Chapter

Contextual Modulations of Visual Receptive Fields: A Bayesian Perspective

Sophie Denève and Timm Lochmann

in Sensory Cue Integration

Published in print September 2011 | ISBN: 9780195387247
Published online September 2012 | e-ISBN: 9780199918379 | DOI: http://dx.doi.org/10.1093/acprof:oso/9780195387247.003.0022

Series: Computational Neuroscience Series

Contextual Modulations of Visual Receptive Fields: A Bayesian Perspective

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This chapter proposes a normative neural model of visual processing under the assumption that visual spiking neurons optimally detect the presence of independent objects in dynamic visual scenes. Rather than by their receptive fields, these neurons are better described by their causal field, that is, by what they predict for the sensory input. As a result, visual layers can discover the set of objects that probably explains the input from the previous layer, solving two problems at once: integrating the sensory input optimally to detect visual objects efficiently, that is, performing optimal combination of visual cues, and resolving ambiguities between similar objects, that is, performing explaining away. This model provides a fresh view of sensory processing at the level of spiking neurons and small circuits as a form of redundancy reduction in time and space.

Keywords: normative neural model; visual processing; visual spiking neurons; causal field; sensory input integration; sensory processing

Chapter.  9621 words.  Illustrated.

Subjects: Neuropsychology

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