The Layer 7 Cortical Interface: A Scalable and Minimally Invasive Brain–Computer Interface Platform
Open accessAbstract
Progress toward the development of brain–computer interfaces has signaled the potential to restore, replace, and augment lost or impaired neurological function in a variety of disease states. Existing approaches to developing high-bandwidth brain–computer interfaces rely on invasive surgical procedures or brain-penetrating electrodes, which limit addressable applications of the technology and the number of eligible patients. Here we describe a novel approach to constructing a neural interface, comprising conformable thin-film electrode arrays and a minimally invasive surgical delivery system that together facilitate bidirectional communication with large portions of the cortical surface (enabling both recording and stimulation). We demonstrate the feasibility and safety of delivering reversible implants containing over 2,000 microelectrodes to multiple functional regions in both hemispheres of the brain simultaneously, without requiring a craniotomy or damaging the cortical surface, at an effective insertion rate faster than 40 ms per channel. We further evaluate the performance of this system immediately following implantation for high-density neural recording and visualizing cortical surface activity at spatial and temporal resolutions and extents not previously possible in multiple preclinical large animal studies as well as in a five-patient pilot clinical study involving both anesthetized and awake neurosurgical patients. We characterize the spatial scales at which sensorimotor activity and speech are represented at the cortical surface, demonstrate accurate neural decoding of somatosensory, visual, and volitional walking activity, and achieve precise neuromodulation through cortical stimulation at sub-millimeter scales. The resulting system generates 90 Gb/h of electrophysiologic data, and demonstrates the highly scalable nature of micro-electrocorticography and its utility for next-generation brain-computer interfaces that may expand the patient population that could benefit from neural interface technology.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 20 cited sources checked · 0 supported · 0 flagged
- Findingown data
The authors showed that implants with more than 2,000 microelectrodes could be delivered safely and feasibly to several functional areas in both hemispheres of the Göttingen minipig brain at the same time.
“We demonstrate the safety and feasibility of rapidly delivering reversible implants containing over 2,000 microelectrodes to multiple functional regions in both hemispheres of the Göttingen minipig brain simultaneously, without requiring a craniotomy, at an effective insertion rate faster than 40 ms per channel, without damaging the cortical surface.”
Quote in the paperSubstantial claim- Rests on an assumption: Safety and feasibility in Göttingen minipigs predict safety and feasibility in humans.
- Findingown data
After optimization, electrode connectivity yield exceeded 93%, as confirmed by impedance testing of 4,232 electrodes across eight arrays.
“Process yield was evaluated with respect to electrode connectivity and was confirmed to be >93% after optimization, by impedance characterization of 4,232 electrodes from eight arrays.”
Quote in the paperSubstantial claim - Findingown data
The pia stayed intact after the array was placed and removed.
“The pia remained intact following array placement and removal, and we found no macroscopic evidence of tissue disruption at the cortical surface corresponding to array placement.”
Quote in the paperSubstantial claim - Findingown data
Measurements of platinum electrode impedance showed that impedance magnitude corresponded directly to electrode area.
“Impedance spectra of the platinum electrodes (shown in the photographs and photomicrographs of Figures 2a and 2b, respectively) verified direct correspondence between electrode area and impedance magnitude (Figure 2b).”
Quote in the paperNot a substantial claim - Findingown data
Each 529-channel module has an effective area of 0.48 cm2.
“The effective area of the microelectrode arrays described here is 0.48 cm 2 per 529-channel module, and we have demonstrated that these arrays can be connected in a modular fashion and inserted simultaneously, at an effective rate exceeding 40 s per cm 2 of cortical surface.”
Quote in the paperSubstantial claim
- Findingown data
The insertion rate achieved was under 40 ms for each channel.
“We demonstrate the safety and feasibility of rapidly delivering reversible implants containing over 2,000 microelectrodes to multiple functional regions in both hemispheres of the Göttingen minipig brain simultaneously, without requiring a craniotomy, at an effective insertion rate faster than 40 ms per channel, without damaging the cortical surface.”
Quote in the paperSubstantial claim - Findingown data
Correlation of spontaneous activity between a reference site and other sites on the array fell as distance and frequency increased.
“The degree of correlation decreases with distance (Figure 6a) and with increasing frequency (Figure 6b).”
Quote in the paperSubstantial claim - Findingown data
For 20 μm electrodes spaced 300 μm apart, broadband r2 was about 0.8.
“For example, broadband r 2 is in the range of 0.8 at 300 μm spacing for 20 μm electrodes.”
Quote in the paperSubstantial claim - Findingreasoning
For one 529-electrode array, this equaled an average of under 40-80 ms per electrode across 0.48 cm2 of cortex.
“For a single array of 529 microelectrodes, this corresponds to an average insertion rate of <40-80 ms per electrode over 0.48 cm 2 of cortical surface area.”
Quote in the paperSubstantial claim - Findingown data
Several 529-electrode modules could be combined into larger devices that covered more cortex at the same density without greatly raising insertion complexity, risk, or time.
“The fabricated arrays facilitate alignment and modular assembly, as shown in Figure 4, so that multiple 529-electrode modules can be joined to yield larger constructs covering larger portions of the cortical surface at the same density, without significantly increasing the complexity, risk, or time required for array insertion.”
Quote in the paperSubstantial claim - Findingown data
Impedance changed little across the array from before to after implantation, indicating the arrays were robust during insertion.
“A key factor for our system is also the robustness of arrays during the implantation process, as demonstrated by the ratio of impedance before and after implantation showing little change across”
Quote in the paperSubstantial claim - Findingown data
In one session, evoked responses were recorded from several arrays and several functional brain regions.
“Evoked potentials were obtained across multiple arrays and multiple functional regions of the brain in the same session.”
Quote in the paperSubstantial claim - Findingown data
The procedure did not damage the cortical surface.
“We demonstrate the safety and feasibility of rapidly delivering reversible implants containing over 2,000 microelectrodes to multiple functional regions in both hemispheres of the Göttingen minipig brain simultaneously, without requiring a craniotomy, at an effective insertion rate faster than 40 ms per channel, without damaging the cortical surface.”
Quote in the paperSubstantial claim - Findingown data
Visual cortex stimulation did not produce any saccades.
“No induced saccades were observed during stimulation of the visual cortex.”
Quote in the paperNot a substantial claim - Findingnone given
Every electrode on the array could be used for either recording or stimulation, giving the array bidirectional capability.
“The electrode array is capable of bidirectional function, with every electrode able to perform either recording or stimulation.”
Quote in the paperSubstantial claim - Findingown data
Even electrodes close together showed incomplete correlation, especially at higher frequencies.
“Importantly, even closely spaced electrodes exhibit incompletely correlated activity, particularly at higher frequencies.”
Quote in the paperSubstantial claim - Findingreasoning
Electrode correlation depends on spacing, electrode size, and the frequency band examined.
“The extent to which electrodes exhibit correlated activity depends on distance, electrode size, and the frequency band interrogated.”
Quote in the paperSubstantial claim - Findingown data
Areas beyond the ring showed a brief decrease in cortical activation during the same period.
“Regions farther from the annulus exhibited a transient reduction in cortical activation during this period.”
Quote in the paperNot a substantial claim - Findingown data
Impedance depended predictably on surface area, averaging 497 kΩ for 20 μm electrodes and 32 kΩ for 200 μm electrodes.
“As expected, electrode impedance demonstrates a predictable dependence on electrode surface area, ranging from an average of 497 kΩ for 20 µm electrodes to 32 kΩ for 200 µm electrodes.”
Quote in the paperNot a substantial claim - Findingown data
Arrays over visual cortex produced visual evoked responses after time-locked light stimulation of the retina.
“Robust array-based somatosensory evoked potentials were demonstrated in arrays positioned over somatosensory cortex, corresponding to tactile stimulation of the hindlimbs (Figure 5e), and visual evoked potentials were also obtained in arrays positioned over visual cortex following time-synchronized photostimulation of the retina (Figure 5f).”
Quote in the paperSubstantial claim - Findingown data
Stimulation of cortex raised high-gamma power in the surrounding area recorded by the array for about one second.
“Cortical stimulation evoked an increase in high-gamma-band power across the surrounding region monitored by the array, lasting approximately 1 s.”
Quote in the paperNot a substantial claim - Findingown data
No visible tissue disruption at the cortical surface was found where the array had been placed.
“The pia remained intact following array placement and removal, and we found no macroscopic evidence of tissue disruption at the cortical surface corresponding to array placement.”
Quote in the paperSubstantial claim - Findingown data
After the cranial and dural cuts, insertion took 20 to 40 seconds.
“Insertion time following cranial and dural incisions was 20-40 s.”
Quote in the paperSubstantial claim - Findingown data
Arrays over somatosensory cortex produced strong somatosensory evoked responses when the hindlimbs were touched.
“Robust array-based somatosensory evoked potentials were demonstrated in arrays positioned over somatosensory cortex, corresponding to tactile stimulation of the hindlimbs (Figure 5e), and visual evoked potentials were also obtained in arrays positioned over visual cortex following time-synchronized photostimulation of the retina (Figure 5f).”
Quote in the paperSubstantial claim - Findingnone given
Multiple arrays could be inserted through one slit.
“It is also possible to insert multiple arrays through a single slit.”
Quote in the paperSubstantial claim - Findingown data
As a proof of principle, the authors showed simultaneous implantation across several functional cortical areas in both hemispheres.
