Literature DB >> 18093826

Techniques for extracting single-trial activity patterns from large-scale neural recordings.

Mark M Churchland1, Byron M Yu, Maneesh Sahani, Krishna V Shenoy.   

Abstract

Large, chronically implanted arrays of microelectrodes are an increasingly common tool for recording from primate cortex and can provide extracellular recordings from many (order of 100) neurons. While the desire for cortically based motor prostheses has helped drive their development, such arrays also offer great potential to advance basic neuroscience research. Here we discuss the utility of array recording for the study of neural dynamics. Neural activity often has dynamics beyond that driven directly by the stimulus. While governed by those dynamics, neural responses may nevertheless unfold differently for nominally identical trials, rendering many traditional analysis methods ineffective. We review recent studies - some employing simultaneous recording, some not - indicating that such variability is indeed present both during movement generation and during the preceding premotor computations. In such cases, large-scale simultaneous recordings have the potential to provide an unprecedented view of neural dynamics at the level of single trials. However, this enterprise will depend not only on techniques for simultaneous recording but also on the use and further development of analysis techniques that can appropriately reduce the dimensionality of the data, and allow visualization of single-trial neural behavior.

Mesh:

Year:  2007        PMID: 18093826      PMCID: PMC2238690          DOI: 10.1016/j.conb.2007.11.001

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN: 0959-4388            Impact factor:   6.627


  71 in total

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8.  Neural variability in premotor cortex provides a signature of motor preparation.

Authors:  Mark M Churchland; Byron M Yu; Stephen I Ryu; Gopal Santhanam; Krishna V Shenoy
Journal:  J Neurosci       Date:  2006-04-05       Impact factor: 6.167

9.  Mixture of trajectory models for neural decoding of goal-directed movements.

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  70 in total

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2.  Roles of monkey premotor neuron classes in movement preparation and execution.

Authors:  Matthew T Kaufman; Mark M Churchland; Gopal Santhanam; Byron M Yu; Afsheen Afshar; Stephen I Ryu; Krishna V Shenoy
Journal:  J Neurophysiol       Date:  2010-06-10       Impact factor: 2.714

3.  Single-trial neural correlates of arm movement preparation.

Authors:  Afsheen Afshar; Gopal Santhanam; Byron M Yu; Stephen I Ryu; Maneesh Sahani; Krishna V Shenoy
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4.  Prefrontal spatial working memory network predicts animal's decision making in a free choice saccade task.

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5.  Reversible large-scale modification of cortical networks during neuroprosthetic control.

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Journal:  Nat Neurosci       Date:  2011-04-17       Impact factor: 24.884

6.  Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity.

Authors:  Byron M Yu; John P Cunningham; Gopal Santhanam; Stephen I Ryu; Krishna V Shenoy; Maneesh Sahani
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Review 7.  Behavioral states, network states, and sensory response variability.

Authors:  Alfredo Fontanini; Donald B Katz
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8.  Cortical preparatory activity: representation of movement or first cog in a dynamical machine?

Authors:  Mark M Churchland; John P Cunningham; Matthew T Kaufman; Stephen I Ryu; Krishna V Shenoy
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9.  DataHigh: graphical user interface for visualizing and interacting with high-dimensional neural activity.

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Review 10.  Decoding Cognitive Processes from Neural Ensembles.

Authors:  Joni D Wallis
Journal:  Trends Cogn Sci       Date:  2018-09-29       Impact factor: 20.229

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