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Poster Communications Year : 2014

Microsaccades enable efficient synchrony-based visual feature learning and detection

Abstract

Fixational eye movements are common across vertebrates, yet their functional roles, if any, are debated. To investigate this issue, we exposed the Virtual Retina simulator to natural images, generated realistic drifts and microsaccades using the model of ref, and analyzed the output spike trains of the parvocellular retinal ganglion cells (RGC).
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Dates and versions

hal-01026508 , version 1 (21-07-2014)

Identifiers

  • HAL Id : hal-01026508 , version 1

Cite

Timothée Masquelier, Geoffrey Portelli, Pierre Kornprobst. Microsaccades enable efficient synchrony-based visual feature learning and detection. Twenty Third Annual Computational Neuroscience Meeting: CNS*2014, Jul 2014, Québec, Canada. 15 (Suppl 1), pp.P121, 2014, BMC Neuroscience. ⟨hal-01026508⟩
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