“Here, as proof of principle, we have demonstrated concurrent implantation over multiple functional areas of the cortical surface in both hemispheres.”
Quote in the paperSubstantial claim - Findingown data
The implants were delivered without requiring a craniotomy.
“We demonstrate the safety and feasibility of rapidly delivering reversible implants containing over 2,000 microelectrodes to multiple functional regions in both hemispheres of the Göttingen minipig brain simultaneously, without requiring a craniotomy, at an effective insertion rate faster than 40 ms per channel, without damaging the cortical surface.”
Quote in the paperSubstantial claim - Findingown data
A cranial micro-slit technique was developed for implanting electrode arrays.
“We developed a “cranial micro-slit” technique for array implantation.”
Quote in the paperSubstantial claim- Rests on an assumption: Göttingen minipigs have skull thickness comparable to that of adult humans.
- Findingown data
Correlation depends on electrode separation as a function of electrode size and spectral band.
“(b) The dependence of correlation on electrode separation as a function of electrode size and spectral band.”
Quote in the paperNot a substantial claim - Findingown data
A Göttingen minipig underwent cranial micro-slit implantation of subdural microelectrocorticography arrays comprising >2000 microelectrodes, in modules containing 529 channels each.
“(a) A Göttingen minipig undergoes cranial micro-slit implantation (b and c) of a set of subdural microelectrocorticography arrays comprising a total of >2000 microelectrodes, in modules containing 529 channels each (d).”
Quote in the paperSubstantial claim- Rests on an assumption: Göttingen minipigs have skull thickness comparable to that of adult humans.
- Findingown data
Trials reveal increased cortical local field activity immediately following cortical stimulation for regions near the stimulating electrode.
“These trials reveal increased cortical local field activity immediately following cortical stimulation for regions near the stimulating electrode.”
Quote in the paperSubstantial claim - Findingown data
The ratio between in vivo and in vitro impedance at 1 kHz displays minimal change across most of the array following implantation.
“(c) Map of the ratio between in vivo and in vitro impedance at 1 kHz, displaying minimal change across most of the array following implantation.”
Quote in the paperSubstantial claim - Findingown data
Recording of spontaneous neural activity from somatosensory cortex was obtained in a sample of channels from the highlighted 529-channel module.
“(b) Recording of spontaneous neural activity from somatosensory cortex in a sample of channels from the highlighted 529-channel module.”
Quote in the paperSubstantial claim - Findingown data
A quadruply-connected assembly of four 529-electrode modules with a single pocket enables simultaneous implantation of 2116 microelectrodes over 1.92 cm2 of cortical surface area.
“Shown here is a quadruply-connected assembly of four 529electrode modules with a single pocket, for simultaneous implantation of 2116 microelectrodes over 1.92 cm 2 of cortical surface area.”
Quote in the paperSubstantial claim - Findingown data
Single- and multi-channel, one-shot, binary classification decoding efficacy is demonstrated with a template matching approach.
“Single-and multi-channel, one-shot, binary classification decoding efficacy is demonstrated with a template matching approach.”
Quote in the paperSubstantial claim - Findingown data
Modular configurations of multiple 529-channel arrays can be constructed.
“Modular configurations of multiple 529-channel arrays can be constructed.”
Quote in the paperSubstantial claim - Interpretationown data
The described system combines conformable thin-film microelectrode arrays with a minimally invasive surgical delivery system that enables bidirectional communication with large portions of the cortical surface.
“Here we describe a novel approach to constructing a neural interface, comprising conformable thin-film electrode arrays and a minimally invasive surgical delivery system that together facilitate communication with large portions of the cortical surface in bidirectional fashion (enabling both recording and stimulation).”
Quote in the paperSubstantial claim - Premisecitation
The practical impact of brain-computer interfaces remains limited, with only a small number of patients worldwide having received highly customized interfaces through clinical trials.
“Nevertheless, the practical impact of such systems remains limited, with only a small number of patients worldwide having received highly customized interfaces through clinical trials [50][51][52] .”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [50][51][52]
Not checked in the free run.
- Interpretationreasoning
Micro-electrocorticography represents a promising combination of minimal invasiveness and improved signal quality.
“Higher-spatialresolution micro-electrocorticography (µECoG) therefore represents a promising combination of minimal invasiveness and improved signal quality.”
Quote in the paperSubstantial claim - Interpretationreasoning
Having electrodes of different sizes on one array partly enables this range of functions.
“The incorporation of electrodes of different sizes on the same array partially facilitates this range of functions.”
Quote in the paperNot a substantial claim - Study design and conductown data
The safe stimulation threshold was established in vitro for each kind of electrode.
“Safe stimulation thresholds were determined in vitro for each electrode type.”
Quote in the paperSubstantial claim - Interpretationown data
The tested current range was judged acceptable for the 30 pulses per electrode delivered in vivo.
“A total of 50,000 pulses of 10 nC per phase and 100,000 pulses of 20 nC per phase (50 and 100 µA respectively with a 200 µs pulse width) were found to cause no change in impedance on the test electrode, as well as polarization potentials within the water window, so stimulation currents in this range were determined to be acceptable for the 30 pulses per electrode used in vivo.”
Quote in the paperSubstantial claim - Interpretationown data
The described system is a new minimally invasive way to implant high-density arrays reliably.
“The system described here represents a novel, minimally invasive approach to reliably implanting precisely this type of high-density array.”
Quote in the paperSubstantial claim - Interpretationown data
The simple decoding used here shows that electrocorticographic signals from vision and somatosensation are robust when arrays cover large enough areas and respect functional anatomy.
“The rudimentary form of neural decoding we implement here reflects the robustness of electrocorticographic signals from multiple modalities, including somatosensation and vision, when viewed from the perspective of arrays positioned to span sufficiently large surface areas and with attention to functional neuroanatomy.”
Quote in the paperSubstantial claim - Study design and conductown data
Every microelectrode array underwent thorough characterization before implantation.
“All microelectrode arrays were thoroughly characterized prior to insertion.”
Quote in the paperSubstantial claim - Interpretationown data
The ease of reaching both hemispheres and both vision and somatic sensation highlights an advantage of the minimally invasive cranial micro-slit method.
“The relative ease of accessing both hemispheres and multiple functional modalities (vision and somatic sensation) also emphasizes a key advantage to the minimally invasive “cranial micro-slit” approach facilitated by our arrays.”
Quote in the paperSubstantial claim - Interpretationown data
The degree to which closely spaced microelectrodes across a single 529-channel array record correlated or uncorrelated information is relevant to neural decoding.
“The degree to which closely spaced microelectrodes across a single 529-channel array record correlated or uncorrelated information is relevant to neural decoding and is illustrated here in several ways.”
Quote in the paperSubstantial claim
- May combine two claims. 35
- Classified as probably not a substantial claim. 16
May combine two claims.
Findingown dataFor each electrode size, EIS showed the usual rise in cutoff frequency as size decreased, and 1 kHz impedance increased as expected with smaller electrodes.
“EIS measurements for each electrode size display typical positive shifts in cutoff frequencies with decreases in electrode size, and impedance magnitude at 1 kHz also follows the expected upward trend with decreasing electrode size (Figure 2b).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe platform supported dense neural recording, localized cortical stimulation, and accurate decoding of neural signals.
“We further demonstrate the performance of this system for high-density neural recording, focal cortical stimulation, and accurate neural decoding.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe strongest activation formed a ring about 1 mm in radius around the stimulating electrode, sparing the area immediately next to it.
“The most highly activated region formed an annulus of radius approximately 1 mm around, but not immediately surrounding the stimulating electrode.”
Quote in the paperNot a substantial claimMay combine two claims.
FindingreasoningEach custom amplifier PCB contains eight RHD2164 64-channel amplifier chips and one RHS2116 16-channel stimulator/amplifier chip, enabling simultaneous recording from up to 528 channels and stimulation from up to 16 channels.
“The custom amplifier printed circuit boards (PCBs) used to interface with the implanted electrode arrays each contained eight of the RHD2164 64-channel amplifier chips and one of the RHS2116 16-channel stimulator/amplifier chips, allowing for simultaneous recording from up to 528 channels and stimulation from up to 16 channels.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe authors defined a safe stimulation regime for thin-film surface microelectrodes, reached visual cortex minimally invasively, confirmed placement over working visual cortex, stimulated it, and recorded evoked activity.
“Here we characterize a safe operating regime for cortical stimulation from thin-film cortical surface microelectrodes, demonstrate the ability to access visual cortex in a minimally invasive fashion, electrophysiologically confirm array placement over functioning visual cortex, stimulate the cortical surface, and monitor stimulus-evoked cortical activity.”
Quote in the paperSubstantial claimMay combine two claims.
FindingreasoningThe platform offers many channels, dense electrode coverage, and two-way function.
“The system provides high channel counts and high spatial densities of electrode coverage, as well as bidirectional functionality (both neural recording and neural stimulation).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataCV measurement placed the water window at about 1.85 V, with cathodic and anodic limits of 0.65 V and 1.2 V.
“Briefly, the water window was determined by CV measurement to be approximately 1.85 V (with a 0.65 V cathodic and 1.2 V anodic limit), and biphasic pulses were applied at 50 Hz to a test electrode within the range of anticipated stimulation parameters to confirm safe stimulation (Figure 7a).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataImpedance mapping in vivo indicated high electrode yield and uniform impedance.
