Normalization as a Canonical Neural Computation.¶
Carandini, M., & Heeger, D. J. (2012). Normalization as a Canonical Neural Computation. Nature Reviews Neuroscience, 51-62.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Gain Control
- In vision and sensory neuroscience, the origin, photoreceptors adapt gain to ambient light over nine orders of magnitude and cortical neurons normalise responses to local contrast through divisive normalisation; the intervention vocabulary — gain modulation, divisive normalisation, dynamic range compression — was developed here and ported outward.
This sourceEstablishes divisive normalization — dividing a neuron's response by a pool of neighboring activity — as a canonical gain-control computation across sensory cortex and a basis for batch/layer normalization and attention.
Supported in partVerified against the work's full text
Source supports light adaptation in photoreceptors/bipolar cells and contrast normalization in cortex, plus normalization generalising from vision; the nine-orders figure and vocabulary list are not stated.
“Across visual environments (for example, an overcast night and a sunny day) light intensities range over 10 factors of 10”
- In vision and sensory neuroscience, the origin, photoreceptors adapt gain to ambient light over nine orders of magnitude and cortical neurons normalise responses to local contrast through divisive normalisation; the intervention vocabulary — gain modulation, divisive normalisation, dynamic range compression — was developed here and ported outward.
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Registry ID ref:529522d57969 · see in the full table