS to directly monitor and interact with action-potential-based electrically processed information.”
The paper relies on this without support.
Future human B/CI technologies require long-term, self-implanting in vivo neural interface systems.
“Future human B/CI technologies may preferably require long-term, self-implanting in vivo neural interface systems, a characteristic that is absent from most current BMI technologies.”
The paper relies on this without support.
Human knowledge is being digitized at an accelerated exponential pace for storage and processing in the cloud.
“Human knowledge is being digitized at an accelerated exponential pace for storage and processing in the cloud.”
The paper relies on this without support.
Neuralnanorobotics may provide a technology at the appropriate scale, with a suitable level of complexity to robustly interface the human brain with the massive volume of data that is stored and processed in the cloud.
“Neuralnanorobotics may provide a technology at the appropriate scale, with a suitable level of complexity to robustly interface the human brain with the massive volume of data that is stored and processed in the cloud.”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Brain-component percentages do not match the stated intracranial volume
MinorThe listed volumes total 1,700 cm3, but 1,350 cm3 is about 79.4% of that total, not 75%. The listed blood and cerebrospinal-fluid percentages also do not match their volumes.
Reported 75 · recomputed 79.411765
“∼1,350 cm3 (∼75%) brain cells, ∼200 cm3 (15%) blood, and up to ∼150 cm3 (10%) of cerebrospinal fluid”
Occipital synapse count implies more neurons than the table allows
MinorTable 2's 22.0 trillion occipital synapses divided by 4.36 thousand synapses per neuron implies about 5.05 billion neurons. That exceeds the listed upper bound of 4.65 billion.
Reported 4.65 · recomputed 5.045872
“| Occipital | 69 | 22.0 | 3–4.65 | 4.36 | 3 |”
Cites
A synaptic model of memory: long-term potentiation in the hippocampus
Bliss, T. V. P., & Collingridge, G. L. (1993) · Nature · doi:10.1038/361031a0 · Cited by 11,566 · see citing works
Parallel organization of functionally segregated circuits linking basal ganglia and cortex
Alexander, G. E., DeLong, M. R., & Strick, P. L. (1986) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.09.030186.002041 · Cited by 8,527 · see citing works
Terry, R. D., Masliah, E., Salmon, D. P., Butters, N., DeTeresa, R., Hill, R., Hansen, L. A., & Katzman, R. (1991) · Annals of Neurology · doi:10.1002/ana.410300410 · Cited by 4,397 · see citing works
Deep Brain Stimulation for Treatment-Resistant Depression
Mayberg, H. S., Lozano, A. M., Voon, V., McNeely, H. E., Seminowicz, D., Hamani, C., Schwalb, J. M., & Kennedy, S. H. (2005) · Neuron · doi:10.1016/j.neuron.2005.02.014 · Cited by 4,059 · see citing works
The molecular biology of memory storage: a dialogue between genes and synapses
Kandel, E. R. (2001) · Science · doi:10.1126/science.1067020 · Cited by 3,917 · see citing works
The Synaptic Organization of the Brain
(2004) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195159561.001.1 · Cited by 3,550 · see citing works
Henry, M. A. (1995) · The Journal of the American Dental Association · doi:10.14219/jada.archive.1995.0108 · Cited by 3,454 · see citing works
The Singularity Is near: When Humans Transcend Biology
Mead, W. R., & Kurzweil, R. (2006) · Foreign Affairs · doi:10.2307/20031996 · Cited by 3,448 · see citing works
The Human Connectome: A Structural Description of the Human Brain
Sporns, O., Tononi, G., & Kötter, R. (2005) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0010042 · Cited by 3,260 · see citing works
The blood-brain barrier: Bottleneck in brain drug development
Pardridge, W. M. (2005) · NeuroRX · doi:10.1602/neurorx.2.1.3 · Cited by 2,798 · see citing works
Reach and grasp by people with tetraplegia using a neurally controlled robotic arm
Hochberg, L. R., Bacher, D., Jarosiewicz, B., Masse, N. Y., Simeral, J. D., Vogel, J., Haddadin, S., Liu, J., Cash, S. S., van der Smagt, P., et al. (2012) · Nature · doi:10.1038/nature11076 · Cited by 2,719 · see citing works
Cellular Scaling Rules for the Brains of Marsupials: Not as “Primitive” as Expected
Santos, S. E. D., Porfírio, J., Cunha, F., Manger, P. R., Tavares, W. C., Pessôa, L. M., Raghanti, M. A., Sherwood, C. C., & Herculano‐Houzel, S. (2017) · Brain Behavior and Evolution · doi:10.1159/000452856 · Cited by 2,651 · see citing works
Synapse loss in frontal cortex biopsies in Alzheimer's disease: Correlation with cognitive severity
DeKosky, S. T., & Scheff, S. W. (1990) · Annals of Neurology · doi:10.1002/ana.410270502 · Cited by 2,376 · see citing works
Azevedo, F. A. C., Carvalho, L. R. B., Grinberg, L. T., Farfel, J. M., Ferretti, R. E. L., Leite, R. E. P., Filho, W. J., Lent, R., & Herculano‐Houzel, S. (2009) · Journal of Comparative Neurology · doi:10.1002/cne.21974 · Cited by 2,337 · see citing works
Experience-dependent structural synaptic plasticity in the mammalian brain
Holtmaat, A., & Svoboda, K. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2699 · Cited by 1,934 · see citing works
Response of brain tissue to chronically implanted neural electrodes
Polikov, V. S., Tresco, P. A., & Reichert, W. M. (2005) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2005.08.015 · Cited by 1,896 · see citing works
Brain–machine interfaces: past, present and future
Lebedev, M. A., & Nicolelis, M. A. L. (2006) · Trends in Neurosciences · doi:10.1016/j.tins.2006.07.004 · Cited by 1,875 · see citing works
Self-citationvan de Burgt, Y., Lubberman, E., Fuller, E. J., Keene, S. T., Faria, G. C., Agarwal, S., Marinella, M. J., Alec Talin, A., & Salleo, A. (2017) · Nature Materials · doi:10.1038/nmat4856 · Cited by 1,872 · see citing works
The human brain in numbers: a linearly scaled-up primate brain
Herculano-Houzel, S. (2009) · Frontiers in Human Neuroscience · doi:10.3389/neuro.09.031.2009 · Cited by 1,778 · cited 1× · see citing works
“The average number of glial cells in the human brain is estimated to be 84.61 ± 9.83 × 10 9 (Herculano-Houzel, 2009), with the population of glial cells in the neocortex estimated at from 18.2 to 38.6 × 10 9 (Karlsen and Pakkenberg, 2011).”
BackgroundInfluentialThe connectomics of brain disorders
Fornito, A., Zalesky, A., & Breakspear, M. (2015) · Nature Reviews Neuroscience · doi:10.1038/nrn3901 · Cited by 1,734 · see citing works
Abbott, L. F., & Regehr, W. G. (2004) · Nature · doi:10.1038/nature03010 · Cited by 1,684 · see citing works
Optogenetic stimulation of a hippocampal engram activates fear memory recall
Liu, X., Ramirez, S., Pang, P. T., Puryear, C. B., Govindarajan, A., Deisseroth, K. A., & Tonegawa, S. (2012) · Nature · doi:10.1038/nature11028 · Cited by 1,669 · see citing works
The importance of mixed selectivity in complex cognitive tasks
Rigotti, M., Barak, O., Warden, M. R., Wang, X.-J., Daw, N. D., Miller, E. K., & Fusi, S. (2013) · Nature · doi:10.1038/nature12160 · Cited by 1,639 · see citing works
The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence
Jung, R. E., & Haier, R. J. (2007) · Behavioral and Brain Sciences · doi:10.1017/s0140525x07001185 · Cited by 1,593 · see citing works
Building Watson: An Overview of the DeepQA Project
Ferrucci, D. A., Brown, E. W., Chu‐Carroll, J., Fan, J., Gondek, D. C., Kalyanpur, A. A., Lally, A., Murdock, J. W., Nyberg, E., Prager, J. M., et al. (2010) · AI Magazine · doi:10.1609/aimag.v31i3.2303 · Cited by 1,523 · see citing works
Towards fully autonomous driving: Systems and algorithms
Levinson, J., Askeland, J., Becker, J., Dolson, J., Held, D., Kammel, S., Kolter, J. Z., Langer, D., Pink, O., Pratt, V., et al. (2011) · 2011 IEEE Intelligent Vehicles Symposium (IV) · doi:10.1109/ivs.2011.5940562 · Cited by 1,374 · see citing works
New roles for astrocytes: redefining the functional architecture of the brain.
Nedergaard, M., Ransom, B., & Goldman, S. A. (2003) · Trends in Neurosciences · doi:10.1016/j.tins.2003.08.008 · Cited by 1,334 · see citing works
Toward Direct Brain-Computer Communication
Vidal, J. J. (1973) · Annual Review of Biophysics and Bioengineering · doi:10.1146/annurev.bb.02.060173.001105 · Cited by 1,311 · see citing works
Nanoelectronic programmable synapses based on phase change materials for brain-inspired computing
Kuzum, D., Jeyasingh, R. G. D., Lee, B., & Wong, H.-S. P. (2012) · Nano Letters · doi:10.1021/nl201040y · Cited by 1,267 · cited 1× · see citing works
“This suggests that emulation of biological synapses is a prerequisite for the development of brain-like computational systems (Maass and Zador, 1999; Fuhrmann et al., 2002; Kuzum et al., 2012).”
BackgroundBlack, J. E., Isaacs, K. R., Anderson, B. J., Alcantara, A. A., & Greenough, W. T. (1990) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.87.14.5568 · Cited by 1,161 · see citing works
London, M., & Häusser, M. (2005) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.28.061604.135703 · Cited by 1,149 · see citing works
Perlmutter, J. S., & Mink, J. W. (2006) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.112824 · Cited by 1,073 · see citing works
The Postsynaptic Architecture of Excitatory Synapses: A More Quantitative View
Sheng, M., & Hoogenraad, C. C. (2007) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.76.060805.160029 · Cited by 1,003 · see citing works
Biophysics of computation: information processing in single neurons
(1999) · Choice Reviews Online · doi:10.5860/choice.36-5662 · Cited by 999 · see citing works
fNIRS-based brain-computer interfaces: a review
Naseer, N., & Hong, K.-S. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00003 · Cited by 988 · see citing works
DeFelipe, J., & Fariñas, I. (1992) · Progress in Neurobiology · doi:10.1016/0301-0082(92)90015-7 · Cited by 975 · see citing works
Larsen, P. O., & von Ins, M. (2010) · Scientometrics · doi:10.1007/s11192-010-0202-z · Cited by 964 · see citing works
The columnar organization of the neocortex.