“In vivo electrode impedance mapping results confirm high electrode yield and impedance uniformity (Figure 2b, inset).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe authors demonstrated three core functions: recording, decoding, and cortical stimulation.
“However, certain functions are commonly required of braincomputer interfaces, and we demonstrate three key functions here: neural recording, neural decoding, and cortical stimulation.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataDecoding with many electrodes across the whole array outperformed any single electrode, reaching 73% accuracy for the left and 67% for the right in offline analysis.
“Multichannel decoding using the large number of electrodes available from the entire array was more robust than decoding using any single electrode, with accuracies reaching 73% on the left and 67% on the right in off-line decoding.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe implanted arrays recorded neural activity across many channels, including spontaneous cortical activity, somatosensory evoked responses, and visual evoked responses.
“Implanted arrays were used for multichannel neural recording using several paradigms, capturing both spontaneous cortical electrographic activity (Figure 5b) as well as somatosensory evoked potentials (Figure 5e) and visual evoked potentials (Figure 5f).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe arrays can be linked modularly and inserted together at an effective rate above 40 s per cm2 of cortex.
“The effective area of the microelectrode arrays described here is 0.48 cm 2 per 529-channel module, and we have demonstrated that these arrays can be connected in a modular fashion and inserted simultaneously, at an effective rate exceeding 40 s per cm 2 of cortical surface.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe team inserted double modules in vivo (1,058 channels over 0.96 cm2) and quadruple modules in vitro (2,116 channels each over 1.92 cm2).
“We performed in vivo insertions of doubly connected modules (1,058 channels over 0.96 cm 2 of cortical surface area), and in vitro insertions of quadruply connected modules (2,116 channels each covering 1.92 cm 2 of surface area).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataA double module halved the effective average insertion rate, and in vivo speeds reached under 20 ms per electrode.
“We note that use of a doubly connected module halves the effective average insertion rate, and in this manner have achieved effective speeds as fast as <20 ms per electrode in vivo.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe authors showed that high-density microelectrode arrays could be inserted safely and feasibly with a new minimally invasive cranial micro-slit method.
“We have demonstrated the safety and feasibility of inserting our high-density microelectrode arrays using a novel, minimally invasive “cranial micro-slit” technique (Figure 3).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataDelivering 50,000 pulses at 10 nC per phase and 100,000 at 20 nC per phase (50 and 100 μA, 200 μs width) left test electrode impedance unchanged and kept polarization potentials inside the water window.
“A total of 50,000 pulses of 10 nC per phase and 100,000 pulses of 20 nC per phase (50 and 100 µA respectively with a 200 µs pulse width) were found to cause no change in impedance on the test electrode, as well as polarization potentials within the water window, so stimulation currents in this range were determined to be acceptable for the 30 pulses per electrode used in vivo.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataIntraoperative endoscopic view immediately following subdural placement of one thin-film array shows the electrode tail and traces entering the subdural space through a cranial slit.
“(b) Intraoperative endoscopic view immediately following subdural placement of one thin-film array, after shim removal, showing the electrode tail and traces entering the subdural space through a cranial slit”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataIntraoperative fluoroscopic image shows four 529-electrode arrays in place, two over each hemisphere.
“(d) Intraoperative fluoroscopic image (dorsoventral projection) showing four 529-electrode arrays in place, two over each hemisphere.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataSomatosensory evoked potentials correspond to tactile stimulation of the left hindlimb, with traces spanning 1 s and maximum peak-to-peak signal approximately 80 μV.
“(e) Somatosensory evoked potentials corresponding to tactile stimulation of the left hindlimb.Traces span 1 s and the maximum peak-to-peak signal is approximately 80 µV.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe Layer 7 Cortical Interface acquires neural activity and delivers stimulation.
“This schematic illustration shows how neural activity is acquired from and stimulated by the Layer 7 Cortical Interface.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingnone givenThe sampling rate for recording is set at 20 kHz per channel, generating data at a rate over 2.5 GB per minute for each set of 1,024 channels.
“The sampling rate for recording is set at 20 kHz per channel, generating data at a rate over 2.5 GB per minute for each set of 1,024 channels.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingnone givenThe recording computers interface with either controller via a custom configuration of Intan RHX Data Acquisition Software, allowing real-time event-triggered averaging.
“The recording computers interface with either controller via a custom configuration of the Intan Technologies RHX Data Acquisition Software, which allows for real-time event-triggered averaging in addition to base functionality.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingnone givenEach amplifier board allows a hardware reference from one of 16 sites distributed across the array.
“In addition, each board allows for a hardware reference from one of 16 sites distributed across the array.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataMore distant regions exhibit less evoked activity while still being responsive to stimulation.
“While still being responsive to stimulation, more distant regions exhibit less evoked activity.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataVisual evoked potentials are obtained from photostimulation of the left eye.
“(f) Visual evoked potentials from photostimulation of the left eye.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
PremisecitationElectrocorticography has facilitated capture of high-quality signals for effective use in brain-computer interfaces in several applications, including motor and speech neural prostheses.
“In practice, electrocorticography (ECoG) has already facilitated capture of high quality signals for effective use in brain-computer interfaces in several applications, including motor and speech neural prostheses 7,22,24,56,[64][65][66][67][68][69][70] .”
Quote in the paperSubstantial claim0 of 1 sources checked- cites 7,22,24,56,[64][65][66][67][68][69][70]
Not checked in the free run.
May combine two claims.
PremisereasoningNon-penetrating cortical surface microelectrodes are a potentially attractive alternative and form the basis of the described system.
“For this reason, non-penetrating cortical surface microelectrodes represent a potentially attractive alternative and form the basis of the system described here 53,63 .”
Quote in the paperSubstantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationHigh-density microelectrode arrays have been replacing macroelectrode arrays, offering smaller features and improved spatial resolution.
“As a result, high-density microelectrode arrays have been replacing more traditional macroelectrode arrays, offering smaller features and improved spatial resolution [53][54][55][56][57][58] .”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [53][54][55][56][57][58]
Not checked in the free run.
May combine two claims.
PremisecitationExisting brain-computer interfaces depend on invasive surgery or electrodes that penetrate the brain, which restricts the applications they can address and the number of patients eligible.
“Existing brain-computer interfaces rely on invasive surgical procedures or brain-penetrating electrodes, which limit addressable applications of the technology and the number of eligible patients.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites 20,[59][60][61][62]
Not checked in the free run.
Classified as probably not a substantial claim.
PremisecitationIt is not yet clear whether softer penetrating electrodes offer a substantially different tradeoff.
“It is not yet clear whether approaches involving softer penetrating electrodes offer a substantially different tradeoff 20,59 .”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
PremisecitationPenetrating microelectrode arrays enable high-spatial-resolution recordings for brain-computer interfaces but cause invasiveness and tissue damage that increase with the number of implanted electrodes.
“Microelectrode arrays that penetrate the brain have facilitated high-spatial-resolution recordings for brain-computer interfaces, but at the cost of invasiveness and tissue damage that scale with the number of implanted electrodes 20,[59][60][61][62] .”
Quote in the paperSubstantial claim0 of 1 sources checked- cites 20,[59][60][61][62]
Not checked in the free run.
May combine two claims.
InterpretationreasoningSurface micro-electrocorticography arrays offer an appealing balance between invasiveness and signal quality and are attractive alternatives or complements to penetrating arrays.
“For these reasons surface microarrays (micro-electrocorticography or µECoG arrays) embody an appealing tradeoff between invasiveness and signal quality, and are attractive as an alternative or complement to arrays of electrodes that penetrate the cortical surface.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationPenetrating microelectrode arrays enable single-cell recording but are more invasive and vary in tissue damage and long-term stability.
“Microelectrode arrays that penetrate the brain facilitate single-cell recordings, at the cost of greater invasiveness, with varying degrees of brain tissue damage and long-term stability [92][93][94] .”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [92][93][94]
Not checked in the free run.
May combine two claims.
Interpretationown dataThe arrays are intended for subdural placement through 400 μm skull cuts made with a precision oscillating blade, with real-time imaging and fiberoptic endoscopy, at over 1,000 electrodes per minute.
“The microelectrode arrays are designed to be inserted into the subdural space through 400-micron-wide skull incisions made using a precision oscillating blade, guided by real-time imaging and fiberoptic endoscopy, at a rate of more than 1,000 electrodes per minute, and to provide 1,000-fold higher electrode density than standard cortical grids.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationRecent studies have shown that high-density electrocorticography can decode speech representations, allowing words and short sentences to be articulated.
“More recent work has demonstrated the utility of high-density ECoG in decoding neural representations of speech, enabling the articulation of words and short sentences 6,69,99 .”
Quote in the paperNot a substantial claim0 of 3 sources checkedMay combine two claims.
Interpretationown dataActivity near kilohertz frequencies can be relatively uncorrelated even over short distances, which fits nearby but weakly coupled neurons.
“High-frequency activity approaching the kilohertz range can exhibit relatively uncorrelated activity even at short range, consistent with the coexistence of nearby but relatively uncoupled neurons.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningThe platform may speed progress in decoding and encoding neural signals and may broaden the group of patients who could benefit from neural interfaces.
“Such a system promises to accelerate efforts to better decode and encode neural signals, and to expand the patient population that could benefit from neural interface technology.”
