Normalization as a canonical neural computation

Matteo Carandini, David J. Heeger

Research output: Contribution to journalArticle

Abstract

There is increasing evidence that the brain relies on a set of canonical neural computations, repeating them across brain regions and modalities to apply similar operations to different problems. A promising candidate for such a computation is normalization, in which the responses of neurons are divided by a common factor that typically includes the summed activity of a pool of neurons. Normalization was developed to explain responses in the primary visual cortex and is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions. Normalization may underlie operations such as the representation of odours, the modulatory effects of visual attention, the encoding of value and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that it serves as a canonical neural computation.

Original languageEnglish (US)
Pages (from-to)51-62
Number of pages12
JournalNature Reviews Neuroscience
Volume13
Issue number1
DOIs
StatePublished - Jan 2012

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Brain
Neurons
Visual Cortex
Invertebrates
Mammals
Odorants

ASJC Scopus subject areas

  • Neuroscience(all)

Cite this

Normalization as a canonical neural computation. / Carandini, Matteo; Heeger, David J.

In: Nature Reviews Neuroscience, Vol. 13, No. 1, 01.2012, p. 51-62.

Research output: Contribution to journalArticle

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