Cortical Spike Synchrony as a Measure of Input Familiarity

Autor(en): Korndoerfer, Clemens
Ullner, Ekkehard
Garcia-Ojalvo, Jordi
Pipa, Gordon 
Stichwörter: COHERENCE RESONANCE; Computer Science; Computer Science, Artificial Intelligence; CONTOUR INTEGRATION; FUNCTIONAL-ORGANIZATION; HORIZONTAL CONNECTIONS; INTRINSIC CONNECTIONS; MODEL; NEURONS; Neurosciences; Neurosciences & Neurology; NOISE; PRIMARY VISUAL-CORTEX; PROJECTIONS
Erscheinungsdatum: 2017
Herausgeber: MIT PRESS
Journal: NEURAL COMPUTATION
Volumen: 29
Ausgabe: 9
Startseite: 2491
Seitenende: 2510
Zusammenfassung: 
Spike synchrony, which occurs in various cortical areas in response to specific perception, action, and memory tasks, has sparked a long-standing debate on the nature of temporal organization in cortex. One prominent view is that this type of synchrony facilitates the binding or grouping of separate stimulus components. We argue instead for a more general function: a measure of the prior probability of incoming stimuli, implemented by long-range, horizontal, intracortical connections. We show that networks of this kindpulse-coupled excitatory spiking networks in a noisy environmentcan provide a sufficient substrate for stimulus-dependent spike synchrony. This allows for a quick (few spikes) estimate of the match between inputs and the input history as encoded in the network structure. Given the ubiquity of small, strongly excitatory subnetworks in cortex, we thus propose that many experimental observations of spike synchrony can be viewed as signs of input patterns that resemble long-term experiencethat is, of patterns with high prior probability.
ISSN: 08997667
DOI: 10.1162/neco_a_00987

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