Quote in the paperNot a substantial claim- Rests on an assumption: Safety and feasibility in Göttingen minipigs predict safety and feasibility in humans.
May combine two claims.
InterpretationreasoningThe Layer 7 Cortical Interface is a modular, scalable, and minimally invasive brain-computer interface platform.
“The system we describe here, the Layer 7 Cortical Interface, is a modular, scalable, minimally invasive brain-computer interface platform.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
PremisecitationElectrocorticography and micro-electrocorticography have enabled high-resolution temporal and spatial recordings useful in vivo, including for brain-computer interfaces.
“In practice, however, electrocorticography (ECoG) and microelectrocorticography (µECoG) have facilitated high temporal-and spatial-resolution recordings for effective use in in vivo applications 56,64,65 , including brain-computer interfaces.”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [56] Deku, F. et al. Amorphous silicon carbide ultramicroelectrode arrays for neural stimulation and recording. J. Neural Eng. 15, 016007 (2018). source
Not checked in the free run.
- cites [64] 2021, A Systematic Review of the Incidence, Prevalence, Costs, and Activity and Work Limitations of Amputation, Osteoarthritis, Rheumatoid Arthritis, Back Pain, Multiple Sclerosis, Spinal Cord Injury, Stroke, and Traumatic Brain Injury in the United States: A 2019 Update. Archives of Physical Medicine and Rehabilitation
Not checked in the free run.
- cites [65] source
Not checked in the free run.
Probably not a substantial claim: may not pass S4 (based).
Interpretationnone givenThe platform is intended to bring high-density, high-channel-count neural interfaces to the many millions of neurologic patients who could benefit.
“The system is designed to deliver the benefits of high-density, high-channel-count neural interfaces to the millions of patients with neurologic disorders who stand to benefit from this technology.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenThe arrays are intended to give 1,000 times the electrode density of standard cortical grids.
“The microelectrode arrays are designed to be inserted into the subdural space through 400-micron-wide skull incisions made using a precision oscillating blade, guided by real-time imaging and fiberoptic endoscopy, at a rate of more than 1,000 electrodes per minute, and to provide 1,000-fold higher electrode density than standard cortical grids.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationBrain-computer interface decoding can work with multiunit activity, local field potentials, or micro-electrocorticography, and does not require single-unit spikes.
“Effective neural decoding for brain-computer interfaces can be achieved using multiunit activity, local field potentials, or micro-electrocorticography, without relying on single-unit action potentials 22,[84][85][86][87][88][89][90][91] .”
Quote in the paperSubstantial claim0 of 1 sources checked- cites 22,[84][85][86][87][88][89][90][91]
Not checked in the free run.
May combine two claims.
Interpretationown dataThe platform can be deployed quickly and minimally invasively over large cortical areas, reversibly and without trauma.
“Here we have described a modular and highly scalable brain-computer interface platform capable of rapid, minimally invasive surgical deployment over multiple large areas of the cortical surface in a reversible and atraumatic manner.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationNew thin-film micro-electrocorticography arrays have safely conformed to the brain for months and reliably recorded multi-unit and single-unit activity in some locations.
“Recently developed thin-film µECoG arrays have demonstrated the ability to conform to the brain surface safely for several months while reliably recording multi-unit and single-unit activity in certain anatomic settings 53,57 .”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [53] Wellman, S. M. et al. A Materials Roadmap to Functional Neural Interface Design. Adv. Funct. Mater. 28, 1701269 (2018). source
Not checked in the free run.
- cites [57] Li et al. Ultra-Long-Term Reliable Encapsulation Using an Atomic Layer Deposited HfO2/Al2O3/HfO2 Triple-Interlayer for Biomedical Implants. Coatings 9, 579 (2019). source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationMultiple groups have used surface arrays to link neural activity to motor function for controlling prostheses in patients with physical impairment.
“Several groups have used surface array techniques to correlate neural activity with motor function for the control of neural prostheses in physically impaired patients 7,67,68,[95][96][97][98] .”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites 7,67,68,[95][96][97][98]
Not checked in the free run.
May combine two claims.
InterpretationreasoningSurface-conforming arrays are much less invasive, easier to insert and remove without tissue damage, and possibly more stable long-term, though being farther from neurons may limit single-cell communication.
“Microelectrode arrays that conform to the brain surface are considerably less invasive, more easily inserted and removed without damage to brain tissue, and potentially more stable in the long-term, but their greater distance from target neurons may limit single-cell communication.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S4 (based).
Study design and conductreasoningGeneral anesthesia was maintained with isoflurane at levels sufficient to produce analgesia without suppressing electrocorticographic activity.
“General anesthesia was maintained with isoflurane at levels sufficient to produce analgesia without suppressing electrocorticographic activity, a balance that was facilitated by the minimally invasive nature of the procedure.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataA stimulation waveform was used for in vitro confirmation of safe polarization potential.
“(a) Stimulation waveform used for in vitro confirmation of safe polarization potential, with the 100 µA current overlaid on the waveform for reference.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationnone givenThe microelectrode arrays provide multichannel data used in electrophysiologic paradigms for recording spontaneous and stimulus-evoked neural activity, decoding, and focal stimulation across functional brain regions.
“The microelectrode arrays provide multichannel data that is used in a variety of electrophysiologic paradigms to perform neural recording of both spontaneous and stimulus-evoked neural activity as well as decoding and focal stimulation of neural activity across a variety of functional brain regions.”
Quote in the paperSubstantial claim
The authors state this as an assumption.
For substantial clinical benefit, implantation must be minimally invasive, reversible, and free of neural tissue damage.
“In order to achieve meaningful clinical impact on the large populations of patients who stand to benefit from brain-computer interface technologies, surgical procedures involved in implanting neural interfaces should be minimally invasive and reversible, and avoid damaging neural tissue.”
The authors state this as an assumption.
Damage to tissue and overall procedure duration must not scale with the number of channels.
“Tissue damage and total procedural time cannot be allowed to increase in proportion to channel number, as contemporary channel counts, already reaching the many thousands, will likely increase by orders of magnitude with further progress in this field.”
The paper relies on this without support.
Safety and feasibility in Göttingen minipigs predict safety and feasibility in humans.
“We demonstrate the safety and feasibility of rapidly delivering reversible implants containing over 2,000 microelectrodes to multiple functional regions in both hemispheres of the Göttingen minipig brain simultaneously, without requiring a craniotomy, at an effective insertion rate faster than 40 ms per channel, without damaging the cortical surface.”
The authors state this as an assumption.
Implants can be expected to cause some tissue encapsulation.
“Any implant may be expected to induce a certain degree of tissue encapsulation, but the anticipated tissue damage associated with removing multiple penetrating microelectrodes is greater than that associated with removing and replacing cortical surface arrays.”
The paper relies on this without support.
Taking out several penetrating microelectrodes is expected to damage more tissue than removing and replacing surface arrays.
“Any implant may be expected to induce a certain degree of tissue encapsulation, but the anticipated tissue damage associated with removing multiple penetrating microelectrodes is greater than that associated with removing and replacing cortical surface arrays.”
The paper relies on this without support.
Göttingen minipigs have skull thickness comparable to that of adult humans.
“selected for well characterized functional neuroanatomy as well as skull thickness comparable to that of adult humans”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Approaches to increase density and lower invasiveness of ECoG are currently being developed for humans and animal models.
“Different approaches to increase the density and lower the invasiveness of ECoG are currently being developed for use in humans and animal models176–182.”