Mountcastle, V. B. (1997) · Brain : a journal of neurology · doi:10.1093/brain/120.4.701 · Cited by 941 · see citing works
Baude, A., Nusser, Z., Roberts, J. D. B., Mulvihill, E., Jeffrey Mcllhinney, R. A., & Somogyi, P. (1993) · Neuron · doi:10.1016/0896-6273(93)90086-7 · Cited by 927 · see citing works
Balancing Structure and Function at Hippocampal Dendritic Spines
Bourne, J. N., & Harris, K. M. (2008) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.31.060407.125646 · Cited by 916 · see citing works
Mannoor, M. S., Jiang, Z., James, T., Kong, Y. L., Malatesta, K. A., Soboyejo, W. O., Verma, N., Gracias, D. H., & McAlpine, M. C. (2013) · Nano Letters · doi:10.1021/nl4007744 · Cited by 876 · see citing works
Patolsky, F., Timko, B. P., Yu, G., Fang, Y., Greytak, A. B., Zheng, G., & Lieber, C. M. (2006) · Science · doi:10.1126/science.1128640 · Cited by 832 · see citing works
Three-Dimensional, Flexible Nanoscale Field-Effect Transistors as Localized Bioprobes
Tian, B., Cohen‐Karni, T., Qing, Q., Duan, X., Xie, P., & Lieber, C. M. (2010) · Science · doi:10.1126/science.1192033 · Cited by 798 · see citing works
Nanoparticle Surface Charges Alter Blood–Brain Barrier Integrity and Permeability
Lockman, P. R., Koziara, J. M., Mumper, R. J., & Allen, D. D. (2004) · Journal of drug targeting · doi:10.1080/10611860400015936 · Cited by 742 · see citing works
Breaking the silence: Brain-computer interfaces (BCI) for communication and motor control
Birbaumer, N. (2006) · Psychophysiology · doi:10.1111/j.1469-8986.2006.00456.x · Cited by 722 · see citing works
Syringe-injectable electronics
Liu, J., Fu, T.-M., Cheng, Z., Hong, G., Zhou, T., Jin, L., Duvvuri, M., Jiang, Z., Kruskal, P., Xie, C., et al. (2015) · Nature Nanotechnology · doi:10.1038/nnano.2015.115 · Cited by 687 · see citing works
Miro1 Is a Calcium Sensor for Glutamate Receptor-Dependent Localization of Mitochondria at Synapses
MacAskill, A. F., Rinholm, J. E., Twelvetrees, A. E., Arancibia‐Cárcamo, I. L., Muir, J., Fransson, Å., Aspenström, P., Attwell, D., & Kittler, J. T. (2009) · Neuron · doi:10.1016/j.neuron.2009.01.030 · Cited by 677 · see citing works
Molecular Functionalization of Carbon Nanotubes and Use as Substrates for Neuronal Growth
Mattson, M. P., Haddon, R. C., & Rao, A. M. (2000) · Journal of Molecular Neuroscience · doi:10.1385/jmn:14:3:175 · Cited by 636 · see citing works
Active tactile exploration using a brain–machine–brain interface
O’Doherty, J. E., Lebedev, M. A., Ifft, P. J., Zhuang, K. Z., Shokur, S., Bleuler, H., & Nicolelis, M. A. L. (2011) · Nature · doi:10.1038/nature10489 · Cited by 629 · see citing works
Self-citationAnatomical and Physiological Plasticity of Dendritic Spines
Alvarez, V. A., & Sabatini, B. L. (2007) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.30.051606.094222 · Cited by 629 · see citing works
Brain Tissue Responses to Neural Implants Impact Signal Sensitivity and Intervention Strategies
Kozai, T. D. Y., Jaquins-Gerstl, A. S., Vazquez, A. L., Michael, A. C., & Cui, X. T. (2015) · ACS Chemical Neuroscience · doi:10.1021/cn500256e · Cited by 622 · see citing works
Self-targeting fluorescent carbon dots for diagnosis of brain cancer cells.
Zheng, M., Ruan, S., Liu, S., Sun, T., Qu, D., Zhao, H., Xie, Z., Gao, H., Jing, X., & Sun, Z. (2015) · ACS Nano · doi:10.1021/acsnano.5b05575 · Cited by 593 · see citing works
Existential Risk Prevention as Global Priority
Bostrom, N. (2013) · Global Policy · doi:10.1111/1758-5899.12002 · Cited by 588 · cited 2× · see citing works
“…cortical structure consists of mini-columnar and laminar arrangements of neurons that are linked via afferent and efferent connections distributed across multiple brain regions (Lorento de Nó, 1938; Mountcastle, 1997; Shepherd and Grillner, 2010; Opris, 2013; Opris et al., 2011, 2013, 2014, 2015).”
BackgroundArtificial Vision for the Blind by Connecting a Television Camera to the Visual Cortex
Dobelle, W. H. (2000) · ASAIO Journal · doi:10.1097/00002480-200001000-00002 · Cited by 584 · see citing works
Miyawaki, Y., Uchida, H., Yamashita, O., Sato, M.-A., Morito, Y., Tanabe, H. C., Sadato, N., & Kamitani, Y. (2008) · Neuron · doi:10.1016/j.neuron.2008.11.004 · Cited by 543 · see citing works
Axonal transport of mitochondria along microtubules and F-actin in living vertebrate neurons.
Morris, R. L., & Hollenbeck, P. J. (1995) · The Journal of Cell Biology · doi:10.1083/jcb.131.5.1315 · Cited by 541 · see citing works
The role of single neurons in information processing
Christof Koch, A., & Segev, I. (2000) · Nature Neuroscience · doi:10.1038/81444 · Cited by 529 · see citing works
Universal Artificial Intellegence
Hutter, M. (2005) · Texts in Theoretical Computer Science An EATCS Series · doi:10.1007/b138233 · Cited by 523 · see citing works
Conceptual Models of Neural Organization.
Pritchard, J. J. (1976) · Europe PMC (PubMed Central) · Cited by 514 · see citing works
Shepherd, G. M. G., & Harris, K. M. (1998) · The Journal of Neuroscience · doi:10.1523/jneurosci.18-20-08300.1998 · Cited by 502 · see citing works
Nonlinear interactions in a dendritic tree: localization, timing, and role in information processing
Koch, C., Poggio, T., & Torre, V (1983) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.80.9.2799 · Cited by 496 · see citing works
The mechanisms and functions of synaptic facilitation.
Jackman, S. L., & Regehr, W. G. (2017) · Neuron · doi:10.1016/j.neuron.2017.02.047 · Cited by 489 · see citing works
Factors influencing the biocompatibility of insertable silicon microshafts in cerebral cortex
Edell, D. J., Toi, V. V., McNeil, V. M., & Clark, L. D. (1992) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.141202 · Cited by 479 · see citing works
Development of a magnetic microrobot for carrying and delivering targeted cells
Li, J., Li, X., Luo, T., et al. (2018) · Science Robotics · doi:10.1126/scirobotics.aat8829 · Cited by 465 · see citing works
Martel, S. M., Mohammadi, M., Felfoul, O., Lu, Z., & Pouponneau, P. (2009) · The International Journal of Robotics Research · doi:10.1177/0278364908100924 · Cited by 461 · see citing works
Perceptual Learning Incepted by Decoded fMRI Neurofeedback Without Stimulus Presentation
Shibata, K., Watanabe, T., Sasaki, Y., & Kawato, M. (2011) · Science · doi:10.1126/science.1212003 · Cited by 456 · see citing works
Intracellular recordings of action potentials by an extracellular nanoscale field-effect transistor
Duan, X., Gao, R., Xie, P., Cohen‐Karni, T., Qing, Q., Choe, H. S., Tian, B., Jiang, X., & Lieber, C. M. (2011) · Nature Nanotechnology · doi:10.1038/nnano.2011.223 · Cited by 456 · see citing works
Long-circulating pegylated polycyanoacrylate nanoparticles as new drug carrier for brain delivery.
Calvo, P., Gouritin, B., Chacun, H., Desmaële, D., D'Angelo, J., Noel, J.-P., Georgin, D., Fattal, E., Andreux, J. P., & Couvreur, P. (2001) · Pharmaceutical Research · doi:10.1023/a:1010931127745 · Cited by 443 · see citing works
Artificial Intelligence as a Positive and Negative Factor in Global Risk
Yudkowsky, E. (2008) · Global Catastrophic Risks · doi:10.1093/oso/9780198570509.003.0021 · Cited by 431 · see citing works
Rees, M. J. (2008) · Oxford University Press eBooks · doi:10.1093/oso/9780198570509.001.0001 · Cited by 426 · see citing works
(2002) · Oxford University Research Archive (ORA) (University of Oxford) · Cited by 421 · see citing works
Freitas, R. A. (2005) · Nanomedicine Nanotechnology Biology and Medicine · doi:10.1016/j.nano.2004.11.003 · Cited by 419 · see citing works
Self-citationA neural interface for a cortical vision prosthesis
Normann, R. A., Maynard, E. M., Rousche, P. J., & Warren, D. J. (1999) · Vision Research · doi:10.1016/s0042-6989(99)00040-1 · Cited by 411 · see citing works
Synaptic Protein Degradation Underlies Destabilization of Retrieved Fear Memory
Lee, S.-H., Choi, J.-H., Lee, N., Lee, H.-R., Kim, J.-I., Yu, N.-K., Choi, S.-L., Lee, S.-H., Kim, H., & Kaang, B.-K. (2008) · Science · doi:10.1126/science.1150541 · Cited by 409 · see citing works
Getting Leukocytes to the Site of Inflammation
Müller, W. A. (2013) · Veterinary Pathology · doi:10.1177/0300985812469883 · Cited by 401 · see citing works
Anatomy and physiology of the blood-brain barrier
Serlin, Y., Shelef, I., Knyazer, B., & Friedman, A. (2015) · Seminars in Cell & Developmental Biology · doi:10.1016/j.semcdb.2015.01.002 · Cited by 397 · see citing works
ANALYSIS OF THE ACTIVITY OF THE CHAINS OF INTERNUNCIAL NEURONS
de N�, R. L. (1938) · Journal of Neurophysiology · doi:10.1152/jn.1938.1.3.207 · Cited by 394 · see citing works
(1999) · Cited by 392 · see citing works
Self-citationProgress towards biocompatible intracortical microelectrodes for neural interfacing applications
Jorfi, M., Skousen, J. L., Weder, C., & Capadona, J. R. (2015) · Journal of Neural Engineering · doi:10.1088/1741-2560/12/1/011001 · Cited by 384 · see citing works
An Ankle-Foot Orthosis Powered by Artificial Pneumatic Muscles
Ferris, D. P., Czerniecki, J. M., & Blake Hannaford, A. (2005) · Journal of Applied Biomechanics · doi:10.1123/jab.21.2.189 · Cited by 377 · see citing works
Dynamic Aspects of CNS Synapse Formation
McAllister, A. K. (2007) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.112830 · Cited by 368 · see citing works
Influence of the Surface Properties on Nanoparticle-Mediated Transport of Drugs to the Brain
Kreuter, J. (2004) · Journal of Nanoscience and Nanotechnology · doi:10.1166/jnn.2003.077 · Cited by 363 · see citing works
Neuromorphic device architectures with global connectivity through electrolyte gating.
