| Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit. | |
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MedLine Citation:
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PMID: 10879535 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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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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Authors:
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R H Hahnloser; R Sarpeshkar; M A Mahowald; R J Douglas; H S Seung |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Nature Volume: 405 ISSN: 0028-0836 ISO Abbreviation: Nature Publication Date: 2000 Jun |
Date Detail:
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Created Date: 2000-07-31 Completed Date: 2000-07-31 Revised Date: 2006-11-15 |
Medline Journal Info:
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Nlm Unique ID: 0410462 Medline TA: Nature Country: ENGLAND |
Other Details:
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Languages: eng Pagination: 947-51 Citation Subset: IM |
Affiliation:
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Institute of Neuroinformatics ETHZ/UNIZ, Zürich, Switzerland. rh@ai.mit.edu |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Electrophysiology Models, Neurological* Neocortex* Nerve Net* Neural Networks (Computer)* Neurons / physiology* Silicon* |
| Chemical | |
Reg. No./Substance:
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7440-21-3/Silicon |
| Comments/Corrections | |
Comment In:
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Nature. 2000 Jun 22;405(6789):891-2
[PMID:
10879514
]
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Erratum In:
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Nature 2000 Dec 21-28;408(6815):1012 |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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