Non-destructive whole-brain monitoring using nanorobots: neural electrical data rate requirements.
Open accessAbstract
Neuronanorobotics, a promising future medical technology, may provide the ultimate tool for achieving comprehensive non-destructive real-time in vivo monitoring of the many information channels in the human brain. This paper focuses on the electrical information channel and employs a novel electrophysiological approach to estimate the data rate requirements, calculated to be (5.52 ± 1.13) x 1016 bits/sec in an entire living human brain, for acquiring, transmitting, and storing singleneuron electrical information using medical nanorobots, corresponding to an estimated synapticprocessed spike rate of (4.31 ± 0.86) x 1015 spikes/sec.
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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”
From Human Brain/Cloud Interface (2019) · cites this paper as Martins et al., 2012
Synapses, 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”
From Human Brain/Cloud Interface (2019) · cites this paper as Martins et al., 2012
Another 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”
From Human Brain/Cloud Interface (2019) · cites this paper as Martins et al., 2012
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”
From Human Brain/Cloud Interface (2019) · cites this paper as Martins et al., 2012
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”
From Human Brain/Cloud Interface (2019) · cites this paper as Martins et al., 2012
The 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”
From Human Brain/Cloud Interface (2019) · cites this paper as Martins et al., 2012
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”
From Human Brain/Cloud Interface (2019) · cites this paper as Martins et al., 2012
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).”
From Human Brain/Cloud Interface (2019) · cites this paper as Martins et al., 2012
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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., et al. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00112 · Cited by 91 · see citing works
Self-citation
- Authors
- MARTINS, N. R. B., ERLHAGEN, W., & FREITAS, R. A.
- Affiliations
- University of Minho (PT)
- Institute for Molecular Manufacturing (US)
- Venue
- International Journal of Machine Consciousness
- Publisher
- World Scientific Pub Co Pte Ltd
- Published
- 2012-06
- Volume
- 04
- Issue
- 01
- Pages
- 109-140
- ISSN
- 1793-8430 (ISSN-L)
- 1793-8473
- OpenAlex
- W2107503898
- Cited by
- 15
- References
- 11
- Citations by year
- 2024: 4 · 2023: 2 · 2022: 1 · 2021: 2 · 2019: 2 · 2018: 2 · 2016: 1 · 2015: 1
- FWCI
- 0.13
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- other-oa
- Locations
- International Journal of Machine Consciousness (publishedVersion)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, other-oa)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by-nc-nd)
- 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 › Neural dynamics and brain function
- Keywords
- medical nanorobots, electrophysiology, data rate requirements, neural information transmission
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