Cited by 1,293Neural dynamics and brain functionAdvanced Memory and Neural ComputingAnalog and Mixed-Signal Circuit Design

Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit

Hahnloser, Richard H. R., Sarpeshkar, Rahul, Mahowald, Misha A., Douglas, Rodney J., Seung, H. Sebastian·2000·Nature

Abstract

Digital circuits such as the flip-flop use feedback to achieve multistability and nonlinearity to restore signals to logical levels, for example 0 and 1. Analogue feedback circuits are generally designed to operate linearly, so that signals are over a range, and the response is unique. By contrast, the response of cortical circuits to sensory stimulation can be both multistable and graded. We propose that the neocortex combines digital selection of an active set of neurons with analogue response by dynamically varying the positive feedback inherent in its recurrent connections. Strong positive feedback causes differential instabilities that drive the selection of a set of active neurons under the constraints embedded in the synaptic weights. Once selected, the active neurons generate weaker, stable feedback that provides analogue amplification of the input. Here we present our model of cortical processing as an electronic circuit that emulates this hybrid operation, and so is able to perform computations that are similar to stimulus selection, gain modulation and spatiotemporal pattern generation in the neocortex.

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Crossref · 10.1038/35016072

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  • A network with rectified linear units can be trained several times faster than its equivalent with tanh units and allows deeper networks with vanishing gradient problems.

    “This network with ReLUs has the ability to get trained several times faster than its equivalent with tanh units [37] as well as it also allows to go deeper with vanishing gradient problems.”

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Authors
Hahnloser, R. H. R., Sarpeshkar, R., Mahowald, M. A., Douglas, R. J., & Seung, H. S.
Affiliations
  • ETH Zurich (CH)
  • Massachusetts Institute of Technology (US)
  • Institute of Neuroinformatics (CH)
Corresponding author
Hahnloser, Richard H. R.
Venue
Nature
Published
2000-06-22
Volume
405
Issue
6789
Pages
947-951
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W1572063013
Cited by
1,293
References
28
Citations by year
2026: 31 · 2025: 57 · 2024: 90 · 2023: 94 · 2022: 109 · 2021: 188 · 2020: 217 · 2019: 163 · 2018: 127 · 2017: 60 · 2016: 3 · 2015: 9 · 2014: 12 · 2013: 5 · 2012: 3
FWCI
6.38
Type
journal article
Language
en
Update notices
erratum (2000-12-21)
Open access
closed
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
  • Physical Sciences › Engineering › Biomedical Engineering › Analog and Mixed-Signal Circuit Design
Keywords
cortical circuits, positive feedback, multistability, stimulus selection, gain modulation, recurrent connectivity, synaptic weights, neuromorphic hardware
MeSH terms
Electrophysiology, Models, Neurological, Nerve Net, Neurons, Silicon, Neural Networks, Computer, Neocortex

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