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Polychronization: Computation with Spikes

Izhikevich, Eugene M.·2006·Neural Computation

Abstract

We present a minimal spiking network that can polychronize, that is, exhibit reproducible time-locked but not synchronous firing patterns with millisecond precision, as in synfire braids. The network consists of cortical spiking neurons with axonal conduction delays and spike-timing-dependent plasticity (STDP); a ready-to-use MATLAB code is included. It exhibits sleeplike oscillations, gamma (40 Hz) rhythms, conversion of firing rates to spike timings, and other interesting regimes. Due to the interplay between the delays and STDP, the spiking neurons spontaneously self-organize into groups and generate patterns of stereotypical polychronous activity. To our surprise, the number of coexisting polychronous groups far exceeds the number of neurons in the network, resulting in an unprecedented memory capacity of the system. We speculate on the significance of polychrony to the theory of neuronal group selection (TNGS, neural Darwinism), cognitive neural computations, binding and gamma rhythm, mechanisms of attention, and consciousness as “attention to memories.”

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Metadata

Authors
Izhikevich, E. M.
Venue
Neural Computation
Published
2006-02-01
Volume
18
Issue
2
Pages
245-282
ISSN
  • 0899-7667 (ISSN-L)
  • 1530-888X
OpenAlex
W2128432504
Cited by
1,062
References
10
FWCI
12.92
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Polychronization: Computation with Spikes. https://app.cochat.ai/papers/10.1162/089976606775093882
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Izhikevich, E. M. (2006). Polychronization: Computation with Spikes. Neural Computation. https://doi.org/10.1162/089976606775093882

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