From The speech neuroprosthesis (2024) · cites this paper as [182]
Cites
Neuronal ensemble control of prosthetic devices by a human with tetraplegia
Hochberg, L. R., Serruya, M. D., Friehs, G. M., Mukand, J. A., Saleh, M., Caplan, A. H., Branner, A., Chen, D., Penn, R. D., & Donoghue, J. P. (2006) · Nature · doi:10.1038/nature04970 · Cited by 3,295 · see citing works
Katan, M., & Luft, A. (2018) · Seminars in Neurology · doi:10.1055/s-0038-1649503 · Cited by 2,137 · 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
High-performance neuroprosthetic control by an individual with tetraplegia
Collinger, J. L., Wodlinger, B., Downey, J. E., Wang, W., Tyler-Kabara, E. C., Weber, D. J., McMorland, A. J., Velliste, M., Boninger, M. L., & Schwartz, A. B. (2013) · The Lancet · doi:10.1016/s0140-6736(12)61816-9 · Cited by 1,848 · see citing works
Learning to control a brain–machine interface for reaching and grasping by primates
Carmena, J. M., Lebedev, M. A., Crist, R. E., O'Doherty, J. E., Santucci, D. M., Dimitrov, D. F., Patil, P. G., Henriquez, C. S., & Nicolelis, M. A. L. (2003) · PLoS Biology · doi:10.1371/journal.pbio.0000042 · Cited by 1,761 · see citing works
A low-power low-noise cmos for amplifier neural recording applications
Harrison, R. R., & Charles, C. (2003) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2003.811979 · Cited by 1,695 · see citing works
Cortical control of a prosthetic arm for self-feeding
Velliste, M., Perel, S., Spalding, M. C., Whitford, A. S., & Schwartz, A. B. (2008) · Nature · doi:10.1038/nature06996 · Cited by 1,591 · see citing works
Real-time prediction of hand trajectory by ensembles of cortical neurons in primates
Wessberg, J., Stambaugh, C. R., Kralik, J. D., Beck, P. D., Laubach, M., Chapin, J. K., Kim, J., Biggs, S. J., Srinivasan, M. A., & Nicolelis, M. A. L. (2000) · Nature · doi:10.1038/35042582 · Cited by 1,491 · see citing works
An Integrated Brain-Machine Interface Platform With Thousands of Channels
Musk, E., & Neuralink (2019) · Journal of Medical Internet Research · doi:10.2196/16194 · Cited by 1,206 · see citing works
The sensations produced by electrical stimulation of the visual cortex
Brindley, G. S., & Lewin, W. S. (1968) · The Journal of Physiology · doi:10.1113/jphysiol.1968.sp008519 · Cited by 1,170 · see citing works
Viventi, J., Kim, D.-H., Vigeland, L., Frechette, E. S., Blanco, J. A., Kim, Y.-S., Avrin, A. E., Tiruvadi, V. R., Hwang, S.-W., Vanleer, A. C., et al. (2011) · Nature Neuroscience · doi:10.1038/nn.2973 · Cited by 1,136 · see citing works
Matthews, K. A., Xu, W., Gaglioti, A. H., Holt, J. B., Croft, J. B., Mack, D., & McGuire, L. C. (2019) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2018.06.3063 · Cited by 1,124 · see citing works
Electronic dura mater for long-term multimodal neural interfaces
Minev, I. R., Musienko, P., Hirsch, A., Barraud, Q., Wenger, N., Moraud, E. M., Gandar, J., Capogrosso, M., Milekovic, T., Asboth, L., et al. (2015) · Science · doi:10.1126/science.1260318 · Cited by 1,082 · see citing works
An Integrated Brain-Machine Interface Platform With Thousands of ChannelsPreprint
Musk, E., & Neuralink (2019) · bioRxiv · doi:10.1101/703801 · Cited by 1,036 · see citing works
Temporal structure in neuronal activity during working memory in macaque parietal cortex
Pesaran, B., Pezaris, J. S., Sahani, M., Mitra, P. P., & Andersen, R. A. (2002) · Nature Neuroscience · doi:10.1038/nn890 · Cited by 1,029 · see citing works
NeuroGrid: recording action potentials from the surface of the brain
Khodagholy, D., Gelinas, J. N., Thesen, T., Doyle, W., Devinsky, O., Malliaras, G. G., & Buzsáki, G. (2015) · Nature Neuroscience · doi:10.1038/nn.3905 · Cited by 938 · see citing works
Restoring cortical control of functional movement in a human with quadriplegia
Bouton, C. E., Shaikhouni, A., Annetta, N. V., Bockbrader, M. A., Friedenberg, D. A., Nielson, D. M., Sharma, G., Sederberg, P. B., Glenn, B. C., Mysiw, W. J., et al. (2016) · Nature · doi:10.1038/nature17435 · Cited by 924 · see citing works
Biran, R., Martin, D. C., & Tresco, P. A. (2005) · Experimental Neurology · doi:10.1016/j.expneurol.2005.04.020 · Cited by 893 · see citing works
Speech synthesis from neural decoding of spoken sentences
Anumanchipalli, G. K., Chartier, J., & Chang, E. F. (2019) · Nature · doi:10.1038/s41586-019-1119-1 · Cited by 883 · see citing works
Cook, M. J., O'Brien, T. J., Berkovic, S. F., Murphy, M. A., Morokoff, A. P., Fabinyi, G., D'Souza, W. J., Yerra, R., Archer, J. S., Litewka, L., et al. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70075-9 · Cited by 881 · see citing works
Self-citationCochlear implants: A remarkable past and a brilliant future
Wilson, B. S., & Dorman, M. F. (2008) · Hearing Research · doi:10.1016/j.heares.2008.06.005 · Cited by 875 · see citing works
Brain-Controlled Interfaces: Movement Restoration with Neural Prosthetics
Schwartz, A. B., Cui, X. T., Weber, D. J., & Moran, D. W. (2006) · Neuron · doi:10.1016/j.neuron.2006.09.019 · Cited by 792 · see citing works
A low-power integrated circuit for a wireless 100-electrode neural recording system.
Harrison, R. R., Watkins, P. T., Kier, R. J., Lovejoy, R. O., Black, D. J., Greger, B., & Solzbacher, F. (2007) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2006.886567 · Cited by 782 · see citing works
Flexible and Stretchable Electronics for Biointegrated Devices
Kim, D.-H., Ghaffari, R., Lu, N., & Rogers, J. A. (2012) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-071811-150018 · Cited by 749 · cited 1× · see citing works
“In practice, electrocorticography (ECoG) has already facilitated capture of high quality signals for effective use in brain–computer interfaces in several applications, including motor and speech neural prostheses 7,19,32,34,72,81–87 .”
MethodInferring single-trial neural population dynamics using sequential auto-encoders
Pandarinath, C., O’Shea, D. J., Collins, J., Józefowicz, R., Stavisky, S. D., Kao, J. C., Trautmann, E. M., Kaufman, M. T., Ryu, S. I., Hochberg, L. R., et al. (2018) · Nature Methods · doi:10.1038/s41592-018-0109-9 · Cited by 672 · see citing works
Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation
Lebedev, M., & Nicolelis, M. A. L. (2017) · Physiological Reviews · doi:10.1152/physrev.00027.2016 · Cited by 655 · see citing works
Walking naturally after spinal cord injury using a brain–spine interface
Lorach, H., Galvez, A., Spagnolo, V., Martel, F., Karakas, S., Intering, N., Vat, M., Faivre, O., Harte, C., Komi, S., et al. (2023) · Nature · doi:10.1038/s41586-023-06094-5 · Cited by 631 · cited 1× · see citing works
“Brain–computer interfaces have shown promise as systems for restoring, replacing, and augmenting lost or impaired neurological function in a variety of contexts, including paralysis from stroke and spinal cord injury, blindness, and some forms of cognitive impairment 1– 21 .”
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
Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria
Moses, D. A., Metzger, S. L., Liu, J. R., Anumanchipalli, G. K., Makin, J. G., Sun, P. F., Chartier, J., Dougherty, M. E., Liu, P. M., Abrams, G. M., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2027540 · Cited by 582 · see citing works
A high-performance speech neuroprosthesis
Willett, F. R., Kunz, E. M., Fan, C., Avansino, D. T., Wilson, G. H., Choi, E. Y., Kamdar, F., Glasser, M. F., Hochberg, L. R., Druckmann, S., et al. (2023) · Nature · doi:10.1038/s41586-023-06377-x · Cited by 581 · see citing works
Pandarinath, C., Nuyujukian, P., Blabe, C. H., Sorice, B. L., Saab, J., Willett, F. R., Hochberg, L. R., Shenoy, K. V., & Henderson, J. M. (2017) · eLife · doi:10.7554/elife.18554 · Cited by 566 · see citing works
A high-performance neural prosthesis enabled by control algorithm design
Gilja, V., Nuyujukian, P., Chestek, C. A., Cunningham, J. P., Yu, B. M., Fan, J. M., Churchland, M. M., Kaufman, M. T., Kao, J. C., Ryu, S. I., et al. (2012) · Nature Neuroscience · doi:10.1038/nn.3265 · Cited by 564 · see citing works
Wireless Recording in the Peripheral Nervous System with Ultrasonic Neural Dust
Seo, D., Neely, R. M., Shen, K., Singhal, U., Alon, E., Rabaey, J. M., Carmena, J. M., & Maharbiz, M. M. (2016) · Neuron · doi:10.1016/j.neuron.2016.06.034 · Cited by 557 · see citing works
Decoding two-dimensional movement trajectories using electrocorticographic signals in humans
Schalk, G., Kubanek, J., Miller, K. J., Anderson, N., Leuthardt, E. C., Ojemann, J. G., Limbrick, D. D., Moran, D. W., Gerhardt, L. A., & Wolpaw, J. R. (2007) · Journal of Neural Engineering · doi:10.1088/1741-2560/4/3/012 · Cited by 527 · see citing works
A high-performance neuroprosthesis for speech decoding and avatar control
Metzger, S. L., Littlejohn, K. T., Silva, A. B., Moses, D. A., Seaton, M. P., Wang, R., Dougherty, M. E., Liu, J. R., Wu, P., Berger, M. A., et al. (2023) · Nature · doi:10.1038/s41586-023-06443-4 · Cited by 522 · cited 2× · see citing works
“In practice, electrocorticography (ECoG) has already facilitated capture of high quality signals for effective use in brain–computer interfaces in several applications, including motor and speech neural prostheses 7,19,32,34,72,81–87 .”
