Sensory noise predicts divisive reshaping of receptive fields

Chalk, Matthew and Masset, Paul and Gutkin, Boris S and Denève, Sophie (2017) Sensory noise predicts divisive reshaping of receptive fields. PLoS Computational Biology, 13 (6). Article number: e1005582 . ISSN 1553-7358

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In order to respond reliably to specific features of their environment, sensory neurons need to integrate multiple incoming noisy signals. Crucially, they also need to compete for the interpretation of those signals with other neurons representing similar features. The form that this competition should take depends critically on the noise corrupting these signals. In this study we show that for the type of noise commonly observed in sensory systems, whose variance scales with the mean signal, sensory neurons should selectively divide their input signals by their predictions, suppressing ambiguous cues while amplifying others. Any change in the stimulus context alters which inputs are suppressed, leading to a deep dynamic reshaping of neural receptive fields going far beyond simple surround suppression. Paradoxically, these highly variable receptive fields go alongside and are in fact required for an invariant representation of external sensory features. In addition to offering a normative account of context-dependent changes in sensory responses, perceptual inference in the presence of signal-dependent noise accounts for ubiquitous features of sensory neurons such as divisive normalization, gain control and contrast dependent temporal dynamics.

Item Type: Article
DOI: 10.1371/journal.pcbi.1005582
Subjects: 500 Science > 570 Life sciences; biology > 571 Physiology
Research Group: Tkacik Group
SWORD Depositor: Sword Import User
Depositing User: Sword Import User
Date Deposited: 14 Dec 2017 07:58
Last Modified: 14 Dec 2017 07:58

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