The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
A model of neocortex
Abstract
Prompted by considerations about (i) the compositionality of cognitive functions, (ii) the physiology of individual cortical neurons, (iii) the role of accurately timed spike patterns in cortex, and (iv) the regulation of global cortical activity, we suggest that the dynamics of cortex on the 1-ms time scale may be described as the activation of circuits of the synfire-chain type (Abeles 1982, 1991). We suggest that the fundamental computational unit in cortex may be a wave-like spatio-temporal pattern of synfire type, and that the binding mechanism underlying compositionality in cognition may be the accurate synchronization of synfire waves that propagate simultaneously on distinct, weakly coupled, synfire chains. We propose that Hebbian synaptic plasticity may result in a superposition of synfire chains in cortical connectivity, whereby a given neuron participates in many distinct chains. We investigate the behaviour of a much-simplified model of cortical dynamics devised along these principles. Calculations and numerical experiments are performed based on an assumption of randomness of stored chains, in the style of statistical physics. It is demonstrated that: (i) there exists a critical value for the total length of stored chains; (ii) this storage capacity is linear in the network's size; (iii) the behaviour of the network around the critical point is characterized by the self-regulation of the number of synfire waves coactive in the network at any given time.
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Citations
Cites
Neural networks and physical systems with emergent collective computational abilities.
Hopfield, J. J. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.8.2554 · Cited by 19,270
Hebb, D. O. (2005) · doi:10.4324/9781410612403 · Cited by 9,825
Gray, C. M., König, P., Engel, A. K., & Singer, W. (1989) · Nature · doi:10.1038/338334a0 · Cited by 4,183
Damasio, A. R. (1989) · Cognition · doi:10.1016/0010-0277(89)90005-x · Cited by 1,538
Chaos in random neural networks
Sompolinsky, H., Crisanti, A., & Sommers, H. J. (1988) · Physical Review Letters · doi:10.1103/physrevlett.61.259 · Cited by 1,061
Cited by
Neuronal Synchrony: A Versatile Code for the Definition of Relations?
Singer, W. (1999) · Neuron · doi:10.1016/s0896-6273(00)80821-1 · Cited by 2,581
Synfire Chains and Cortical Songs: Temporal Modules of Cortical Activity
Ikegaya, Y., Aaron, G., Cossart, R., Aronov, D., Lampl, I., Ferster, D., & Yuste, R. (2004) · Science · doi:10.1126/science.1093173 · Cited by 838
Shadlen, M. N., & Movshon, J. A. (1999) · Neuron · doi:10.1016/s0896-6273(00)80822-3 · Cited by 606
Fitch, W. T. (2010) · doi:10.1017/cbo9780511817779 · Cited by 594
The Temporal Correlation Hypothesis of Visual Feature Integration
Gray, C. M. (1999) · Neuron · doi:10.1016/s0896-6273(00)80820-x · Cited by 541
Metadata
- Authors
- Bienenstock, E.
- Venue
- Network: Computation in Neural Systems
- Publisher
- Informa UK Limited
- Published
- 1995-05-01
- Volume
- 6
- Issue
- 2
- Pages
- 179-224
- ISSN
- 0954-898X (ISSN-L)
- 1361-6536
- OpenAlex
- W2152428149
- Cited by
- 205
- References
- 5
- FWCI
- 4.57
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.