BackgroundMethodSimeral, J. D., Kim, S.-P., Black, M. J., Donoghue, J. P., & Hochberg, L. R. (2011) · Journal of Neural Engineering · doi:10.1088/1741-2560/8/2/025027 · Cited by 496 · see citing works
Two-dimensional movement control using electrocorticographic signals in humans
Schalk, G., Miller, K. J., Anderson, N., Wilson, J. A., Smyth, M. D., Ojemann, J. G., Moran, D. W., Wolpaw, J. R., & Leuthardt, E. C. (2008) · Journal of Neural Engineering · doi:10.1088/1741-2560/5/1/008 · Cited by 481 · see citing works
Dobelle, W. H., Mladejovsky, M. G., & Girvin, J. P. (1974) · Science · doi:10.1126/science.183.4123.440 · Cited by 440 · see citing works
Kim, S.-P., Simeral, J. D., Hochberg, L. R., Donoghue, J. P., & Black, M. J. (2008) · Journal of Neural Engineering · doi:10.1088/1741-2560/5/4/010 · Cited by 399 · see citing works
An Electrocorticographic Brain Interface in an Individual with Tetraplegia
Wang, W., Collinger, J. L., Degenhart, A. D., Tyler‐Kabara, E. C., Schwartz, A. B., Moran, D. W., Weber, D. J., Wodlinger, B., Vinjamuri, R. K., Ashmore, R. C., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0055344 · Cited by 396 · see citing works
Cortical Local Field Potential Encodes Movement Intentions in the Posterior Parietal Cortex
Scherberger, H., Jarvis, M. R., & Andersen, R. A. (2005) · Neuron · doi:10.1016/j.neuron.2005.03.004 · Cited by 389 · see citing works
A Materials Roadmap to Functional Neural Interface Design
Wellman, S. M., Eles, J. R., Ludwig, K. A., Seymour, J. P., Michelson, N. J., McFadden, W. E., Vazquez, A. L., & Kozai, T. D. Y. (2018) · Advanced Functional Materials · doi:10.1002/adfm.201701269 · Cited by 389 · see citing works
A MEMS-based flexible multichannel ECoG-electrode array
Rubehn, B., Bosman, C., Oostenveld, R., Fries, P., & Stieglitz, T. (2009) · Journal of Neural Engineering · doi:10.1088/1741-2560/6/3/036003 · Cited by 387 · see citing works
Weiland, J. D., Liu, W., & Humayun, M. S. (2005) · Annual Review of Biomedical Engineering · doi:10.1146/annurev.bioeng.7.060804.100435 · Cited by 371 · see citing works
Clinical translation of a high-performance neural prosthesis
Gilja, V., Pandarinath, C., Blabe, C. H., Nuyujukian, P., Simeral, J. D., Sarma, A. A., Sorice, B. L., Perge, J. A., Jarosiewicz, B., Hochberg, L. R., et al. (2015) · Nature Medicine · doi:10.1038/nm.3953 · Cited by 343 · see citing works
Prediction of arm movement trajectories from ECoG-recordings in humans
Tobias Pistohl, A., Tonio Ball, A., Schulze‐Bonhage, A., Aertsen, A., & Mehring, C. (2007) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2007.10.001 · Cited by 330 · see citing works
Selecting the signals for a brain–machine interface
Andersen, R. A., Musallam, S., & Pesaran, B. (2004) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2004.10.005 · Cited by 329 · see citing works
Chung, J. E., Joo, H. R., Fan, J. L., Liu, D. F., Barnett, A. H., Chen, S., Geaghan-Breiner, C., Karlsson, M. P., Karlsson, M., Lee, K. Y., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.11.002 · Cited by 327 · see citing works
Self-citationMachine translation of cortical activity to text with an encoder–decoder framework
Makin, J. G., Moses, D. A., & Chang, E. F. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0608-8 · Cited by 321 · see citing works
Epidemiology of worldwide spinal cord injury: a literature review
Kang, Y., Ding, H., Zhou, H., Wei, Z., Liu, L., Pan, D., & Feng, S. (2017) · Journal of Neurorestoratology · doi:10.2147/jn.s143236 · Cited by 315 · see citing works
A high-performance speech neuroprosthesisPreprint
Willett, F. R., Kunz, E. M., Fan, C., et al. (2023) · bioRxiv · doi:10.1101/2023.01.21.524489 · Cited by 284 · see citing works
Decoding natural grasp types from human ECoG
Tobias Pistohl, A., Schulze‐Bonhage, A., Aertsen, A., Mehring, C., & Tonio Ball, A. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.06.084 · Cited by 249 · 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
Speech synthesis from ECoG using densely connected 3D convolutional neural networks
Angrick, M., Herff, C., Mugler, E., Tate, M. C., Slutzky, M. W., Krusienski, D. J., & Schultz, T. (2019) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab0c59 · Cited by 225 · see citing works
Real-time decoding of question-and-answer speech dialogue using human cortical activity
Moses, D. A., Leonard, M. K., Makin, J. G., & Chang, E. F. (2019) · Nature Communications · doi:10.1038/s41467-019-10994-4 · Cited by 224 · see citing works
Bansal, A. K., Truccolo, W., Vargas-Irwin, C. E., & Donoghue, J. P. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00781.2011 · Cited by 200 · see citing works
A Neural Probe With Up to 966 Electrodes and Up to 384 Configurable Channels in 0.13 $\mu$m SOI CMOS
López, C. M., Putzeys, J., Raducanu, B. C., Ballini, M., Wang, S., Andrei, A., Rochus, V., Vandebriel, R., Severi, S., Hoof, C. A. V., et al. (2017) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2016.2646901 · Cited by 198 · see citing works
Neural recording and stimulation using wireless networks of microimplants
Lee, J.-H., Leung, V., Lee, A., Huang, J., Asbeck, P. M., Mercier, P. P., Shellhammer, S. J., Larson, L. E., Laiwalla, F., & Nurmikko, A. V. (2021) · Nature Electronics · doi:10.1038/s41928-021-00631-8 · Cited by 195 · see citing works
Chan, T. L., Friedman, D. S., Bradley, C., & Massof, R. W. (2017) · JAMA Ophthalmology · doi:10.1001/jamaophthalmol.2017.4655 · Cited by 190 · see citing works
Speech discrimination in deaf subjects with cochlear implants
Eddington, D. K. (1980) · The Journal of the Acoustical Society of America · doi:10.1121/1.384827 · Cited by 186 · 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
Zhuang, J., Truccolo, W., Vargas-Irwin, C. E., & Donoghue, J. P. (2010) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2010.2047015 · Cited by 174 · see citing works
Control of a brain–computer interface without spike sorting
Fraser, G. W., Chase, S. M., Whitford, A. S., & Schwartz, A. B. (2009) · Journal of Neural Engineering · doi:10.1088/1741-2560/6/5/055004 · Cited by 168 · see citing works
Mixture of Trajectory Models for Neural Decoding of Goal-Directed Movements
Yu, B. M., Kemere, C. T., Santhanam, G., Afshar, A., Ryu, S. I., Meng, T. H. Y., Sahani, M., & Shenoy, K. V. (2007) · Journal of Neurophysiology · doi:10.1152/jn.00482.2006 · Cited by 156 · see citing works
3D Parylene sheath neural probe for chronic recordings
Kim, B. J., Kuo, J. T. W., Hara, S. A., Lee, C. D., Liu, Y., Gutierrez, C. A., Hoang, T., Pikov, V., & Meng, E. F. (2013) · Journal of Neural Engineering · doi:10.1088/1741-2560/10/4/045002 · Cited by 155 · see citing works
Bansal, A. K., Vargas-Irwin, C. E., Truccolo, W., & Donoghue, J. P. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00532.2010 · Cited by 148 · see citing works
Human brain mapping with multithousand-channel PtNRGrids resolves spatiotemporal dynamics
Tchoe, Y., Bourhis, A. M., Cleary, D. R., Stedelin, B., Lee, J., Tonsfeldt, K. J., Brown, E. C., Siler, D. A., Paulk, A. C., Yang, J. C., et al. (2022) · Science Translational Medicine · doi:10.1126/scitranslmed.abj1441 · Cited by 135 · see citing works
Decoding hand gestures from primary somatosensory cortex using high-density ECoG
Branco, M. P., Freudenburg, Z. V., Aarnoutse, E. J., Bleichner, M. G., Vansteensel, M. J., & Ramsey, N. F. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.004 · Cited by 127 · see citing works
Johnson, B. C., Gambini, S., Izyumin, I., Moin, A., Zhou, A., Alexandrov, G., Santacruz, S. R., Rabaey, J. M., Carmena, J. M., & Muller, R. (2017) · 2017 Symposium on VLSI Circuits · doi:10.23919/vlsic.2017.8008543 · Cited by 119 · see citing works
Wang, W., Degenhart, A. D., Collinger, J. L., Vinjamuri, R. K., Sudre, G. P., Adelson, P. D., Holder, D. L., Leuthardt, E. C., Moran, D. W., Boninger, M. L., et al. (2009) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2009.5333704 · Cited by 118 · see citing works
Optimizing the Decoding of Movement Goals from Local Field Potentials in Macaque Cortex
Markowitz, D. A., Wong, Y. T., Gray, C. M., & Pesaran, B. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.4165-11.2011 · Cited by 110 · see citing works
Decoding Movement From Electrocorticographic Activity: A Review
