Literature DB >> 16554511

Measurement of time-dependent changes in the irregularity of neural spiking.

Ronnie M Davies1, George L Gerstein, Stuart N Baker.   

Abstract

Irregularity of firing in spike trains has been associated with coding processes and information transfer or alternatively treated as noise. Previous studies of irregularity have mainly used the coefficient of variation (CV) of the interspike interval distribution. Proper estimation of CV requires a constant underlying firing rate, a condition that most experimental situations do not fulfill either within or across trials. Here we introduce a novel irregularity metric based on the ratio of adjacent intervals in the spike train. The new metric is not affected by firing rate and is very localized in time so that it can be used to examine the time course of irregularity relative to an alignment marker. We characterized properties of the new metric with simulated spike trains of known characteristics and then applied it to data recorded from 108 single neurons in the motor cortex of two monkeys during performance of a precision grip task. Fifty-six cells were antidromically identified as pyramidal tract neurons (PTNs). Sixty-one cells (30 PTNs) exhibited significant temporal modulation of their irregularity during task performance with the contralateral hand. The irregularity modulations generally differed in sign and latency from the modulations of firing rate. High irregularity tended to occur during the task phases requiring the most detailed control of movement, whereas neural firing became more regular during the steady hold phase. Such irregularity modulation could have important consequences for the response of downstream neurons and may provide insight into the nature of the cortical code.

Mesh:

Year:  2006        PMID: 16554511     DOI: 10.1152/jn.01030.2005

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


  35 in total

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Review 3.  Techniques for extracting single-trial activity patterns from large-scale neural recordings.

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4.  Network oscillations and intrinsic spiking rhythmicity do not covary in monkey sensorimotor areas.

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Journal:  J Physiol       Date:  2007-02-08       Impact factor: 5.182

5.  Comparison of local measures of spike time irregularity and relating variability to firing rate in motor cortical neurons.

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Journal:  J Comput Neurosci       Date:  2009-05-16       Impact factor: 1.621

6.  Reward-dependent modulation of neuronal activity in the primate dorsal raphe nucleus.

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Journal:  J Neurosci       Date:  2008-05-14       Impact factor: 6.167

7.  A characterization of the time-rescaled gamma process as a model for spike trains.

Authors:  Takeaki Shimokawa; Shinsuke Koyama; Shigeru Shinomoto
Journal:  J Comput Neurosci       Date:  2009-10-21       Impact factor: 1.621

8.  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

9.  Two types of dopamine neuron distinctly convey positive and negative motivational signals.

Authors:  Masayuki Matsumoto; Okihide Hikosaka
Journal:  Nature       Date:  2009-05-17       Impact factor: 49.962

10.  Ideal observer analysis of signal quality in retinal circuits.

Authors:  Robert G Smith; Narender K Dhingra
Journal:  Prog Retin Eye Res       Date:  2009-05-13       Impact factor: 21.198

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