Literature DB >> 20861439

Visual stimulation decorrelates neuronal activity.

Mike W Oram1.   

Abstract

The accuracy of neuronal encoding depends on the response statistics of individual neurons and the correlation of the activity between different neurons. Here, the dynamics of the neuronal response statistics in the anterior superior temporal sulcus of the macaque monkey is described. A transient reduction in the normalized trial-by-trial variability and decorrelation of the responses with both the activity of other neurons and previous activity of the same neuron are found at response onset. The variability of neuronal activity and its correlation structure return to the levels observed in the resting state 50-100 ms after response onset, except for marked increases in the signal correlation between neurons. The transient changes in the response statistics are seen even if there is little or no stimulus-elicited activity, indicating the effect is due to network properties rather than to activity changes per se. Modeling also indicates that the observed variations in response variability and correlation structure of the neuronal activity over time cannot be attributed to changes in firing rate. However, a reset of the underlying spike-generating process, possibly due to the driving input changing from recurrent to feedforward inputs, captures most of the observed changes. The nonstationarity indicated by the changes in correlation structure around response onset increases coding efficiency: compared with the mutual information calculated without regard to the transitory changes, the decorrelation increases the information conveyed by the initial response of modeled neuronal pairs by ≤ 4% and suggests that an integration time of as little as 50 ms is sufficient to extract 95% the available information during the initial response period.

Mesh:

Year:  2010        PMID: 20861439     DOI: 10.1152/jn.00711.2009

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


  19 in total

1.  Stimulus-dependent variability and noise correlations in cortical MT neurons.

Authors:  Adrián Ponce-Alvarez; Alexander Thiele; Thomas D Albright; Gene R Stoner; Gustavo Deco
Journal:  Proc Natl Acad Sci U S A       Date:  2013-07-22       Impact factor: 11.205

2.  Spatial representation and cognitive modulation of response variability in the lateral intraparietal area priority map.

Authors:  Annegret L Falkner; Michael E Goldberg; B Suresh Krishna
Journal:  J Neurosci       Date:  2013-10-09       Impact factor: 6.167

3.  Stochastic transitions into silence cause noise correlations in cortical circuits.

Authors:  Gabriela Mochol; Ainhoa Hermoso-Mendizabal; Shuzo Sakata; Kenneth D Harris; Jaime de la Rocha
Journal:  Proc Natl Acad Sci U S A       Date:  2015-03-04       Impact factor: 11.205

4.  Visual stimulation quenches global alpha range activity in awake primate V4: a case study.

Authors:  Thomas Deneux; Timothée Masquelier; Maria A Bermudez; Guillaume S Masson; Gustavo Deco; Ivo Vanzetta
Journal:  Neurophotonics       Date:  2017-06-28       Impact factor: 3.593

5.  The Magnitude, But Not the Sign, of MT Single-Trial Spike-Time Correlations Predicts Motion Detection Performance.

Authors:  Alireza Hashemi; Ashkan Golzar; Jackson E T Smith; Erik P Cook
Journal:  J Neurosci       Date:  2018-04-06       Impact factor: 6.167

6.  Dissociation of response variability from firing rate effects in frontal eye field neurons during visual stimulation, working memory, and attention.

Authors:  Mindy H Chang; Katherine M Armstrong; Tirin Moore
Journal:  J Neurosci       Date:  2012-02-08       Impact factor: 6.167

7.  Task-evoked functional connectivity does not explain functional connectivity differences between rest and task conditions.

Authors:  Lauren K Lynch; Kun-Han Lu; Haiguang Wen; Yizhen Zhang; Andrew J Saykin; Zhongming Liu
Journal:  Hum Brain Mapp       Date:  2018-08-24       Impact factor: 5.038

Review 8.  Neural changes after training to perform cognitive tasks.

Authors:  Xue-Lian Qi; Christos Constantinidis
Journal:  Behav Brain Res       Date:  2012-12-20       Impact factor: 3.332

9.  Cellular and circuit mechanisms maintain low spike co-variability and enhance population coding in somatosensory cortex.

Authors:  Cheng Ly; Jason W Middleton; Brent Doiron
Journal:  Front Comput Neurosci       Date:  2012-03-08       Impact factor: 2.380

10.  Variability of prefrontal neuronal discharges before and after training in a working memory task.

Authors:  Xue-Lian Qi; Christos Constantinidis
Journal:  PLoS One       Date:  2012-07-25       Impact factor: 3.240

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