Gkoupidenis, P., Koutsouras, D. A., & Malliaras, G. G. (2017) · Nature Communications · doi:10.1038/ncomms15448 · Cited by 353 · see citing works
Activity-dependent dynamics and sequestration of proteasomes in dendritic spines
Bingol, B., & Schuman, E. M. (2006) · Nature · doi:10.1038/nature04769 · Cited by 347 · see citing works
Neuronal activity regulates diffusion across the neck of dendritic spines
Bloodgood, B. L., & Sabatini, B. L. (2005) · Science · doi:10.1126/science.1114816 · Cited by 344 · see citing works
Site of Action Potential Initiation in Layer 5 Pyramidal Neurons
Palmer, L. M., & Stuart, G. J. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.4812-05.2006 · Cited by 336 · see citing works
Conceptual models of neural organization.
Szentágothai, J., & Arbib, M. A. (1974) · PubMed · Cited by 329 · see citing works
Liewald, D., Miller, R., Logothetis, N., Wagner, H.-J., & Schüz, A. (2014) · Biological Cybernetics · doi:10.1007/s00422-014-0626-2 · Cited by 322 · see citing works
Learning to walk with a robotic ankle exoskeleton
Gordon, K. E., & Ferris, D. P. (2007) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2006.12.006 · Cited by 321 · see citing works
Restoring the sense of touch with a prosthetic hand through a brain interface
Tabot, G. A., Dammann, J. F., Berg, J. A., Tenore, F. V., Boback, J. L., Vogelstein, R. J., & Bensmaia, S. J. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1221113110 · Cited by 320 · see citing works
A cortical neural prosthesis for restoring and enhancing memory
Berger, T. W., Hampson, R. E., Song, D. B., Goonawardena, A. V., Marmarelis, V. Z., & Deadwyler, S. A. (2011) · Journal of Neural Engineering · doi:10.1088/1741-2560/8/4/046017 · Cited by 316 · see citing works
Drug transport in brain via the cerebrospinal fluid.
Pardridge, W. M. (2011) · Fluids and Barriers of the CNS · doi:10.1186/2045-8118-8-7 · Cited by 316 · see citing works
Nopoulos, P., Flaum, M., O’Leary, D., & Andreasen, N. C. (2000) · Psychiatry Research: Neuroimaging · doi:10.1016/s0925-4927(99)00044-x · Cited by 303 · see citing works
Mallouk, T. E., & Sen, A. (2009) · Scientific American · doi:10.1038/scientificamerican0509-72 · Cited by 294 · see citing works
Zeck, G., & Fromherz, P. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.181348698 · Cited by 290 · see citing works
Alzheimer’s disease-related alterations in synaptic density: neocortex and hippocampus.
Scheff, S. W., & Price, D. A. (2006) · Journal of Alzheimer's Disease · doi:10.3233/jad-2006-9s312 · Cited by 284 · see citing works
Cochlear Implantation in Adults
Gaylor, J. M., Raman, G., Chung, M. C., Lee, J., Rao, M., Lau, J., & Poe, D. S. (2013) · JAMA Otolaryngology–Head & Neck Surgery · doi:10.1001/jamaoto.2013.1744 · Cited by 276 · see citing works
Trushina, E. V., Nemutlu, E., Zhang, S., Christensen, T. A., Camp, J. J., Mesa, J., Siddiqui, A., Tamura, Y., Sesaki, H., Wengenack, T. M., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0032737 · Cited by 268 · see citing works
Coding of temporal information by activity-dependent synapses.
Fuhrmann, G., Segev, I., Markram, H., & Tsodyks, M. (2002) · Journal of Neurophysiology · doi:10.1152/jn.00258.2001 · Cited by 267 · see citing works
Robotic Leg Control with EMG Decoding in an Amputee with Nerve Transfers
Hargrove, L. J., Simon, A. M., Young, A. J., Lipschutz, R. D., Finucane, S. B., Smith, D. G., & Kuiken, T. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1300126 · Cited by 253 · see citing works
A Brain-to-Brain Interface for Real-Time Sharing of Sensorimotor Information
Pais-Vieira, M., Lebedev, M., Kunicki, C., Wang, J., & Nicolelis, M. A. L. (2013) · Scientific Reports · doi:10.1038/srep01319 · Cited by 252 · see citing works
Self-citationStructural determinants of transmission at large hippocampal mossy fiber synapses
Rollenhagen, A., Sätzler, K., Rodríguez, E. P., Jonas, P., Frotscher, M., & Lübke, J. H. R. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.1946-07.2007 · Cited by 246 · see citing works
Impact of Synaptic Unreliability on the Information Transmitted by Spiking Neurons
Zador, A. M. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.79.3.1219 · Cited by 242 · see citing works
Multifunctional carbon-nanotube cellular endoscopes.
Singhal, R., Orynbayeva, Z., Kalyana Sundaram, R. V., Niu, J. J., Bhattacharyya, S., Vitol, E. A., Schrlau, M. G., Papazoglou, E. S., Friedman, G., & Gogotsi, Y. (2011) · Nature Nanotechnology · doi:10.1038/nnano.2010.241 · Cited by 241 · see citing works
Mass of the postsynaptic density and enumeration of three key molecules
Chen, X., Vinade, L., Leapman, R. D., Petersen, J. D., Nakagawa, T., Phillips, T. M., Sheng, M., & Reese, T. S. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0505359102 · Cited by 236 · see citing works
Lewis, P. M., Ackland, H. M., Lowery, A. J., & Rosenfeld, J. V. (2015) · Brain Research · doi:10.1016/j.brainres.2014.11.020 · Cited by 228 · see citing works
Self-citationLateral organization of endocytic machinery in dendritic spines
Rácz, B., Blanpied, T. A., Ehlers, M., & Weinberg, R. J. (2004) · Nature Neuroscience · doi:10.1038/nn1303 · Cited by 227 · see citing works
Molecular anatomy of the postsynaptic density.
Okabe, S. (2007) · Molecular and Cellular Neuroscience · doi:10.1016/j.mcn.2007.01.006 · Cited by 225 · see citing works
Simplified dynamics of human and mammalian neocortical neurons.
WILSON, H. R. (1999) · Journal of Theoretical Biology · doi:10.1006/jtbi.1999.1002 · Cited by 222 · see citing works
(2004) · Medical Entomology and Zoology · Cited by 218 · see citing works
Self-citationNanoparticle transport across the blood brain barrier
Grabrucker, A. M., Ruozi, B., Belletti, D., Pederzoli, F., Forni, F., Vandelli, M. A., & Tosi, G. (2016) · Tissue Barriers · doi:10.1080/21688370.2016.1153568 · Cited by 217 · see citing works
Potential neurotoxicity of nanoparticles
Hu, Y., & Gao, J. (2010) · International Journal of Pharmaceutics · doi:10.1016/j.ijpharm.2010.04.026 · Cited by 214 · see citing works
Mapping the Landscape of Human-Level Artificial General Intelligence
Adams, S. S., Arel, I., Bach, J., Coop, R., Furlan, R., Goertzel, B., Hall, J. S., Samsonovich, A., Scheutz, M., Schlesinger, M., et al. (2012) · AI Magazine · doi:10.1609/aimag.v33i1.2322 · Cited by 213 · see citing works
Conscious Brain-to-Brain Communication in Humans Using Non-Invasive Technologies
Grau, C., Ginhoux, R., Riera, A., Nguyen, T. L., Chauvat, H., Berg, M., Amengual, J. L., Pascual-Leone, A., & Ruffini, G. (2014) · PLoS ONE · doi:10.1371/journal.pone.0105225 · Cited by 211 · see citing works
A Direct Brain-to-Brain Interface in Humans
Rao, R. P. N., Stocco, A., Bryan, M., Sarma, D., Youngquist, T. M., Wu, J., & Prat, C. S. (2014) · PLoS ONE · doi:10.1371/journal.pone.0111332 · Cited by 210 · see citing works
Rengachary, S. S., & Wilkins, R. H. (2004) · Medical Entomology and Zoology · Cited by 209 · see citing works
Neural Dust: An Ultrasonic, Low Power Solution for Chronic Brain-Machine Interfaces
Seo, D., Maharbiz, M., Alon, E., et al. (2013) · doi:10.2307/j.ctt9qh0x7.26 · Cited by 204
Reliability and information transmission in spiking neurons.