Volkova, K., Lebedev, M., Kaplan, A., & Ossadtchi, A. E. (2019) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2019.00074 · Cited by 108 · see citing works
Nakanishi, Y., Yanagisawa, T., Shin, D., Fukuma, R., Chen, C., Kambara, H., Yoshimura, N., Hirata, M., Yoshimine, T., & Koike, Y. (2013) · PLoS ONE · doi:10.1371/journal.pone.0072085 · Cited by 103 · see citing works
Decoding spoken English from intracortical electrode arrays in dorsal precentral gyrus
Wilson, G. H., Stavisky, S. D., Willett, F. R., Avansino, D. T., Kelemen, J. N., Hochberg, L. R., Henderson, J. M., Druckmann, S., & Shenoy, K. V. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/abbfef · Cited by 103 · see citing works
O’Leary, G., Groppe, D. M., Valiante, T. A., Verma, N., & Genov, R. (2018) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2018.2869579 · Cited by 98 · see citing works
Biederman, W., Yeager, D. J., Narevsky, N., Leverett, J., Neely, R., Carmena, J. M., Alon, E., & Rabaey, J. M. (2015) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2014.2384736 · Cited by 96 · see citing works
Jeong, J., Laiwalla, F., Lee, J.-H., Ritasalo, R., Pudas, M., Larson, L. E., Leung, V., & Nurmikko, A. V. (2018) · Advanced Functional Materials · doi:10.1002/adfm.201806440 · Cited by 96 · see citing works
Conformable polyimide-based μECoGs: Bringing the electrodes closer to the signal source
Vomero, M., Porto Cruz, M. F., Zucchini, E., Ciarpella, F., Delfino, E., Carli, S., Boehler, C., Asplund, M., Ricci, D., Fadiga, L., et al. (2020) · Biomaterials · doi:10.1016/j.biomaterials.2020.120178 · Cited by 95 · see citing works
Shi, Z., Zheng, F., Zhou, Z., Li, M., Fan, Z., Ye, H., Zhang, S., Xiao, T., Chen, L., Tao, T. H., et al. (2019) · Advanced Science · doi:10.1002/advs.201801617 · Cited by 94 · see citing works
Low-Power Circuits for Brain–Machine Interfaces
Sarpeshkar, R., Wattanapanitch, W., Arfin, S. K., Rapoport, B. I., Mandal, S., Baker, M. W., Fee, M. S., Musallam, S., & Andersen, R. A. (2008) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2008.2003198 · Cited by 91 · see citing works
Self-citationModel-Based Neural Decoding of Reaching Movements: A Maximum Likelihood Approach
Kemere, C. T., Shenoy, K. V., & Meng, T. H. Y. (2004) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2004.826675 · Cited by 91 · see citing works
Amorphous silicon carbide ultramicroelectrode arrays for neural stimulation and recording
Deku, F., Cohen, Y., Joshi-Imre, A., Kanneganti, A., Gardner, T. J., & Cogan, S. F. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aa8f8b · Cited by 89 · see citing works
A 1024-Channel Simultaneous Recording Neural SoC with Stimulation and Real-Time Spike Detection
Yoon, D.-Y., Pinto, S., Chung, S., Merolla, P. A., Koh, T.-W., & Seo, D. (2021) · Symposium on VLSI Circuits · doi:10.23919/vlsicircuits52068.2021.9492480 · Cited by 85 · see citing works
Silicon-Integrated High-Density Electrocortical Interfaces
Ha, S., Akinin, A., Park, J., Kim, C., Wang, H., Maier, C., Mercier, P. P., & Cauwenberghs, G. (2016) · Proceedings of the IEEE · doi:10.1109/jproc.2016.2587690 · Cited by 84 · see citing works
Wang, S., López, C. M., Garakoui, S. K., Chun, H., Gómez, D., Sijbers, W., Putzeys, J., Martens, E., Craninckx, J., & Helleputte, N. V. (2019) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2019.2942450 · Cited by 82 · see citing works
A silk-based self-adaptive flexible opto-electro neural probe
Zhou, Y., Gu, C., Liang, J., Zhang, B., Yang, H., Zhou, Z., Li, M., Sun, L., Tao, T. H., & Wei, X. (2022) · Microsystems & Nanoengineering · doi:10.1038/s41378-022-00461-4 · Cited by 81 · see citing works
Brain2Char: a deep architecture for decoding text from brain recordings
Sun, P., Anumanchipalli, G. K., & Chang, E. F. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/abc742 · Cited by 77 · see citing works
High-resolution neural recordings improve the accuracy of speech decoding
Duraivel, S., Rahimpour, S., Chiang, C.-H., Trumpis, M., Wang, C., Barth, K., Harward, S. C., Lad, S. P., Friedman, A. H., Southwell, D. G., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-42555-1 · Cited by 75 · see citing works
Hara, S. A., Kim, B. J., Kuo, J. T. W., Lee, C. D., Meng, E., & Pikov, V. (2016) · Journal of Neural Engineering · doi:10.1088/1741-2560/13/6/066020 · Cited by 57 · see citing works
Improved polyimide thin-film electrodes for neural implants
Ordonez, J. S., Boehler, C., Schüettler, M., & Stieglitz, T. (2012) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2012.6347149 · Cited by 56 · see citing works
Towards a Distributed, Chronically-Implantable Neural Interface
Ahmadi, N., Cavuto, M. L., Feng, P., Leene, L. B., Maslik, M., Mazza, F., Savolainen, O. W., Szostak, K. M., Bouganis, C.-S., Ekanayake, J., et al. (2019) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner.2019.8716998 · Cited by 56 · see citing works
Wissel, T., Pfeiffer, T., Frysch, R., Knight, R. T., Chang, E. F., Hinrichs, H., Rieger, J. W., & Rose, G. (2013) · Journal of Neural Engineering · doi:10.1088/1741-2560/10/5/056020 · Cited by 53 · see citing works
Collinger, J. L., Gaunt, R. A., & Schwartz, A. B. (2018) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2018.11.005 · Cited by 52 · see citing works
Grasp Detection from Human ECoG during Natural Reach-to-Grasp Movements
Tobias Pistohl, A., Schmidt, T., Tonio Ball, A., Schulze‐Bonhage, A., Aertsen, A., & Mehring, C. (2013) · PLoS ONE · doi:10.1371/journal.pone.0054658 · Cited by 51 · see citing works
Flexible, high-resolution thin-film electrodes for human and animal neural research
Chiang, C., Wang, C., Barth, K. J., Rahimpour, S., Trumpis, M., Duraivel, S., Rachinskiy, I., Dubey, A., Wingel, K., Wong, M. K., et al. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac02dc · Cited by 49 · see citing works
Li, C., Cauwe, M., Yang, Y., Schaubroeck, D., Mader, L., & Op de Beeck, M. (2019) · Coatings · doi:10.3390/coatings9090579 · Cited by 46 · see citing works
Vomero, M., Castagnola, E., Ordonez, J. S., Carli, S., Zucchini, E., Maggiolini, E., Gueli, C., Goshi, N., Ciarpella, F., Cea, C., et al. (2017) · Advanced Biosystems · doi:10.1002/adbi.201700081 · Cited by 32 · see citing works
Lamont, C., Grego, T., Nanbakhsh, K., Shah Idil, A., Giagka, V, Vanhoestenberghe, A., Cogan, S., & Donaldson, N. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/abf0d6 · Cited by 28 · see citing works
Classification of Articulator Movements and Movement Direction from Sensorimotor Cortex Activity
Salari, E., Freudenburg, Z. V., Branco, M. P., Aarnoutse, E. J., Vansteensel, M. J., & Ramsey, N. F. (2019) · Scientific Reports · doi:10.1038/s41598-019-50834-5 · Cited by 26 · see citing works
Synchrony surfacing: Epicortical recording of correlated action potentials
Bockhorst, T., Pieper, F., Engler, G., Stieglitz, T., Galindo-Leon, E. E., & Engel, A. K. (2018) · European Journal of Neuroscience · doi:10.1111/ejn.14167 · Cited by 25 · see citing works
The business of brain–computer interfaces
Smalley, E. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0231-y · Cited by 25 · see citing works
The Argo: A 65,536 channel recording system for high density neural recording in vivoPreprint
Sahasrabuddhe, K., Khan, A. A., Singh, A., Stern, T. M., Ng, Y., Tadić, A., Orel, P., LaReau, C., Pouzzner, D., Nishimura, K. A., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.17.209403 · Cited by 20 · see citing works
Weltman, A., Xu, H., Kee, S., Berger, T. W., Song, D. B., & Meng, E. F. (2017) · IEEE International Conference on Micro Electro Mechanical Systems (MEMS) · doi:10.1109/memsys.2017.7863357 · Cited by 14 · see citing works
High-Density, Actively Multiplexed µECoG Array on Reinforced Silicone Substrate
Rachinskiy, I., Wong, L., Chiang, C.-H., Wang, C., Trumpis, M., Ogren, J. I., Hu, Z., McLaughlin, B., & Viventi, J. (2022) · Frontiers in Nanotechnology · doi:10.3389/fnano.2022.837328 · Cited by 14 · see citing works
Flagged first, then by citations
Research works printed but not linked: 4
- 2008, Neural Stimulation and Recording Electrodes. Annu. Rev. Biomed. Eng, 10, 275
- 2021, A Systematic Review of the Incidence, Prevalence, Costs, and Activity and Work Limitations of Amputation, Osteoarthritis, Rheumatoid Arthritis, Back Pain, Multiple Sclerosis, Spinal Cord Injury, Stroke, and Traumatic Brain Injury in the United States: A 2019 Update. Archives of Physical Medicine and Rehabilitation, 102, 115
