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Sensory Cue Integration$
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Julia Trommershäuser, Konrad Kording, and Michael S. Landy

Print publication date: 2011

Print ISBN-13: 9780195387247

Published to Oxford Scholarship Online: September 2012

DOI: 10.1093/acprof:oso/9780195387247.001.0001

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Contextual Modulations of Visual Receptive Fields: A Bayesian Perspective

Contextual Modulations of Visual Receptive Fields: A Bayesian Perspective

Chapter:
(p.406) CHAPTER 22 Contextual Modulations of Visual Receptive Fields: A Bayesian Perspective
Source:
Sensory Cue Integration
Author(s):

Sophie Denève

Timm Lochmann

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195387247.003.0022

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

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