Bialek, W., & Rieke, F. (1992) · Trends in Neurosciences · doi:10.1016/0166-2236(92)90005-s · Cited by 200 · see citing works
Nanotechnology—novel therapeutics for CNS disorders
Srikanth, M., & Kessler, J. A. (2012) · Nature Reviews Neurology · doi:10.1038/nrneurol.2012.76 · Cited by 198 · see citing works
Handbook of Brain Microcircuits
(2010) · Oxford University Press eBooks · doi:10.1093/med/9780195389883.001.0001 · Cited by 197 · see citing works
BrainNet: A Multi-Person Brain-to-Brain Interface for Direct Collaboration Between Brains
Jiang, L., Stocco, A., Losey, D. M., Abernethy, J. A., Prat, C. S., & Rao, R. P. N. (2019) · Scientific Reports · doi:10.1038/s41598-019-41895-7 · Cited by 190 · cited 1× · see citing works
“A three-human BTBI system, called “BrainNet,” has been recently developed, which allowed three human subjects to collaboratively solve a task using non-invasive, direct brain-to-brain communication (Jiang et al., 2018).”
BackgroundTotal regional and global number of synapses in the human brain neocortex
Tang, Y. C., Nyengaard, J. R., de Groot, D. M. G., & Gundersen, H. J. G. (2001) · Synapse · doi:10.1002/syn.1083 · Cited by 182 · see citing works
Kim, S., Kim, Y., & Ma, E. (2011) · Molecules · doi:10.3390/molecules17010355 · Cited by 181 · see citing works
Winslow, B. D., & Tresco, P. A. (2010) · Biomaterials · doi:10.1016/j.biomaterials.2009.11.049 · Cited by 178 · see citing works
Chronically implanted intrafascicular recording electrodes
Lefurge, T., Goodall, E., Horch, K., Stensaas, L., & Schoenberg, A. (1991) · Annals of Biomedical Engineering · doi:10.1007/bf02368469 · Cited by 172 · see citing works
Neural Dust: An Ultrasonic, Low Power Solution for Chronic Brain-Machine Interfaces
Seo, D., Carmena, J. M., Rabaey, J. M., Alon, E., & Maharbiz, M. M. (2013) · arXiv · doi:10.48550/arxiv.1307.2196 · Cited by 172 · see citing works
Magnetoelectric ‘spin’ on stimulating the brain.
Guduru, R., Liang, P., Hong, J., Rodzinski, A., Hadjikhani, A., Horstmyer, J., Levister, E., & Khizroev, S. (2015) · Nanomedicine · doi:10.2217/nnm.15.52 · Cited by 171 · see citing works
Silicon-neuron junction: capacitive stimulation of an individual neuron on a silicon chip.
Fromherz, P., & Stett, A. (1995) · Physical Review Letters · doi:10.1103/physrevlett.75.1670 · Cited by 167 · see citing works
Exploratory design in medical nanotechnology: a mechanical artificial red cell.
Frcitas, R. A. (1998) · Artificial Cells, Blood Substitutes, and Biotechnology · doi:10.3109/10731199809117682 · Cited by 167 · see citing works
Magneto-electric nano-particles for non-invasive brain stimulation.
Yue, K., Guduru, R., Hong, J., Liang, P., Nair, M., & Khizroev, S. (2012) · PLoS ONE · doi:10.1371/journal.pone.0044040 · Cited by 161 · see citing works
Biomechanical Design of a Powered Ankle-Foot Prosthesis
Au, S. K., Weber, J., & Herr, H. (2007) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2007.4428441 · Cited by 158 · see citing works
Facilitation of picture naming after repetitive transcranial magnetic stimulation
Mottaghy, F. M., Hungs, M., Brügmann, M., Sparing, R., Boroojerdi, B., Foltys, H., Huber, W., & Töpper, R. (1999) · Neurology · doi:10.1212/wnl.53.8.1806 · Cited by 153 · see citing works
Information processing by graded-potential transmission through tonically active synapses
Juusola, M., French, A. S., Uusitalo, R. O., & Weckström, M. (1996) · Trends in Neurosciences · doi:10.1016/s0166-2236(96)10028-x · Cited by 152 · see citing works
Large-Scale Automated Histology in the Pursuit of Connectomes
Kleinfeld, D., Bharioke, A., Blinder, P., Bock, D. D., Briggman, K. L., Chklovskii, D. B., Denk, W. T., Helmstaedter, M. N., Kaufhold, J. P., Lee, W.-C. A., et al. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.4077-11.2011 · Cited by 152 · see citing works
Rise of Augmented Reality: Current and Future Application Areas
Alkhamisi, A. O., & Monowar, M. M. (2013) · International Journal of Internet and Distributed Systems · doi:10.4236/ijids.2013.14005 · Cited by 151 · see citing works
Dynamic stochastic synapses as computational units.
Maass, W., & Zador, A. M. (1999) · Neural Computation · doi:10.1162/089976699300016494 · Cited by 149 · see citing works
Intranasal delivery: An approach to bypass the blood brain barrier
Talegaonkar, S., & Mishra, P. (2004) · Bioline International (Bioline International) · Cited by 148 · see citing works
Restoring lost cognitive function.
Berger, T. W., Ahuja, A., Courellis, S. H., Deadwyler, S. A., Erinjippurath, G., Gerhardt, G. A., Gholmieh, G., Granacki, J. J., Hampson, R., Hsaio, M. C., et al. (2005) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/memb.2005.1511498 · Cited by 148 · see citing works
A quantitative analysis of blood-brain barrier ultrastructure in the aging human.
Stewart, P. A., Magliocco, M., Hayakawa, K., Farrell, C. L., Del Maestro, R. F., Girvin, J., Kaufmann, J. C. E., Vinters, H. V., & Gilbert, J. (1987) · Microvascular Research · doi:10.1016/0026-2862(87)90022-7 · Cited by 148 · see citing works
Mechanical and Biological Interactions of Implants with the Brain and Their Impact on Implant Design
Prodanov, D., & Delbeke, J. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2016.00011 · Cited by 148 · see citing works
A Collaborative Brain-Computer Interface for Improving Human Performance
Wang, Y., & Jung, T.-P. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020422 · Cited by 147 · see citing works
Neuronal correlates of depression
Chaudhury, D., Liu, H., & Han, M. (2015) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-015-2044-6 · Cited by 142 · see citing works
Engineered nanoparticles, How brain friendly is this new guest?
Cupaioli, F. A., Zucca, F. A., Boraschi, D., & Zecca, L. (2014) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2014.05.002 · Cited by 139 · see citing works
Cognit activation: a mechanism enabling temporal integration in working memory
Fuster, J. M., & Bressler, S. L. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2012.03.005 · Cited by 139 · see citing works
Nanorobot: A versatile tool in nanomedicine
Patel, G. M., Patel, G. C., Patel, R. B., et al. (2006) · Journal of drug targeting · doi:10.1080/10611860600612862 · Cited by 134 · see citing works
General intelligence and memory span: Evidence for a common neuroanatomic framework
Colom, R., Jung, R. E., & Haier, R. J. (2007) · Cognitive Neuropsychology · doi:10.1080/02643290701781557 · Cited by 131 · see citing works
Mind-controlled transgene expression by a wireless-powered optogenetic designer cell implant.
Folcher, M., Oesterle, S., Zwicky, K., Thekkottil, T., Heymoz, J., Hohmann, M., Christen, M., Daoud El-Baba, M., Buchmann, P., & Fussenegger, M. (2014) · Nature Communications · doi:10.1038/ncomms6392 · Cited by 130 · see citing works
Stone, J. L., & Hughes, J. R. (2013) · Journal of Clinical Neurophysiology · doi:10.1097/wnp.0b013e31827edb2d · Cited by 129 · see citing works
Non-Invasive Brain-to-Brain Interface (BBI): Establishing Functional Links between Two Brains
Yoo, S., Kim, H., Filandrianos, E., TAGHADOS, S. J., & Park, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0060410 · Cited by 127 · see citing works
Implantable bioelectronic interfaces for lost nerve functions
Heiduschka, P., & Thanos, S. (1998) · Progress in Neurobiology · doi:10.1016/s0301-0082(98)00013-6 · Cited by 126 · see citing works
Electrophysiological classes of neocortical neurons.
Contreras, D. (2004) · Neural Networks · doi:10.1016/j.neunet.2004.04.003 · Cited by 124 · see citing works
Timko, B. P., Cohen-Karni, T., Qing, Q., Tian, B., & Lieber, C. M. (2010) · IEEE Transactions on Nanotechnology · doi:10.1109/tnano.2009.2031807 · Cited by 114 · see citing works
The Interscutularis Muscle Connectome
Lu, J., Tapia, J. C., White, O. L., & Lichtman, J. W. (2009) · PLoS Biology · doi:10.1371/journal.pbio.1000032 · Cited by 114 · see citing works
Brain-machine interfaces: an overview.
Lebedev, M. (2014) · Translational Neuroscience · doi:10.2478/s13380-014-0212-z · Cited by 112 · see citing works
Self-citationDynamics of cortical dendritic membrane potential and spikes in freely behaving rats.
Moore, J. J., Ravassard, P. M., Ho, D., Acharya, L., Kees, A. L., Vuong, C., & Mehta, M. R. (2017) · Science · doi:10.1126/science.aaj1497 · Cited by 110 · see citing works
Weldon, M. K. (2016) · CRC Press eBooks · doi:10.1201/b21038 · Cited by 110 · see citing works
Detecting and Estimating Signals over Noisy and Unreliable Synapses: Information-Theoretic Analysis
Manwani, A., & Koch, C. (2001) · Neural Computation · doi:10.1162/089976601300014619 · Cited by 105 · see citing works
The bandwidth bottleneck that is throttling the Internet.
Hecht, J. (2016) · Nature · doi:10.1038/536139a · Cited by 103 · see citing works
Carbon nanopipettes for cell probes and intracellular injection
Schrlau, M. G., Falls, E. M., Ziober, B. L., & Bau, H. H. (2007) · Nanotechnology · doi:10.1088/0957-4484/19/01/015101 · Cited by 102 · see citing works
Motor-cortical activity in tetraplegics
Shoham, S., Halgren, E., Maynard, E. M., & Normann, R. A. (2001) · Nature · doi:10.1038/35101651 · Cited by 99 · see citing works
The morphology of excitatory central synapses: from structure to function.
