Literature DB >> 29975592

Linking V1 Activity to Behavior.

Eyal Seidemann1,2,3, Wilson S Geisler1,2.   

Abstract

A long-term goal of visual neuroscience is to develop and test quantitative models that account for the moment-by-moment relationship between neural responses in early visual cortex and human performance in natural visual tasks. This review focuses on efforts to address this goal by measuring and perturbing the activity of primary visual cortex (V1) neurons while nonhuman primates perform demanding, well-controlled visual tasks. We start by describing a conceptual approach-the decoder linking model (DLM) framework-in which candidate decoding models take neural responses as input and generate predicted behavior as output. The ultimate goal in this framework is to find the actual decoder-the model that best predicts behavior from neural responses. We discuss key relevant properties of primate V1 and review current literature from the DLM perspective. We conclude by discussing major technological and theoretical advances that are likely to accelerate our understanding of the link between V1 activity and behavior.

Entities:  

Keywords:  computational neuroscience; identification tasks; neural decoding; perceptual decisions; population coding; visual cortex

Mesh:

Year:  2018        PMID: 29975592      PMCID: PMC6141357          DOI: 10.1146/annurev-vision-102016-061324

Source DB:  PubMed          Journal:  Annu Rev Vis Sci        ISSN: 2374-4642            Impact factor:   6.422


  94 in total

Review 1.  VSDI: a new era in functional imaging of cortical dynamics.

Authors:  Amiram Grinvald; Rina Hildesheim
Journal:  Nat Rev Neurosci       Date:  2004-11       Impact factor: 34.870

2.  Stimulus dependence of neuronal correlation in primary visual cortex of the macaque.

Authors:  Adam Kohn; Matthew A Smith
Journal:  J Neurosci       Date:  2005-04-06       Impact factor: 6.167

3.  Spatial attention decorrelates intrinsic activity fluctuations in macaque area V4.

Authors:  Jude F Mitchell; Kristy A Sundberg; John H Reynolds
Journal:  Neuron       Date:  2009-09-24       Impact factor: 17.173

Review 4.  Measuring and interpreting neuronal correlations.

Authors:  Marlene R Cohen; Adam Kohn
Journal:  Nat Neurosci       Date:  2011-06-27       Impact factor: 24.884

Review 5.  Feedforward and feedback sources of choice probability in neural population responses.

Authors:  Bruce G Cumming; Hendrikje Nienborg
Journal:  Curr Opin Neurobiol       Date:  2016-02-27       Impact factor: 6.627

6.  Sensitivity loss in odd-symmetric mechanisms and phase anomalies in peripheral vision.

Authors:  P J Bennett; M S Banks
Journal:  Nature       Date:  1987 Apr 30-May 6       Impact factor: 49.962

7.  Neuronal Mechanisms of Visual Attention.

Authors:  John H R Maunsell
Journal:  Annu Rev Vis Sci       Date:  2015-11-24       Impact factor: 6.422

8.  A precise retinotopic map of primate striate cortex generated from the representation of angioscotomas.

Authors:  Daniel L Adams; Jonathan C Horton
Journal:  J Neurosci       Date:  2003-05-01       Impact factor: 6.167

9.  Estimates of the contribution of single neurons to perception depend on timescale and noise correlation.

Authors:  Marlene R Cohen; William T Newsome
Journal:  J Neurosci       Date:  2009-05-20       Impact factor: 6.167

10.  Orthogonal micro-organization of orientation and spatial frequency in primate primary visual cortex.

Authors:  Ian Nauhaus; Kristina J Nielsen; Anita A Disney; Edward M Callaway
Journal:  Nat Neurosci       Date:  2012-11-11       Impact factor: 24.884

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  4 in total

1.  Predicting Perceptual Decisions Using Visual Cortical Population Responses and Choice History.

Authors:  Anna Ivic Jasper; Seiji Tanabe; Adam Kohn
Journal:  J Neurosci       Date:  2019-06-24       Impact factor: 6.167

2.  Perceptual enhancement and suppression correlate with V1 neural activity during active sensing.

Authors:  James E Niemeyer; Seth Akers-Campbell; Aaron Gregoire; Michael A Paradiso
Journal:  Curr Biol       Date:  2022-05-17       Impact factor: 10.900

3.  Decision Signals in the Local Field Potentials of Early and Mid-Level Macaque Visual Cortex.

Authors:  Aravind Krishna; Seiji Tanabe; Adam Kohn
Journal:  Cereb Cortex       Date:  2021-01-01       Impact factor: 5.357

4.  Effects of top-down influence suppression on behavioral and V1 neuronal contrast sensitivity functions in cats.

Authors:  Jian Ding; Zheng Ye; Fei Xu; Xiangmei Hu; Hao Yu; Shen Zhang; Yanni Tu; Qiuyu Zhang; Qingyan Sun; Tianmiao Hua; Zhong-Lin Lu
Journal:  iScience       Date:  2021-12-24
  4 in total

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