Literature DB >> 25966805

Infragranular layers lead information flow during slow oscillations according to information directionality indicators.

J M Amigó1, R Monetti, N Tort-Colet, M V Sanchez-Vives.   

Abstract

The recurrent circuitry of the cerebral cortex generates an emergent pattern of activity that is organized into rhythmic periods of firing and silence referred to as slow oscillations (ca 1 Hz). Slow oscillations not only are dominant during slow wave sleep and deep anesthesia, but also can be generated by the isolated cortical network in vitro, being a sort of default activity of the cortical network. The cortex is densely and reciprocally connected with subcortical structures and, as a result, the slow oscillations in situ are the result of an interplay between cortex and thalamus. Due to this reciprocal connectivity and interplay, the mechanism responsible for the initiation of waves in the corticothalamocortical loop during slow oscillations is still a matter of debate. It was our objective to determine the directionality of the information flow between different layers of the cortex and the connected thalamus during spontaneous activity. With that purpose we obtained multilayer local field potentials from the rat visual cortex and from its connected thalamus, the lateral geniculate nucleus, during deep anaesthesia. We analyzed directionality of information flow between thalamus, cortical infragranular layers (5 and 6) and supragranular layers (2/3) by means of three information theoretical indicators: transfer entropy, symbolic transfer entropy and transcript mutual information. These three indicators coincided in finding that infragranular layers lead the information flow during slow oscillations both towards supragranular layers and towards the thalamus.

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Year:  2015        PMID: 25966805     DOI: 10.1007/s10827-015-0563-7

Source DB:  PubMed          Journal:  J Comput Neurosci        ISSN: 0929-5313            Impact factor:   1.621


  33 in total

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Journal:  Nat Neurosci       Date:  2013-01-13       Impact factor: 24.884

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Journal:  Phys Rev Lett       Date:  2008-04-14       Impact factor: 9.161

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  2 in total

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Journal:  J Neural Eng       Date:  2018-06-01       Impact factor: 5.379

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  2 in total

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