Rollenhagen, A., & Lübke, J. H. R. (2006) · Cell and Tissue Research · doi:10.1007/s00441-006-0288-z · Cited by 99 · see citing works
Building an organic computing device with multiple interconnected brains
Pais-Vieira, M., Chiuffa, G., Lebedev, M., Yadav, A., & Nicolelis, M. A. L. (2015) · Scientific Reports · doi:10.1038/srep11869 · Cited by 99 · see citing works
Self-citationProtein components for nanodevices
Astier, Y., Bayley, H., & Howorka, S. (2005) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2005.10.012 · Cited by 97 · see citing works
Intracortical Recording Interfaces: Current Challenges to Chronic Recording Function
Gunasekera, B., Saxena, T. K., Bellamkonda, R. V., & Karumbaiah, L. (2015) · ACS Chemical Neuroscience · doi:10.1021/cn5002864 · Cited by 92 · see citing works
Freitas, R. A. (2003) · doi:10.1201/9781498712576 · Cited by 91 · see citing works
Self-citationModeling psychiatric disorders: from genomic findings to cellular phenotypes
Falk, A., Heine, V. M., Harwood, A. J., Sullivan, P. F., Peitz, M., Brüstle, O., Shen, S., Sun, Y.-M., Glover, J. C., Posthuma, D., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.89 · Cited by 86 · see citing works
Advances in implantable bionic devices for blindness: a review
Lewis, P., Ayton, L. N., Guymer, R. H., Lowery, A. J., Blamey, P. J., Allen, P. J., Luu, C. D., & Rosenfeld, J. V. (2016) · ANZ Journal of Surgery · doi:10.1111/ans.13616 · Cited by 86 · see citing works
Self-citationCurrent status and future perspectives of sonodynamic therapy in glioma treatment.
Wang, X., Jia, Y., Wang, P., Liu, Q., & Zheng, H. (2017) · Ultrasonics Sonochemistry · doi:10.1016/j.ultsonch.2017.02.020 · Cited by 86 · see citing works
Mesh nanoelectronics: seamless integration of electronics with tissues.
Dai, X., Hong, G., Gao, T., & Lieber, C. M. (2018) · Accounts of Chemical Research · doi:10.1021/acs.accounts.7b00547 · Cited by 86 · see citing works
Neuron-silicon junction with voltage-gated ionic currents
Schätzthauer, R., & Fromherz, P. (1998) · European Journal of Neuroscience · doi:10.1046/j.1460-9568.1998.00205.x · Cited by 85 · see citing works
Li, G., & Zhang, D. (2016) · PLOS ONE · doi:10.1371/journal.pone.0150667 · Cited by 80 · see citing works
Nag, O. K., Stewart, M. H., Deschamps, J. R., Susumu, K., Oh, E., Tsytsarev, V., Tang, Q., Efros, A. L., Vaxenburg, R., Black, B. J., et al. (2017) · ACS Nano · doi:10.1021/acsnano.7b00954 · Cited by 80 · see citing works
Synapse turnover: the formation and termination of transient synapses.
Puro, D. G., Mello, F. G. D., & Nirenberg, M. W. (1977) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.74.11.4977 · Cited by 79 · see citing works
Subretinal implantation of semiconductor-based photodiodes: progress and challenges.
Peachey, N. S., & Chow, A. Y. (1999) · PubMed · Cited by 77 · see citing works
Estimating search engine index size variability: a 9-year longitudinal study
van den Bosch, A., Bogers, T., & de Kunder, M. (2016) · Scientometrics · doi:10.1007/s11192-016-1863-z · Cited by 77 · see citing works
Kristensen, B. W., Noraberg, J., Thiébaud, P., Koudelka‐Hep, M., & Zimmer, J. (2001) · Brain Research · doi:10.1016/s0006-8993(00)03304-7 · Cited by 76 · see citing works
A multielectrode implant device for the cerebral cortex
deCharms, R. C., Blake, D. T., & Merzenich, M. M. (1999) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(99)00087-4 · Cited by 75 · see citing works
Karlsen, A. S., & Pakkenberg, B. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr033 · Cited by 75 · see citing works
Long-term survival of retinal cell cultures on retinal implant materials
Guenther, E., Tröger, B., Schlosshauer, B., & Zrenner, E. (1999) · Vision Research · doi:10.1016/s0042-6989(99)00128-5 · Cited by 71 · see citing works
Pardue, M. T., Stubbs, E. B., Perlman, J. I., et al. (2001) · Experimental Eye Research · doi:10.1006/exer.2001.1041 · Cited by 71 · see citing works
Microbivores: Artificial Mechanical Phagocytes using Digest and Discharge Protocol
Freitas, R. A. (2005) · Cited by 71 · see citing works
Self-citationTowards functional connectomics
Seung, H. S. (2011) · Nature · doi:10.1038/471170a · Cited by 67 · see citing works
The challenge of integrating devices into the central nervous system.
Tresco, P. A., & Winslow, B. D. (2011) · Critical Reviews™ in Biomedical Engineering · doi:10.1615/critrevbiomedeng.v39.i1.30 · Cited by 65 · see citing works
Neural decoding of collective wisdom with multi-brain computing
Eckstein, M. P., Das, K., Pham, B. T., Peterson, M., Abbey, C. K., Sy, J. L., & Giesbrecht, B. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.07.009 · Cited by 64 · see citing works
Syringe-injectable electronics with a plug-and-play input/output interface.
Schuhmann, T. G., Yao, J., Hong, G., Fu, T.-M., & Lieber, C. M. (2017) · Nano Letters · doi:10.1021/acs.nanolett.7b03081 · Cited by 63 · see citing works
Surgical Implantation and Biocompatibility of Central Nervous System Auditory Prostheses
Niparko, J. K., Altschuler, R. A., Wiler, J. A., Xue, X., & Anderson, D. J. (1989) · Annals of Otology Rhinology & Laryngology · doi:10.1177/000348948909801209 · Cited by 62 · see citing works
Neural Activity in Frontal Cortical Cell Layers: Evidence for Columnar Sensorimotor Processing
Opriș, I. C., Hampson, R. E., Stanford, T. R., Gerhardt, G. A., & Deadwyler, S. A. (2010) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2010.21534 · Cited by 62 · see citing works
Biocompatibility and applications of carbon nanotubes in medical nanorobots.
Попов, А. М., Lozovik, Y. E., Fiorito, S., et al. (2007) · PubMed Central · Cited by 61 · see citing works
Skousen, J. L., Bridge, M. J., & Tresco, P. A. (2015) · Biomaterials · doi:10.1016/j.biomaterials.2014.08.039 · Cited by 61 · see citing works
Nanoparticles as Novel Carrier for Brain Delivery: A Review
Agarwal, A., Lariya, N. K., Saraogi, G. K., Dubey, N., Agrawal, H., & Agrawal, G. P. (2009) · Current Pharmaceutical Design · doi:10.2174/138161209787582057 · Cited by 60 · see citing works
Collaborative Brain-Computer Interface for Aiding Decision-Making
Poli, R., Valeriani, D., & Cinel, C. (2014) · PLoS ONE · doi:10.1371/journal.pone.0102693 · Cited by 58 · see citing works
Hans Bergers Entdeckung des Elektrenkephalogramms und seine ersten Befunde 1924?1931
Jung, R., & Berger, W. (1979) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/bf00344814 · Cited by 57 · see citing works
Bits and brains: Information flow in the nervous system
Bialek, W., DeWeese, M., Rieke, F., & Warland, D. (1993) · Physica A Statistical Mechanics and its Applications · doi:10.1016/0378-4371(93)90563-j · Cited by 57 · see citing works
Mayr, W., Bijak, M., Rafolt, D., Sauermann, S., Unger, E., & Lanmüller, H. (2001) · Medical Engineering & Physics · doi:10.1016/s1350-4533(01)00014-5 · Cited by 57 · see citing works
Prefrontal cortical microcircuits bind perception to executive control
Opriș, I. C., Santos, L. M., Gerhardt, G. A., Song, D. B., Berger, T. W., Hampson, R. E., & Deadwyler, S. A. (2013) · Scientific Reports · doi:10.1038/srep02285 · Cited by 56 · see citing works
Deep brain stimulation for treatment-resistant depression.
Taghva, A. S., Malone, D. A., & Rezai, A. R. (2013) · World Neurosurgery · doi:10.1016/j.wneu.2012.10.068 · Cited by 56 · see citing works
Computing Arm Movements with a Monkey Brainet
Ramakrishnan, A., Ifft, P. J., Pais-Vieira, M., Byun, Y. W., Zhuang, K. Z., Lebedev, M. A., & Nicolelis, M. A. L. (2015) · Scientific Reports · doi:10.1038/srep10767 · Cited by 54 · see citing works
Self-citationInhibition of the tissue reaction to a biodegradable biomaterial by monoclonal antibodies to IFN-?
Khouw, I. M. S. L., van Wachem, P. B., de Leij, L. F. M. H., & van Luyn, M. J. A. (1998) · Journal of Biomedical Materials Research · doi:10.1002/(sici)1097-4636(199808)41:2 · Cited by 53 · see citing works
Phagocytic and metabolic reactions to chronically implanted metal brain electrodes.
Babb, T. L., & Kupfer, W. (1984) · Experimental Neurology · doi:10.1016/0014-4886(84)90179-1 · Cited by 51 · see citing works
Malmstrom, J. A., McNaughton, T. G., & Horch, K. W. (1998) · Annals of Biomedical Engineering · doi:10.1114/1.35 · Cited by 50 · cited 1× · see citing works
“…nitride, silicon dioxide, stainless steel, or nichrome (Niparko et al., 1989a,b; Edell et al., 1992; Yuen and Agnew, 1995; Huber et al., 1998; Malmstrom et al., 1998; Decharms et al., 1999; Normann et al., 1999;Mattson et al., 2000; Kristensen et al., 2001; Parak et al., 2001; Freitas, 2003).”
Background
Flagged first, then by citations
Research works printed but not linked: 35
- Anderson, 2011, Exploring the retinal connectome., Mol. Vis., 17, 355
- 2018, The Dawn Of The 5G World. White paper.
- 2009, Wired for Thought.
- 2017, Cisco Visual Networking Index: Forecast and Methodology, 2016–2021.
