# Show Reference: "Normalization as a canonical neural computation"

Normalization as a canonical neural computation Nature Reviews Neuroscience, Vol. 13, No. 1. (23 November 2011), pp. 51-62, doi:10.1038/nrn3136 by Matteo Carandini, David J. Heeger
@article{carandini-and-heeger-2012,
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.},
author = {Carandini, Matteo and Heeger, David J.},
citeulike-article-id = {10100149},
day = {23},
doi = {10.1038/nrn3136},
issn = {1471-003X},
journal = {Nature Reviews Neuroscience},
keywords = {biology, divisive-normalization, neural-computation},
month = nov,
number = {1},
pages = {51--62},
pmcid = {PMC3273486},
pmid = {22108672},
posted-at = {2014-06-12 10:49:50},
priority = {2},
publisher = {Nature Publishing Group},
title = {Normalization as a canonical neural computation},
url = {http://dx.doi.org/10.1038/nrn3136},
volume = {13},
year = {2011}
}



Carandini et al. argue for compositionality of mechanisms and mechanism sketches.

According to Carandini and Heeger, structures on the level of microcircuits which are repeated throughout the brain implement what the authors call `canonical neural computations'. Well-known examples of such canonical neural computations are:

• exponentiation
• linear filtering.

Another canonical neural computation proposed by Carandini and Heeger is (divisive) normalization.

Divisive normalization models describe neural responses well in cases of

• olfactory perception in drosophila,
• visual processing in retina and V1,
• possibly in other cortical areas,
• modulation of responses through attention in visual cortex.

Divisive normalization is probably implemented through (GABA-ergic) inhibition in some cases (fruitfly olfactory system). In others (V1), it seems to be implemented by different means.