Literature DB >> 24904074

Local and Global Correlations between Neurons in the Middle Temporal Area of Primate Visual Cortex.

Selina S Solomon1, Spencer C Chen1, John W Morley2, Samuel G Solomon3.   

Abstract

In humans and other primates, the analysis of visual motion includes populations of neurons in the middle-temporal (MT) area of visual cortex. Motion analysis will be constrained by the structure of neural correlations in these populations. Here, we use multi-electrode arrays to measure correlations in anesthetized marmoset, a New World monkey where area MT lies exposed on the cortical surface. We measured correlations in the spike count between pairs of neurons and within populations of neurons, for moving dot fields and moving gratings. Correlations were weaker in area MT than in area V1. The magnitude of correlations in area MT diminished with distance between receptive fields, and difference in preferred direction. Correlations during presentation of moving gratings were stronger than those during presentation of moving dot fields, extended further across cortex, and were less dependent on the functional properties of neurons. Analysis of the timescales of correlation suggests presence of 2 mechanisms. A local mechanism, associated with near-synchronous spiking activity, is strongest in nearby neurons with similar direction preference and is independent of visual stimulus. A global mechanism, operating over larger spatial scales and longer timescales, is independent of direction preference and is modulated by the type of visual stimulus presented.
© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  area MT; extrastriate; marmoset; population coding; visual motion

Mesh:

Year:  2014        PMID: 24904074     DOI: 10.1093/cercor/bhu111

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


  19 in total

1.  Spatial precision of population activity in primate area MT.

Authors:  Spencer C Chen; John W Morley; Samuel G Solomon
Journal:  J Neurophysiol       Date:  2015-06-03       Impact factor: 2.714

2.  Emergence of complex wave patterns in primate cerebral cortex.

Authors:  Rory G Townsend; Selina S Solomon; Spencer C Chen; Alexander N J Pietersen; Paul R Martin; Samuel G Solomon; Pulin Gong
Journal:  J Neurosci       Date:  2015-03-18       Impact factor: 6.167

3.  Dynamic population codes of multiplexed stimulus features in primate area MT.

Authors:  Erin Goddard; Samuel G Solomon; Thomas A Carlson
Journal:  J Neurophysiol       Date:  2017-04-05       Impact factor: 2.714

4.  Sensitivity of neurons in the middle temporal area of marmoset monkeys to random dot motion.

Authors:  Tristan A Chaplin; Benjamin J Allitt; Maureen A Hagan; Nicholas S C Price; Ramesh Rajan; Marcello G P Rosa; Leo L Lui
Journal:  J Neurophysiol       Date:  2017-06-21       Impact factor: 2.714

Review 5.  Correlations and Neuronal Population Information.

Authors:  Adam Kohn; Ruben Coen-Cagli; Ingmar Kanitscheider; Alexandre Pouget
Journal:  Annu Rev Neurosci       Date:  2016-04-21       Impact factor: 12.449

Review 6.  The marmoset monkey as a model for visual neuroscience.

Authors:  Jude F Mitchell; David A Leopold
Journal:  Neurosci Res       Date:  2015-02-13       Impact factor: 3.304

7.  The asynchronous state's relation to large-scale potentials in cortex.

Authors:  A Alishbayli; J G Tichelaar; U Gorska; M X Cohen; B Englitz
Journal:  J Neurophysiol       Date:  2019-10-23       Impact factor: 2.714

8.  Motion Perception in the Common Marmoset.

Authors:  Shaun L Cloherty; Jacob L Yates; Dina Graf; Gregory C DeAngelis; Jude F Mitchell
Journal:  Cereb Cortex       Date:  2020-04-14       Impact factor: 5.357

9.  Rapid Adaptation Induces Persistent Biases in Population Codes for Visual Motion.

Authors:  Elizabeth Zavitz; Hsin-Hao Yu; Elise G Rowe; Marcello G P Rosa; Nicholas S C Price
Journal:  J Neurosci       Date:  2016-04-20       Impact factor: 6.167

10.  Neuronal variability reflects probabilistic inference tuned to natural image statistics.

Authors:  Dylan Festa; Amir Aschner; Aida Davila; Adam Kohn; Ruben Coen-Cagli
Journal:  Nat Commun       Date:  2021-06-15       Impact factor: 14.919

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