- Coles, 2006, The Toxic Terabyte: How Data-Dumping Threatens Business Efficiency. IBM Global Technology Services.
- Domschke, 2014, Quandary - Are Molecularly Manufactured Burgers Imbued with the Life Force? (Fqxi Essay Contest, in Response to the Question, How Should Humanity Steer the Future?)
- Finley, 2018, The Wired Guide to 5G.
- Ford, 2010, The Secrets of Intelligence Lie within a Single Cell: New Scientist, The Big Idea.21 April.
- Freitas, Is Diamond Biocompatible With Living Cells?
- Freitas, 2002, Is Sapphire Biocompatible With Living Cells?
- Freitas, Current status of nanomedicine and medical nanorobotics (Invited Survey)., J. Comput. Theor. Nanosci., 2, 1
- Freitas, 2016, The Alzheimer Protocols: A Nanorobotic Cure for Alzheimer’s Disease and Related Neurodegenerative Conditions.
- Freitas, 2006, Nanofactory Collaboration.
- Goertzel, 2006, The Hidden Pattern.
- Harris, 1999, Synapse Web.
- 2008, IBM Seeks to Build the Computer of the Future Based on Insights from the Brain IBM Awarded, D. A.RPA Funding for Cognitive Computing Collaboration.
- Kemp, 2018, The State of the Internet in Q4. We Are Social.
- Knapp, 2013, Chinese Supercomputer Is Now The World’s Fastest - By A Lot.
- Kurzweil, 2014, Get Ready for Hybrid Thinking. Ted Talk.
- Martins, 2015, Action potential monitoring using neuronanorobotics: neuroelectric nanosensors., Intl. J. Nanomaterials and Nanostructures, 1, 20
- Mavroides, 2011, Nanorobotics: Current Approaches and Techniques.
- Merkle, 1989, Energy Limits to the Computational Power of the Human Brain.
- Minsky, 1985, The Society of Mind.
- Miraz, 2015, Review on internet of things (loT), Internet of Everything (IoE) and Internet ofNano Things (IoNT), Proceedings of the fifth international IEEE conference on Internet Technologies and Applications (ITA), 219
- 2017, National Institute of Neurological Disorders and Stroke.
- 2019, Open Brain Computer Interface.
- Saha, 2008, Vertically Arranged Gold Nanowires: An Interface for Live Neuronal Recordings., 1
- Sandberg, 2008, Whole Brain Emulation: A Roadmap.
- Schneider, 2009, Science Fiction and Philosophy: From Time Travel to Superintelligence
- 2018, Data Center Storage Capacity Worldwide from 2016 to 2021 by Segment (in Exabytes).
- Tweedie, 2015, How Do You Move In Virtual Reality? With a Treadmill Like This One I Just Tried.
- 2016, Thirty-Second Session, Agenda Item 3: Promotion and Protection of All Human Rights, Civil, Political, Economic, Social and Cultural Rights, Including the Right to Development.
- 2014, IP Latency Statistics, Verizon.
- Whitby, 2000, How to avoid a robot takeover: political and ethical choices in the design and introduction of intelligent artifacts., Presented presented at the AISB-00 Symposium on Artificial Intelligence, Ethics an (Quasi-) Human Rights
- Zigmond, 2014, Neurobiology of Brain Disorders: Biological Basis of Neurological and Psychiatric Disorders.
Cited by
Sorted by citations
Interface, interaction, and intelligence in generalized brain–computer interfaces
Gao, X., Wang, Y., Chen, X., & Gao, S. (2021) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2021.04.003 · Cited by 306 · see citing works
Summary of over Fifty Years with Brain-Computer Interfaces—A Review
Kawala‐Sterniuk, A., Browarska, N., Al‐Bakri, A. F., Pelc, M., Zygarlicki, J., Šidiková, M., Martínek, R., & Gorzelańczyk, E. J. (2021) · Brain Sciences · doi:10.3390/brainsci11010043 · Cited by 303 · see citing works
“Their application potential is vast and ranges from clinical to home-entertainment applications [10,303].”
BackgroundInfluentialMitusova, K. A., Peltek, O. O., Karpov, T. E., Muslimov, A. R., Zyuzin, M. V., & Timin, A. S. (2022) · Journal of Nanobiotechnology · doi:10.1186/s12951-022-01610-7 · Cited by 186 · see citing works
Age mosaicism across multiple scales in adult tissues
Arrojo e Drigo, R., Lev-Ram, V., Tyagi, S., Ramachandra, R., Deerinck, T., Bushong, E., Phan, S., Orphan, V., Lechene, C., Ellisman, M. H., et al. (2019) · Cell Metabolism · doi:10.1016/j.cmet.2019.05.010 · Cited by 137 · see citing works
A Brief Introduction to Magnetoencephalography (MEG) and Its Clinical Applications
Fred, A. L., Kumar, S. N., Haridhas, A. K., Ghosh, S., Bhuvana, H. P., Sim, W. K. J., Vijayaragavan, V., Givo, F. A. S., Jousmäki, V., Padmanabhan, P., et al. (2022) · Brain Sciences · doi:10.3390/brainsci12060788 · Cited by 83 · see citing works
“29) × 1014 synapses that assist in communication between the neurons [4].”
BackgroundMartínek, R., Ládrová, M., Šidiková, M., Jaroš, R., Behbehani, K., Kahankova, R. V., & Kawala‐Sterniuk, A. (2021) · Sensors · doi:10.3390/s21155186 · Cited by 86 · see citing works
Interfacing with the Brain: How Nanotechnology Can Contribute
Ahmed, A. A. A., Alegret, N., Almeida, B., Álvarez‐Puebla, R. A., Andrews, A. M., Ballerini, L., Barrios‐Capuchino, J. J., Becker, C., Blick, R. H., Bonakdar, S., et al. (2025) · ACS Nano · doi:10.1021/acsnano.4c10525 · Cited by 68 · see citing works
Martínek, R., Ládrová, M., Šidiková, M., Jaroš, R., Behbehani, K., Kahankova, R. V., & Kawala‐Sterniuk, A. (2021) · Sensors · doi:10.3390/s21196343 · Cited by 54 · see citing works
Oxygen and brain death; back from the brink
Bailey, D. M. (2019) · Experimental Physiology · doi:10.1113/ep088005 · Cited by 54 · see citing works
“Structural complexities, computational capabilities and bioenergetic demands reflect whole-brain estimates based on data cited by Azevedo et al. (2009); Bailey (2019b); Cherry et al. (2018); Engl & Attwell (2015); Herculano-Houzel (2011); Kety (1957); Martins et al. (2019); andWaldrop (2012).”
MethodAssessing the Risks Posed by the Convergence of Artificial Intelligence and Biotechnology
O'Brien, J. T., & Nelson, C. (2020) · Health Security · doi:10.1089/hs.2019.0122 · Cited by 49 · see citing works
Conceptualising technology, its development and future: The six genres of technology
Harwood, S., & Eaves, S. (2020) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2020.120174 · Cited by 44 · see citing works
A Survey on Brain-Computer Interface-Inspired Communications: Opportunities and Challenges
Hu, H., Wang, Z., Zhao, X., Li, R., Li, A., Si, Y., Wang, J., Zhou, T., & Xu, T. (2024) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2024.3396847 · Cited by 37 · see citing works
What's Next in Blockchain Research?
Treiblmaier, H., Swan, M., Filippi, P. D., Lacity, M. C., T, T. H. M. I., & Kim, H. (2021) · ACM SIGMIS Database the DATABASE for Advances in Information Systems · doi:10.1145/3447934.3447938 · Cited by 47 · see citing works
“…machine learning (such as audit-logging and image recognition) might be used to automatically coordinate hundreds of fleet-many items at scales ranging from the macro logistics of space settlement to the micro coordination of brain-computer interfaces and medical nanorobots (Martins et al., 2019).”
Self-citationThe global consciousness path to sustainable tourism: a perspective paper
Lew, A. A. (2020) · Tourism Review · doi:10.1108/tr-07-2019-0291 · Cited by 34 · see citing works
Neuromorphic neuromodulation: Towards the next generation of closed-loop neurostimulation
Contreras, L. F. H., Truong, N. D., Eshraghian, J. K., Xu, Z., Huang, Z., Bersani--Veroni, T., Aguilar, I., Leung, W. H., Nikpour, A., & Kavehei, O. (2024) · PNAS Nexus · doi:10.1093/pnasnexus/pgae488 · Cited by 30 · see citing works
Transcending the brain: is there a cost to hacking the nervous system?
Khan, S., & Aziz, T. Z. (2019) · Brain Communications · doi:10.1093/braincomms/fcz015 · Cited by 28 · see citing works
Integration of cloud computing in BCI: A review
Kumar, Y., Kumar, J., & Sheoran, P. (2023) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2023.105548 · Cited by 29 · see citing works
Improving scalability in systems neuroscience
Chen, Z. S., & Pesaran, B. (2021) · Neuron · doi:10.1016/j.neuron.2021.03.025 · Cited by 25 · see citing works
Poststroke Cognitive Impairment Research Progress on Application of Brain‐Computer Interface
Sun, X., Li, M., Li, Q., Yin, H.-N., Jiang, X., Li, H., Sun, Z., & Yang, T. (2022) · BioMed Research International · doi:10.1155/2022/9935192 · Cited by 27 · see citing works
Yao, D., Zhang, Y., Liu, T., Xu, P., Gong, D., Lu, J., Xia, Y., Luo, C., Guo, D., Dong, L., et al. (2020) · Cognitive Neurodynamics · doi:10.1007/s11571-020-09577-7 · Cited by 25 · see citing works
Hayat, H., Nukala, A., Nyamira, A., Fan, J., & Wang, P. (2021) · Biomedical Materials · doi:10.1088/1748-605x/ac15b2 · Cited by 26 · see citing works
“Data collected by BMIs can be uploaded to cloud computing devices and services which can make use of much more powerful computers to create mathematical models of the data using ML [50].”
Optimizing Computer–Brain Interface Parameters for Non-invasive Brain-to-Brain Interface
LaRocco, J., & Paeng, D. (2020) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2020.00001 · Cited by 21 · see citing works
“The accessibility of human BBIs has been previously constrained by CBIs, typically requiring highly invasive implanted devices, imprecise neurostimulation techniques, and immobile equipment (Ye et al., 2016; Martins et al., 2019).”
