Abstract
The collective behavior of interconnected spiking nerve cells is investigated. It is shown that a variety of model systems exhibit the same short-time behavior and rapidly converge to (approximately) periodic firing patterns with locally synchronized action potentials. The dynamics of one model can be described by a downhill motion on an abstract energy landscape. Since an energy landscape makes it possible to understand and program computation done by an attractor network, the results will extend our understanding of collective computation from models based on a firing-rate description to biologically more realistic systems with integrate-and-fire neurons.
Dates
Type | When |
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Created | 19 years, 2 months ago (May 31, 2006, 9:16 a.m.) |
Deposited | 3 years, 4 months ago (April 13, 2022, 1:51 p.m.) |
Indexed | 1 month, 2 weeks ago (July 11, 2025, 6:26 a.m.) |
Issued | 30 years, 1 month ago (July 18, 1995) |
Published | 30 years, 1 month ago (July 18, 1995) |
Published Online | 30 years, 1 month ago (July 18, 1995) |
Published Print | 30 years, 1 month ago (July 18, 1995) |
@article{Hopfield_1995, title={Rapid local synchronization of action potentials: toward computation with coupled integrate-and-fire neurons.}, volume={92}, ISSN={1091-6490}, url={http://dx.doi.org/10.1073/pnas.92.15.6655}, DOI={10.1073/pnas.92.15.6655}, number={15}, journal={Proceedings of the National Academy of Sciences}, publisher={Proceedings of the National Academy of Sciences}, author={Hopfield, J J and Herz, A V}, year={1995}, month=jul, pages={6655–6662} }