Literature DB >> 11353028

Contrast-dependent nonlinearities arise locally in a model of contrast-invariant orientation tuning.

A Kayser1, N J Priebe, K D Miller.   

Abstract

We study a recently proposed "correlation-based," push-pull model of the circuitry of layer 4 of cat visual cortex. This model was previously shown to explain the contrast-invariance of cortical orientation tuning. Here we show that it can simultaneously account for several contrast-dependent (c-d) "nonlinearities" in cortical responses. These include an advance with increasing contrast in the temporal phase of response to a sinusoidally modulated stimulus; a change in shape of the temporal frequency tuning curve, so that higher temporal frequencies may give little or no response at low contrast but reasonable responses at high contrast; and contrast saturation that occurs at lower contrasts in cortex than in the lateral geniculate nucleus (LGN). In the context of the model circuit, these properties arise from a mixture of nonlinear cellular and synaptic mechanisms: short-term synaptic depression, spike-rate adaptation, contrast-induced changes in cellular conductance, and the nonzero spike threshold. The former three mechanisms are sufficient to explain the experimentally observed increase in c-d phase advance in cortex relative to LGN. The c-d changes in temporal frequency tuning arise as a threshold effect: voltage modulations in response to higher-frequency inputs are only slightly above threshold at lower contrast, but become robustly suprathreshold at higher contrast. The other three nonlinear mechanisms also play a crucial role in this result, allowing contrast dependence of temporal frequency tuning to coexist with contrast-invariance of orientation tuning. Contrast saturation, and the observation that responses to stimuli of increasing temporal frequency saturate at increasingly high contrasts, can be induced both by the model's push-pull inhibition and by synaptic depression. Previous proposals explained these nonlinear response properties by assuming contrast-invariant orientation tuning as a starting point, and adding normalization by shunting inhibition derived equally from cells of all preferred orientations. The present proposal simultaneously explains both contrast-invariant orientation tuning and these contrast-dependent nonlinearities and requires only processing that is local in orientation, in agreement with intracellular measurements.

Entities:  

Mesh:

Year:  2001        PMID: 11353028     DOI: 10.1152/jn.2001.85.5.2130

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  19 in total

Review 1.  Canonical computations of cerebral cortex.

Authors:  Kenneth D Miller
Journal:  Curr Opin Neurobiol       Date:  2016-02-08       Impact factor: 6.627

2.  A nonlinear model of the behavior of simple cells in visual cortex.

Authors:  Miguel A García-Pérez
Journal:  J Comput Neurosci       Date:  2004 Nov-Dec       Impact factor: 1.621

3.  The emergence of contrast-invariant orientation tuning in simple cells of cat visual cortex.

Authors:  Ian M Finn; Nicholas J Priebe; David Ferster
Journal:  Neuron       Date:  2007-04-05       Impact factor: 17.173

4.  A neurally efficient implementation of sensory population decoding.

Authors:  Kris S Chaisanguanthum; Stephen G Lisberger
Journal:  J Neurosci       Date:  2011-03-30       Impact factor: 6.167

5.  Modeling lateral geniculate nucleus response with contrast gain control. Part 2: analysis.

Authors:  Davis Cope; Barbara Blakeslee; Mark E McCourt
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2014-02-01       Impact factor: 2.129

6.  A novel mutual information estimator to measure spike train correlations in a model thalamocortical network.

Authors:  Ekaterina D Gribkova; Baher A Ibrahim; Daniel A Llano
Journal:  J Neurophysiol       Date:  2018-09-05       Impact factor: 2.714

7.  The role of delayed suppression in slow and fast contrast adaptation in V1 simple cells.

Authors:  Manuel Levy; Julien Fournier; Yves Frégnac
Journal:  J Neurosci       Date:  2013-04-10       Impact factor: 6.167

8.  Feedforward origins of response variability underlying contrast invariant orientation tuning in cat visual cortex.

Authors:  Srivatsun Sadagopan; David Ferster
Journal:  Neuron       Date:  2012-06-07       Impact factor: 17.173

9.  Modeling lateral geniculate nucleus response with contrast gain control. Part 1: formulation.

Authors:  Davis Cope; Barbara Blakeslee; Mark E McCourt
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2013-11-01       Impact factor: 2.129

10.  Adaptive gain modulation in V1 explains contextual modifications during bisection learning.

Authors:  Roland Schäfer; Eleni Vasilaki; Walter Senn
Journal:  PLoS Comput Biol       Date:  2009-12-18       Impact factor: 4.475

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.