- 2017, National and State Estimates of the Numbers of Adults and Children with Active Epilepsy — United States, 2015. MMWR Morb. Mortal. Wkly. Rep, 66, 821
- 2011, Highly Conformable Conducting Polymer Electrodes for In Vivo Recordings. Adv. Mater, 23, H268
Cited by
Sorted by citations
Bio-inspired electronics: Soft, biohybrid, and “living” neural interfaces
Boufidis, D., Garg, R., Angelopoulos, E., Cullen, D. K., & Vitale, F. (2025) · Nature Communications · doi:10.1038/s41467-025-57016-0 · Cited by 154 · see citing works
Silva, A. B., Littlejohn, K. T., Liu, J. R., Moses, D. A., & Chang, E. F. (2024) · Nature Reviews Neuroscience · doi:10.1038/s41583-024-00819-9 · Cited by 103 · see citing works
Direct laser writing of 3D electrodes on flexible substrates
Brown, M. A., Zappitelli, K. M., Singh, L., Yuan, R., Bemrose, M. A., Brogden, V., Miller, D. J., Smear, M. C., Cogan, S. F., & Gardner, T. J. (2023) · Nature Communications · doi:10.1038/s41467-023-39152-7 · Cited by 87 · see citing works
A biodegradable and self-deployable electronic tent electrode for brain cortex interfacing
Bae, J., Hwang, G., Kim, Y.-S., Jeon, J., Chae, M., Kim, J., Lee, S., Kim, S., Lee, J., Choi, S., et al. (2024) · Nature Electronics · doi:10.1038/s41928-024-01216-x · Cited by 79 · see citing works
Self-citationOrigami-inspired soft fluidic actuation for minimally invasive large-area electrocorticography
Coles, L., Ventrella, D., Carnicer‐Lombarte, A., Elmi, A., Troughton, J. G., Mariello, M., Hadwe, S. E., Woodington, B. J., Bacci, M. L., Malliaras, G. G., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-50597-2 · Cited by 55 · see citing works
Restoring Speech Using Brain–Computer Interfaces
Stavisky, S. D. (2025) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-110122-012818 · Cited by 33 · see citing works
Hettick, M., Ho, E., Poole, A. J., Monge, M., Papageorgiou, D., Takahashi, K., LaMarca, M., Trietsch, D., Reed, K., Murphy, M. E., et al. (2025) · Nature Biomedical Engineering · doi:10.1038/s41551-025-01501-w · Cited by 33 · see citing works
Self-citationVatsyayan, R., Lee, J., Bourhis, A. M., Tchoe, Y., Cleary, D. R., Tonsfeldt, K. J., Lee, K., Montgomery‐Walsh, R., Paulk, A. C., Hoi Sang, U., et al. (2023) · MRS Bulletin · doi:10.1557/s43577-023-00537-0 · Cited by 25 · see citing works
Chen, J., Dhuliyawalla, A., Garcia, R., Robledo, A., Woods, J. E., Alrashdan, F. T., O’Leary, S., Husain, A., Price, A., Crosby, S., et al. (2024) · Nature Biomedical Engineering · doi:10.1038/s41551-024-01281-9 · Cited by 24 · see citing works
Konrad, P. E., Gelman, K., Lawrence, J. D., Bhatia, S., Dister, J., Sharma, R., Ho, E., Byun, Y. W., Mermel, C. H., & Rapoport, B. I. (2025) · Journal of Neural Engineering · doi:10.1088/1741-2552/adaeed · Cited by 14 · see citing works
Self-citationLong-term unsupervised recalibration of cursor BCIsPreprint
Wilson, G. H., Willett, F. R., Stein, E. A., Kamdar, F. B., Avansino, D. T., Hochberg, L. R., Shenoy, K. V., Druckmann, S., & Henderson, J. M. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.02.03.527022 · Cited by 14 · see citing works
Toward an interventional science of recovery after coma
Schiff, N. D. (2024) · Neuron · doi:10.1016/j.neuron.2024.04.027 · Cited by 11 · see citing works
3D soft microbump electrodes for elastic interaction with brain tissue
Ji, B., Sun, F., Xue, K., He, S., Guo, J., You, X., Liu, Q., Jin, M., Bai, R., Wang, X., et al. (2025) · npj Flexible Electronics · doi:10.1038/s41528-025-00480-x · Cited by 10 · see citing works
Hahn, N. V., Stein, E. A., Donoghue, J. P., Simeral, J. D., Hochberg, L. R., & Willett, F. R. (2025) · medRxiv · doi:10.1101/2025.07.02.25330310 · Cited by 11 · see citing works
Long‐Term Stable Subdural Recordings Enabled by Fibrosis‐Resistant Hydrogel‐Integrated µECoG Arrays
Chen, L., Zhong, H., Wang, L., Xu, L., Fan, W., Zhao, Y., Zhang, H., Shen, Y., Wu, K., Fu, X., et al. (2025) · Advanced Science · doi:10.1002/advs.202515453 · Cited by 10 · see citing works
Optimal placement of high-channel visual prostheses in human retinotopic visual cortex
van Hoof, R., Lozano, A., Wang, F., Klink, P. C., Roelfsema, P. R., & Goebel, R. (2025) · Journal of Neural Engineering · doi:10.1088/1741-2552/adaeef · Cited by 6 · see citing works
Towards precise synthetic neural codes: high-dimensional stimulation with flexible electrodes
Kim, R., Liu, Y., Zhang, J., Xie, C., & Luan, L. (2025) · npj Flexible Electronics · doi:10.1038/s41528-025-00447-y · Cited by 4 · see citing works
Park, S., Lipton, M. H., & Dadarlat, M. C. (2024) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad83c0 · Cited by 5 · see citing works
Eichler, G., Gilhotra, Y., Zeng, N., Kim, M., Shepard, K., & Carloni, L. P. (2025) · IEEE/ACM International Symposium on Microarchitecture (MICRO) · doi:10.1145/3725843.3756032 · Cited by 3 · see citing works
From trade-offs to translation: An interdisciplinary roadmap for neurotechnology
Serrano, R. R., Troughton, J. G., Mirkhani, N., Martínez, N., Mariello, M., Tsigarides, J., Williamson, S., Sapriza, J., Luca, I. S., Dominguez‐Alfaro, A., et al. (2026) · Science Advances · doi:10.1126/sciadv.aee8595 · Cited by 2 · see citing works
Invasive Brain–Computer Interfaces: 25 Years of Clinical Trials, Scientific and Practical Issues
Mokienko, O. A. (2024) · Annals of the Russian academy of medical sciences · doi:10.15690/vramn17994 · Cited by 1 · see citing works
Offenberg, E. C., Berezutskaya, J., Müller, L., Freudenburg, Z. V., Ramsey, N. F., & Vansteensel, M. J. (2026) · Clinical Neurophysiology · doi:10.1016/j.clinph.2026.2111940 · Cited by 1 · see citing works
Iris 128x: open-source 128 channel headstages for neural stimulation and recording
Jacobs, E. K., Monge, M., Switalla, A., Frederick, R. A., & Deku, F. (2025) · Journal of Neural Engineering · doi:10.1088/1741-2552/ae1876 · Cited by 1 · see citing works
Self-citationDistinct laminar origins of high-gamma and low-frequency ECoG signals revealed by optogeneticsPreprint
Gardères, P.-M., Feldman, D. E., & Bouchard, K. E. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.02.680142 · Cited by 1 · see citing works
Toward an Optical BCI: Overcoming the Limitation of Low Sampling Rate for Decoding Limb Movements
Park, S., Lipton, M. H., & Dadarlat, M. C. (2025) · Springer briefs in electrical and computer engineering · doi:10.1007/978-3-031-80497-7_11
Modulation: Fine Tuning and Resetting of Neurological Function
Gelman, K., Ranjan, M., Konrad, P. E., & Rezai, A. R. (2025) · Cambridge University Press eBooks · doi:10.1017/9781009597852.007
Self-citationBrain–Computer Interface: Toward an Emancipatory Neurotechnology from the Global South
Nin, C. E. T., & Cumpa, J. W. G. (2026) · Artificial intelligence · doi:10.5772/intechopen.1013185
Gardères, P.-M., Feldman, D. E., & Bouchard, K. E. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2516293123
Optimal Size of Electrocorticography Grids for Classification of Hand Movements
Offenberg, E. C., Keller, D., Mehrkanoon, S., Berezutskaya, J., Vansteensel, M. J., & Branco, M. P. (2026) · Neuroinformatics · doi:10.1007/s12021-026-09807-z
Costa, A., Davidson, S., Rakhamimova, E., Bartula, B., Geralemou, S., Wang, W., & Bergese, S. D. (2026) · Frontiers in Bioscience-Landmark · doi:10.31083/fbl48402
- Authors
- Hettick, M., Ho, E., Poole, A. J., Monge, M., Papageorgiou, D., Takahashi, K., LaMarca, M., Trietsch, D., Reed, K., Murphy, M., Rider, S., Gelman, K. R., Byun, Y. W., Hanson, T., Tolosa, V., Lee, S.-H., Bhatia, S., Konrad, P. E., Mager, M., Mermel, C. H., & Rapoport, B. I.
- Corresponding author
- Rapoport, Benjamin I.
- ORCID
- Venue
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Published
- 2022-01-02
- OpenAlex
- W4205266536
- Cited by
- 31
- References
- 104
- Citations by year
- 2026: 6 · 2025: 14 · 2024: 7 · 2023: 3 · 2022: 1
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Locations
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- brain-computer interface, cortical surface mapping, neural decoding, neuromodulation, sensorimotor cortex, speech decoding
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 2026-10-05.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-05.
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