Literature DB >> 21709677

Measuring and interpreting neuronal correlations.

Marlene R Cohen1, Adam Kohn.   

Abstract

Mounting evidence suggests that understanding how the brain encodes information and performs computations will require studying the correlations between neurons. The recent advent of recording techniques such as multielectrode arrays and two-photon imaging has made it easier to measure correlations, opening the door for detailed exploration of their properties and contributions to cortical processing. However, studies have reported discrepant findings, providing a confusing picture. Here we briefly review these studies and conduct simulations to explore the influence of several experimental and physiological factors on correlation measurements. Differences in response strength, the time window over which spikes are counted, spike sorting conventions and internal states can all markedly affect measured correlations and systematically bias estimates. Given these complicating factors, we offer guidelines for interpreting correlation data and a discussion of how best to evaluate the effect of correlations on cortical processing.

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Year:  2011        PMID: 21709677      PMCID: PMC3586814          DOI: 10.1038/nn.2842

Source DB:  PubMed          Journal:  Nat Neurosci        ISSN: 1097-6256            Impact factor:   24.884


  92 in total

1.  Clustering of perirhinal neurons with similar properties following visual experience in adult monkeys.

Authors:  C A Erickson; B Jagadeesh; R Desimone
Journal:  Nat Neurosci       Date:  2000-11       Impact factor: 24.884

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.  Analyzing functional connectivity using a network likelihood model of ensemble neural spiking activity.

Authors:  Murat Okatan; Matthew A Wilson; Emery N Brown
Journal:  Neural Comput       Date:  2005-09       Impact factor: 2.026

4.  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

5.  Central and peripheral precuing of forced-choice discrimination.

Authors:  M Cheal; D R Lyon
Journal:  Q J Exp Psychol A       Date:  1991-11

6.  The effect of correlated variability on the accuracy of a population code.

Authors:  L F Abbott; P Dayan
Journal:  Neural Comput       Date:  1999-01-01       Impact factor: 2.026

7.  Cortical auditory neuron interactions during presentation of 3-tone sequences: effective connectivity.

Authors:  I E Espinosa; G L Gerstein
Journal:  Brain Res       Date:  1988-05-31       Impact factor: 3.252

Review 8.  Correlations and brain states: from electrophysiology to functional imaging.

Authors:  Adam Kohn; Amin Zandvakili; Matthew A Smith
Journal:  Curr Opin Neurobiol       Date:  2009-07-15       Impact factor: 6.627

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.  Neural activity in the middle temporal area and lateral intraparietal area during endogenously cued shifts of attention.

Authors:  Todd M Herrington; John A Assad
Journal:  J Neurosci       Date:  2009-11-11       Impact factor: 6.167

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  430 in total

Review 1.  Conditional modeling and the jitter method of spike resampling.

Authors:  Asohan Amarasingham; Matthew T Harrison; Nicholas G Hatsopoulos; Stuart Geman
Journal:  J Neurophysiol       Date:  2011-10-26       Impact factor: 2.714

2.  Mechanisms of selective attention: response enhancement, noise reduction, and efficient pooling of sensory responses.

Authors:  John T Serences
Journal:  Neuron       Date:  2011-12-08       Impact factor: 17.173

3.  Accurately estimating neuronal correlation requires a new spike-sorting paradigm.

Authors:  Valérie Ventura; Richard C Gerkin
Journal:  Proc Natl Acad Sci U S A       Date:  2012-04-23       Impact factor: 11.205

Review 4.  From the statistics of connectivity to the statistics of spike times in neuronal networks.

Authors:  Gabriel Koch Ocker; Yu Hu; Michael A Buice; Brent Doiron; Krešimir Josić; Robert Rosenbaum; Eric Shea-Brown
Journal:  Curr Opin Neurobiol       Date:  2017-08-30       Impact factor: 6.627

5.  On the Complexity of Resting State Spiking Activity in Monkey Motor Cortex.

Authors:  Paulina Anna Dąbrowska; Nicole Voges; Michael von Papen; Junji Ito; David Dahmen; Alexa Riehle; Thomas Brochier; Sonja Grün
Journal:  Cereb Cortex Commun       Date:  2021-05-18

6.  Spatial resolution dependence on spectral frequency in human speech cortex electrocorticography.

Authors:  Leah Muller; Liberty S Hamilton; Erik Edwards; Kristofer E Bouchard; Edward F Chang
Journal:  J Neural Eng       Date:  2016-08-31       Impact factor: 5.379

Review 7.  Improving data quality in neuronal population recordings.

Authors:  Kenneth D Harris; Rodrigo Quian Quiroga; Jeremy Freeman; Spencer L Smith
Journal:  Nat Neurosci       Date:  2016-08-26       Impact factor: 24.884

8.  Reduced Repertoire of Cortical Microstates and Neuronal Ensembles in Medically Induced Loss of Consciousness.

Authors:  Michael Wenzel; Shuting Han; Elliot H Smith; Erik Hoel; Bradley Greger; Paul A House; Rafael Yuste
Journal:  Cell Syst       Date:  2019-05-01       Impact factor: 10.304

9.  Local and Global Influences of Visual Spatial Selection and Locomotion in Mouse Primary Visual Cortex.

Authors:  Ethan G McBride; Su-Yee J Lee; Edward M Callaway
Journal:  Curr Biol       Date:  2019-05-02       Impact factor: 10.834

10.  DataHigh: graphical user interface for visualizing and interacting with high-dimensional neural activity.

Authors:  Benjamin R Cowley; Matthew T Kaufman; Zachary S Butler; Mark M Churchland; Stephen I Ryu; Krishna V Shenoy; Byron M Yu
Journal:  J Neural Eng       Date:  2013-11-12       Impact factor: 5.379

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