Literature DB >> 26906455

Superlinear Summation of Information in Premotor Neuron Pairs.

Fernando Montani1, Andriy Oliynyk2, Luciano Fadiga3,4.   

Abstract

Whether premotor/motor neurons encode information in terms of spiking frequency or by their relative time of firing, which may display synchronization, is still undetermined. To address this issue, we used an information theory approach to analyze neuronal responses recorded in the premotor (area F5) and primary motor (area F1) cortices of macaque monkeys under four different conditions of visual feedback during hand grasping. To evaluate the sensitivity of spike timing correlation between single neurons, we investigated the stimulus dependent synchronization in our population of pairs. We first investigated the degree of correlation of trial-to-trial fluctuations in response strength between neighboring neurons for each condition, and second estimated the stimulus dependent synchronization by means of an information theoretical approach. We compared the information conveyed by pairs of simultaneously recorded neurons with the sum of information provided by the respective individual cells. The information transmission across pairs of cells in the primary motor cortex seems largely independent, whereas information transmission across pairs of premotor neurons is summed superlinearly. The brain could take advantage of both the accuracy provided by the independency of F1 and the synergy allowed by the superlinear information population coding in F5, distinguishing thus the generalizing role of F5.

Keywords:  Cortex; Neural code; information theory; motor control; neural networks; spike synchronization

Mesh:

Year:  2015        PMID: 26906455     DOI: 10.1142/S012906571650009X

Source DB:  PubMed          Journal:  Int J Neural Syst        ISSN: 0129-0657            Impact factor:   5.866


  2 in total

1.  Higher-Order Cumulants Drive Neuronal Activity Patterns, Inducing UP-DOWN States in Neural Populations.

Authors:  Roman Baravalle; Fernando Montani
Journal:  Entropy (Basel)       Date:  2020-04-22       Impact factor: 2.524

2.  Causal Shannon-Fisher Characterization of Motor/Imagery Movements in EEG.

Authors:  Román Baravalle; Osvaldo A Rosso; Fernando Montani
Journal:  Entropy (Basel)       Date:  2018-09-02       Impact factor: 2.524

  2 in total

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