BackgroundIoT-driven augmented reality and virtual reality systems in neurological sciences
Sahu, M., Gupta, R. V., Ambasta, R. K., & Kumar, P. (2024) · Internet of Things · doi:10.1016/j.iot.2024.101098 · Cited by 23 · see citing works
The extensible Data-Brain model: Architecture, applications and directions
Kuai, H., & Zhong, N. (2020) · Journal of Computational Science · doi:10.1016/j.jocs.2020.101103 · Cited by 17 · see citing works
Swan, M., dos Santos, R. P., & Witte, F. (2022) · Quantum Reports · doi:10.3390/quantum4010008 · Cited by 16 · see citing works
“However, in the “big data” era, the requirements associated with modeling the brain (which has an estimated 86 billion neurons and 242 trillion synapses [21]) are coming within reach.”
BackgroundSelf-citationMerging Minds: The Conceptual and Ethical Impacts of Emerging Technologies for Collective Minds
Lyreskog, D. M., Zohny, H., Savulescu, J., & Singh, I. (2023) · Neuroethics · doi:10.1007/s12152-023-09516-3 · Cited by 15 · see citing works
“What we are likely to see in the coming years is the emergence of TCMs which do not easily lend themselves to be clearly boxed into any of these four categories, under descriptions such as “Cloudminds”, “Mindplexes”, or “Decentralized Selves” [22, 31, 32, 52, 61].”
BackgroundService Provisioning in Edge-Cloud Continuum: Emerging Applications for Mobile Devices
Rodrigues, D. O., Souza, A. M. D., Braun, T. I., Maia, G., Loureiro, A. A. F., & Villas, L. A. (2023) · Journal of Internet Services and Applications · doi:10.5753/jisa.2023.2913 · Cited by 13 · see citing works
“The popularization of immersive virtual worlds also brings interest on moving entities, objects and sensations in and out of the virtual reality with neural interfaces (Sadeghi et al., 2016; Martins et al., 2019; Grau et al., 2014), immersive projections (Takeda et al.”
BackgroundNeuromedia, cognitive offloading, and intellectual perseverance
Turner, C. (2022) · Synthese · doi:10.1007/s11229-022-03472-w · Cited by 16 · see citing works
“According to Martins et al. (2019), the field of neuralnanorobotics is poised to create the first Brain Cloud Interface, or BCI hooked up to the wireless cloud.”
BackgroundSocio-Economic Implications of the Digital Revolution
Helbing, D., & Hausladen, C. I. (2024) · Routledge eBooks · doi:10.4324/9781003119128-32 · Cited by 10 · see citing works
Building blocks for autonomous computing materials: Dimers, trimers, and tetramers
Wei, X., Zhao, Y., Zhuang, Y., & Hernandez, R. (2021) · The Journal of Chemical Physics · doi:10.1063/5.0064988 · Cited by 10 · see citing works
Лозо, О. В., & Onishchenko, O. (2021) · Grassroots Journal of Natural Resources · doi:10.33002/nr2581.6853.040310 · Cited by 10 · see citing works
“The current search for the solution for the climate change, which is happening in information society (Raban, Gordon and Geifman, 2011; Duff, 2015; Martins et al. , 2019; Filippova, 2021), is impossible without the development of cognitive bases and systemic technologies of AI, including the field…”
BackgroundCyborgs R Us: The Bio-Nano Panopticon of Injected Bodies?
Kyrie, V., & Broudy, D. (2022) · International Journal of Vaccine Theory Practice and Research · doi:10.56098/ijvtpr.v2i2.49 · Cited by 10 · see citing works
“, 2018) and neural-nanorobots, comprising endoneurobots, gliabots, and synaptobots that are capable of interfacing with individual neurons and synapses to create a “human brain/cloud interface” (Martins et al., 2019), among other nanotechnologies; b.”
BackgroundNature and Human Brain: Information-sharing Paradigms
Volobuev, A. N., Romanov, D. V., & Иванович, Р. П. (2021) · Bulletin of Science and Practice · doi:10.33619/2414-2948/62/06 · Cited by 9 · see citing works
MEG-Based Detection of Voluntary Eye Fixations Used to Control a Computer
Ovchinnikova, A. O., Vasilyev, A. N., Zubarev, I., Kozyrskiy, B. L., & Shishkin, S. L. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.619591 · Cited by 9 · see citing works
“Moreover, fluent, direct translation of human intentions into actions are often expected from the BCI technology in the future (Martins et al., 2019).”
BackgroundEngineered nanoparticle network models for autonomous computing
Wei, X., Zhao, Y., Zhuang, Y., et al. (2021) · The Journal of Chemical Physics · doi:10.1063/5.0048898 · Cited by 9 · see citing works
Free Will and Autonomy in the Age of Neurotechnologies
Lavazza, A. (2022) · Ethics of science and technology assessment/Wissenschaftsethik und Technikfolgenbeurteilung · doi:10.1007/978-3-030-94032-4_5 · Cited by 7 · see citing works
van Beinum, A. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-04268-8 · Cited by 6 · see citing works
“…when comparing ethical positions of projects informed by each perspective, with transhumanists upholding individual autonomy and personal choice (Martins et al., 2019) while critical posthumanists emphasize the nomadic and relational subjectivity that distributes risk and responsibility across…”
Neuroscience-Driven Solutions for Speech Impairment
S., A. C. G. V., Biradar, S., & Raghavan, R. (2025) · IGI Global eBooks · doi:10.4018/979-8-3693-5464-3.ch006 · Cited by 6 · see citing works
Group-member selection for RSVP-based collaborative brain-computer interfaces
Si, Y., Wang, Z., Xu, G., Wang, Z., Xu, T., Zhou, T., & Hu, H. (2024) · Frontiers in Neuroscience · doi:10.3389/fnins.2024.1402154 · Cited by 6 · see citing works
Romanchuk, N. (2021) · Bulletin of Science and Practice · doi:10.33619/2414-2948/70/23 · Cited by 6 · see citing works
Living-Neuron-Based Autogenerator
Gerasimova, S. A., Beltyukova, A., Fedulina, A., Matveeva, M., Lebedeva, A., & Pisarchik, A. N. (2023) · Sensors · doi:10.3390/s23167016 · Cited by 6 · see citing works
Role of 5G Communication Along With Blockchain Security in Brain-Computer Interfacing
Ahmad, M. M., & Ahuja, K. (2021) · Advances in medical technologies and clinical practice book series · doi:10.4018/978-1-7998-7433-1.ch004 · Cited by 6 · see citing works
Lavazza, A. (2021) · Springer eBooks · doi:10.1007/978-3-030-84494-3_9 · Cited by 6 · see citing works
Yang, Q., & Yu, F. (2024) · Nano Biomedicine and Engineering · doi:10.26599/nbe.2024.9290098 · Cited by 5 · see citing works
Veteran and Brain-Computer Interfaces: The Duty to Care
Guérin, V. (2025) · AJOB Neuroscience · doi:10.1080/21507740.2025.2530948 · Cited by 5 · see citing works
“With nano-robotic devices, Robert Freitas explores what he calls the “brain/cloud interface” that offers external informational storage capacity (Martins et al. 2019).”
TechnoBrainBodies-in-Cultures: An Intersectional Case
Schmitz, S. (2021) · Frontiers in Sociology · doi:10.3389/fsoc.2021.651486 · Cited by 5 · see citing works
“…model of the brain as connectome and an expected “non-destructive, real-time, secure, long-term, and virtually autonomous in vivo system” (Martins et al., 2019, p. 9, italics taken from the original): different types of neuralnanorobots implemented in the brain should enable it to be…”
BackgroundInfluentialNeurochips: Considerations from a neurosurgeon’s standpoint
Rabadán, A. T. (2021) · Surgical Neurology International · doi:10.25259/sni_591_2020 · Cited by 5 · see citing works
“[5,10] Particular attention should be paid to a research that is being performed in animals connecting the brain of rats through the network.[23,30,45,46] DBS, invasive non-DBS, TMS, and neurochips share the objective of improvement the people’s quality of life, but neurochips would speculatively have the advantage of…”
BackgroundCosmetic and Medical Applications of Microbial Nanotechnology
Bhat, E. A., Sajjad, N., & Rather, I. A. (2021) · Springer eBooks · doi:10.1007/978-981-16-1923-6_16 · Cited by 5 · see citing works
Lyreskog, D. M., Zohny, H., Mann, S. P., Singh, I., & Savulescu, J. (2024) · Science and Engineering Ethics · doi:10.1007/s11948-024-00492-2 · Cited by 4 · see citing works
“Many of the reasons for this are technical, in the sense that blockchain technology could alleviate or solve complex practical problems presented to brain interfaces and other TCMs. Martins et al. (2019), for instance, argue for the prospects of a Brain/Cloud interface: “[A] B/CI might serve as a personalised conduit,…”
BackgroundInfluentialNeurosurgery and the Brain-Computer Interface
Rosenfeld, J. V. (2024) · Advances in experimental medicine and biology · doi:10.1007/978-3-031-64892-2_32 · Cited by 4 · see citing works
Self-citationBryndin, E. (2021) · American Journal of Applied Psychology · doi:10.11648/j.ajap.20211003.11 · Cited by 4 · see citing works
Deruelle, F. (2024) · Surgical Neurology International · doi:10.25259/sni_731_2024 · Cited by 4 · see citing works
Math Agents: Computational Infrastructure, Mathematical Embedding, and Genomics
Swan, M., Kido, T., Roland, E., & Santos, R. P. D. (2023) · arXiv · doi:10.48550/arxiv.2307.02502 · Cited by 4 · see citing works
Self-citationКонцепция цифрового трудового правоотношения
Filipova, I., & Tomashevski, K. (2025) · Law Journal of the Higher School of Economics · doi:10.17323/2072-8166.2025.4.114.142 · Cited by 3 · see citing works
Sravanthi, G. S., & Sharma, L. D. (2026) · Frontiers in Neuroscience · doi:10.3389/fnins.2026.1753779 · Cited by 4 · see citing works
Yu, X., Fan, L., Fan, S., & Hong, L. (2026) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2026.1703605 · Cited by 3 · see citing works
Cognitive Augmentation Via a Brain/Cloud Interface
Angelica, A., Opriș, I. C., Lebedev, M., & Boehm, F. (2021) · Contemporary clinical neuroscience · doi:10.1007/978-3-030-54564-2_17 · Cited by 3 · see citing works
Self-citationKalumbilo, L., Mpolya, E., & Vianney, J.-M. (2023) · The Pan African Medical Journal · doi:10.11604/pamj.2023.45.1.36831 · Cited by 3 · see citing works
Neuromorphic Computing Primitives Using Polymer-Networked Nanoparticles
Zhao, Y., Wei, X., & Hernandez, R. (2024) · The Journal of Physical Chemistry C · doi:10.1021/acs.jpcc.4c06055 · Cited by 3 · see citing works
Is There a Place in Human Consciousness Where Surveillance Cannot Go?Noor: A Brain Opera
Pearlman, E. (2020) · Leonardo · doi:10.1162/leon_a_02008 · Cited by 3 · see citing works
Communication of Internal Speech with Communicative Associative Robot via Spectral Neurointerface
Bryndin, E. (2021) · Electrical Science & Engineering · doi:10.30564/ese.v3i1.3255 · Cited by 3 · see citing works
EEG Brain-Computer Interfaces for Internet of Everything (IoE)
Kremenska, A., Lekova, A. K., & Dimitrov, G. P. (2022) · International Conference on Information Technologies (InfoTech) · doi:10.1109/infotech55606.2022.9897097 · Cited by 3 · see citing works
“Researchers in [1] also anticipated that within the next 20–30 years IoE would empower the non-invasive brain-to-brain interfaces.”
