Literature DB >> 26157005

Local Circuits for Contrast Normalization and Adaptation Investigated with Two-Photon Imaging in Cat Primary Visual Cortex.

Andreas J Keller1, Kevan A C Martin2.   

Abstract

Sensory neurons encode stimulus intensity in their instantaneous spike rate and adjust the set-points of the stimulus-response relationships by adaptation. In the visual cortex, adaptation is crucial because the mechanism of fast gain control (normalization) increases the contrast sensitivity of individual neurons at the cost of encoding a far narrower range of contrasts than is encountered in natural scenes. The mechanism of adaptation, however, is a slow process and has a time constant of seconds. Here we use two-photon calcium imaging of identified excitatory and inhibitory neurons in superficial layers of cat primary visual cortex to answer two questions: for a given set-point, what is range of contrasts represented within a local pool of neurons, and what accounts for the slow time constant of contrast adaptation? We found that a local patch of excitatory neurons has a large diversity of contrast tunings, which effectively extends the range of contrast that can be encoded instantaneously in cortex. Additionally, we identified a pool of parvalbumin-positive GABAergic neurons and neurons in the upper tier of imaging sites that showed a paradoxical slow increase in activity during adaptation, thus implicating them in the slow set-point adaptation of the excitatory population. Our results provide new insights into the circuits and mechanisms underlying cortical adaptation and gain control. SIGNIFICANCE STATEMENT: Neurons in the primary visual cortex (V1) respond near instantaneously over a limited range of contrasts but can also shift their operating range according to the average contrast of the scene. This "contrast adaptation" takes 5-10 s and ensures that a full range of contrasts can be encoded in V1, while remaining sensitive to small changes in local contrast. By optically recording many layer 2 neurons simultaneously, we discovered that networks of neurons collectively code for a much wider range of contrasts. Whereas most neurons responded to sustained increases in contrast by decreasing their spike firing rates, two types of inhibitory neurons in the cat's visual cortex paradoxically increased their firing rates and so could inhibit other neurons to produce contrast adaptation.
Copyright © 2015 the authors 0270-6474/15/3510078-10$15.00/0.

Entities:  

Keywords:  cat visual cortex; computation of contrast; contrast adaptation; immunostaining of functionally imaged cells; normalization; two-photon calcium imaging in the cat

Mesh:

Substances:

Year:  2015        PMID: 26157005      PMCID: PMC6605411          DOI: 10.1523/JNEUROSCI.0906-15.2015

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  31 in total

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2.  Membrane mechanisms underlying contrast adaptation in cat area 17 in vivo.

Authors:  M V Sanchez-Vives; L G Nowak; D A McCormick
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3.  Coding of the contrasts in natural images by populations of neurons in primary visual cortex (V1).

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Review 5.  Neuronal circuits of the neocortex.

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7.  Temporal dynamics of contrast gain in single cells of the cat striate cortex.

Authors:  A B Bonds
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8.  Relationship between contrast adaptation and orientation tuning in V1 and V2 of cat visual cortex.

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Review 10.  Normalization as a canonical neural computation.

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2.  Noisy Spiking in Visual Area V2 of Amblyopic Monkeys.

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Review 3.  Predictive Processing: A Canonical Cortical Computation.

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Review 4.  Cortical synaptic architecture supports flexible sensory computations.

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5.  Distinct learning-induced changes in stimulus selectivity and interactions of GABAergic interneuron classes in visual cortex.

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Journal:  Nat Neurosci       Date:  2018-05-21       Impact factor: 24.884

6.  Heterogeneous side effects of cortical inactivation in behaving animals.

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7.  Stimulus relevance modulates contrast adaptation in visual cortex.

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9.  Synaptic connections formed by patchy projections of pyramidal cells in the superficial layers of cat visual cortex.

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10.  Adaptation towards scale-free dynamics improves cortical stimulus discrimination at the cost of reduced detection.

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