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Title: Power Consumption During Neuronal Computation

Abstract

Maintaining the ability of the nervous system to perceive, remember, process, and react to the outside world necessitates a continuous energy supply. However, the overall power consumption is remarkably low, which has inspired engineers to mimic nervous systems in designing artificial cochlea, retinal implants, and brain–computer interfaces (BCIs) to improve the quality of life in patients. Such neuromorphic devices are both energy efficient and increasingly able to emulate many functions of the human nervous system. We explore the energy constraints of neuronal signaling within biology, review the quantitative tradeoff between energy use and information processing, and ask whether the biophysics and design of nerve cells minimizes energy consumption.

Authors:
 [1];  [2]
  1. Univ. College London (United Kingdom)
  2. Ludwig Maximilian Univ., Munich (Germany)
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1565222
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Proceedings of the IEEE
Additional Journal Information:
Journal Volume: 102; Journal Issue: 5; Journal ID: ISSN 0018-9219
Publisher:
Institute of Electrical and Electronics Engineers
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; Biological information theory; biological neural networks; biological optimization; cellular biophysics; energy consumption; energy efficiency

Citation Formats

Sengupta, Biswa, and Stemmler, Martin B. Power Consumption During Neuronal Computation. United States: N. p., 2014. Web. doi:10.1109/jproc.2014.2307755.
Sengupta, Biswa, & Stemmler, Martin B. Power Consumption During Neuronal Computation. United States. https://doi.org/10.1109/jproc.2014.2307755
Sengupta, Biswa, and Stemmler, Martin B. Mon . "Power Consumption During Neuronal Computation". United States. https://doi.org/10.1109/jproc.2014.2307755. https://www.osti.gov/servlets/purl/1565222.
@article{osti_1565222,
title = {Power Consumption During Neuronal Computation},
author = {Sengupta, Biswa and Stemmler, Martin B.},
abstractNote = {Maintaining the ability of the nervous system to perceive, remember, process, and react to the outside world necessitates a continuous energy supply. However, the overall power consumption is remarkably low, which has inspired engineers to mimic nervous systems in designing artificial cochlea, retinal implants, and brain–computer interfaces (BCIs) to improve the quality of life in patients. Such neuromorphic devices are both energy efficient and increasingly able to emulate many functions of the human nervous system. We explore the energy constraints of neuronal signaling within biology, review the quantitative tradeoff between energy use and information processing, and ask whether the biophysics and design of nerve cells minimizes energy consumption.},
doi = {10.1109/jproc.2014.2307755},
journal = {Proceedings of the IEEE},
number = 5,
volume = 102,
place = {United States},
year = {Mon Apr 14 00:00:00 EDT 2014},
month = {Mon Apr 14 00:00:00 EDT 2014}
}

Journal Article:
Free Publicly Available Full Text
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Citation Metrics:
Cited by: 59 works
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Figures / Tables:

Fig. 1 Fig. 1: Energy efficiency of an analog and a pulsatile system. The analog system (blue) is represented by a continuous-time RC filter, while the pulsatile system (green) is represented by a serial M-bit register. (a) Analog system consumes increasingly less power as the SNR decreases, while the power required formore » a digital device stays nearly constant. (b) For SNRs below 40 dB, analog systems are more efficient than their pulsatile counterparts. (c) Analog systems have higher information capacity at intermediate levels of power consumption; below and above these levels, pulsatile systems have higher capacities. Based on analysis in [15].« less

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