BackgroundInfluentialBeyond the Human? A Critique of Transhumanism
Fuchs, T. A. E. (2021) · doi:10.1093/oso/9780192898197.003.0003 · Cited by 2 · see citing works
Brain-computer interface—Brain information reading and activity control
Xu, W., Chen, L., Sui, X., Yun, T., & Liu, Z. (2022) · Chinese Science Bulletin (Chinese Version) · doi:10.1360/tb-2022-0338 · Cited by 3 · see citing works
Nhemachena, A. (2022) · Journal of African American Studies · doi:10.1007/s12111-022-09601-6 · Cited by 2 · see citing works
Feature Selection Using EEG Signals: A Novel Hybrid Binary Particle Swarm Optimization
Nemati, M., Taheri, A., Ghazizadeh, A., Dehkordi, M. B., & Meghdari, A. F. (2022) · RSI International Conference on Robotics and Mechatronics (ICRoM) · doi:10.1109/icrom57054.2022.10025190 · Cited by 2 · see citing works
“Non-invasive BRIs are more popular because of being risk-free and not requiring surgery, but as “there is no free lunch”, the quality of obtained data from non-invasive BRIs is not desirable [16].”
BackgroundRomanchuk, N., Volobuev, A. N., & Bulgakova, S. V. (2023) · Bulletin of Science and Practice · doi:10.33619/2414-2948/95/10 · Cited by 1 · see citing works
Minds and Robots: An Impassable Border
Zizzi, P., & Pregnolato, M. (2021) · Contemporary systems thinking · doi:10.1007/978-3-030-71877-0_15 · Cited by 2 · see citing works
Fares, H., Ronchini, M., Zamani, M., Farkhani, H., Chiappalone, M., Neftci, E. O., & Moradi, F. (2026) · npj Biomedical Innovations. · doi:10.1038/s44385-026-00074-w · Cited by 2 · see citing works
“The raw computational power of the human brain ranges between 10 13 to 10 16 operations/sec 186,187 .”
InfluentialNeurosurgical Considerations for the Brain Computer Interface
Rosenfeld, J. V., Wong, Y. T., Szlawski, J., & Gutman, M. (2022) · Handbook of Neuroengineering · doi:10.1007/978-981-15-2848-4_38-1 · Cited by 1 · see citing works
Self-citationCapo, L., & Lafuente, J. (2022) · Springer eBooks · doi:10.1007/978-3-030-90862-1_6 · Cited by 1 · see citing works
Networked Nanoparticle Arrays for Autonomous Computing: (Invited Paper)
Wei, X., Harazinska, E., Zhao, Y., et al. (2024) · IEEE International Conference on Nanotechnology (IEEE-NANO) · doi:10.1109/nano61778.2024.10628712 · Cited by 1 · see citing works
“…rules of conventional VLSI, and we are inspired by the fact that the brain is an existence proof for such low-energy consumption and high-computing speed materials that do not rely on a von Neumann architecture [15], [16], as it operates at exascale speeds while consuming about 20 W energy [17].”
BackgroundTheater in Latin America: Promoting Cerebral Internet in Jungle
Flores, D. S. (2020) · Saudi Journal of Medicine · doi:10.36348/sjm.2020.v05i01.009
“The most recent researches about cerebral internet published by Berkeley University [5] could be being developed with information of illicital experimentation with cerebral internet in children peruvian of schools such as Innova Schools.”
BackgroundAugmentation of Brain Functions by Nanotechnology
Opriș, I. C., Preza, N., Lebedev, M., Noga, B. R., Chang, S. J., Casanova, M. F., Lupușoru, M. O. D., Pulgar, V. M., Khizroev, S., Bohorquez, J. E., et al. (2021) · Contemporary clinical neuroscience · doi:10.1007/978-3-030-54564-2_11
Self-citationResources, G. J. O. N. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3951302
Frequency Of Brain Atrophy Diagnosed on Computed Tomography
Munir, H., Arshad, N., Ali, A. S., Jamil, M., & John, A. (2022) · Pakistan Journal of Health Sciences · doi:10.54393/pjhs.v3i01.53
Brain neural network, development, microbiome, microbial toxins and COVID-19
Samrezaee, A., Doustmehraban, M., Ghadimi, N., Bahador, S., Barghi, A., Ghanbarzadeh, E., Rigi, A. M., Hedayati, M., & Kimiaeifar, A. (2022) · Journal of Current Biomedical Reports · doi:10.52547/jcbior.3.1.14
Nanobots: Uploading the human brain
Sony, J. D., Ganesh, C. S. S., Bhavani, R. R., et al. (2022) · AIP conference proceedings · doi:10.1063/5.0103487
Mao, C., & Wan, M. (2023) · doi:10.1002/9783527839773.ch11
Neurosurgical Considerations for the Brain Computer Interface
Rosenfeld, J. V., Wong, Y. T., Szlawski, J., & Gutman, M. (2023) · Handbook of Neuroengineering · doi:10.1007/978-981-16-5540-1_38
Self-citationОСОБЕННОСТИ СТИМУЛИРОВАНИЯ ТРУДОВОЙ ДЕЯТЕЛЬНОСТИ персонала предприятий в России и за рубежом
Kirilchuk, S. P., Наливайченко, Е. В., & Стрельбицкий, А. С. (2023) · Региональные проблемы преобразования экономики · doi:10.26726/1812-7096-2023-3-134-144
Exo-edge computing: Pushing the limits of decentralized processing beyond the cloud
Palle, R. R. (2019) · International Journal of Engineering in Computer Science · doi:10.33545/26633582.2019.v1.i2a.98
Technoscientific Convergence and Transhumanist Technocultural Imaginary
Boruah, B. H. (2024) · Springer eBooks · doi:10.1007/978-981-97-4275-2_4
How Can Artificial Intelligence Contribute to Mitigating Climate Change?
Nayak, P., Bag, A., & Maria, A. V. (2025) · Practice, progress, and proficiency in sustainability · doi:10.4018/979-8-3693-8684-2.ch006
Research 4.0 and the Ontological Turn
Nhemachena, A. (2025) · Journal of Religion in Africa · doi:10.1163/15700666-12340331
Diagnosis of Neurological Disorders Using Artificial Intelligence Advances
Malviya, R., Kumar, S., Solanke, A. S., Goyal, P., & Chauhan, K. (2025) · doi:10.1002/9781394347537.ch5
Exploring the Application of Brain-Computer Interface Technology in Stroke Rehabilitation
Cai, Z. (2025) · Highlights in Science Engineering and Technology · doi:10.54097/c4as9v08
Magruk, A. (2025) · Foundations of Science · doi:10.1007/s10699-025-10020-5
“In some time, we are likely to witness the next generation of the internet which will be the Internet of Thoughts – the proposal of a network of data transmission from the human brain to the cloud computing networks (B/CI) in real-time (Martins et al., 2021).”
Metamorphoses of Labor Law Subjects in AI-driven World
Tomashevski, K. L., & Анатольевна, Ф. И. (2026) · Kutafin Law Review · doi:10.17803/2713-0533.2026.1.35.081-099
- Authors
- Martins, N. R. B., Angelica, A., Chakravarthy, K., Svidinenko, Y., Boehm, F. J., Opris, I., Lebedev, M. A., Swan, M., Garan, S. A., Rosenfeld, J. V., Hogg, T., & Freitas, R. A.
- Affiliations
- Lawrence Berkeley National Laboratory (US)
- UC San Diego Health System (US)
- National Research University Higher School of Economics (RU)
- Purdue University West Lafayette (US)
- Uniformed Services University of the Health Sciences (US)
- Institute for Molecular Manufacturing (US)
- Corresponding author
- Martins, Nuno R. B.
- ORCID
- Venue
- Frontiers in Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2019-03-29
- Volume
- 13
- Pages
- 112-112
- ISSN
- 1662-453X (ISSN-L)
- PMC
- PMC6450227
- OpenAlex
- W2927435888
- Cited by
- 91
- References
- 242
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 13 · 2023: 9 · 2022: 16 · 2021: 28 · 2020: 8 · 2019: 4
- FWCI
- 5.85
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Neuroscience (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (submittedVersion, cc-by)
- PubMed Central (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Research University Higher School of Economics (14.641.31.0003)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Physical Sciences › Engineering › Biomedical Engineering › Molecular Communication and Nanonetworks
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- blood-brain barrier, axon initial segment, glial cells, synapses, cognitive disorders, neuromonitoring, cloud computing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-27.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-27.
Cited sources are checked by gpt-6-sol.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review