Autoren:	Reyes-Puerta, Vicente Kim, Suam Sun, Jyh-Jang Imbrosci, Barbara Kilb, Werner Luhmann, Heiko
Titel:	High stimulus-related information in barrel cortex inhibitory interneurons
Online-Publikationsdatum:	4-Okt-2022
Erscheinungsdatum:	2015
Sprache des Dokuments:	Englisch
Zusammenfassung/Abstract:	The manner in which populations of inhibitory (INH) and excitatory (EXC) neocortical neurons collectively encode stimulus-related information is a fundamental, yet still unresolved question. Here we address this question by simultaneously recording with large-scale multi-electrode arrays (of up to 128 channels) the activity of cell ensembles (of up to 74 neurons) distributed along all layers of 3–4 neighboring cortical columns in the anesthetized adult rat somatosensory barrel cortex in vivo. Using two different whisker stimulus modalities (location and frequency) we show that individual INH neurons – classified as such according to their distinct extracellular spike waveforms – discriminate better between restricted sets of stimuli (≤6 stimulus classes) than EXC neurons in granular and infra-granular layers. We also demonstrate that ensembles of INH cells jointly provide as much information about such stimuli as comparable ensembles containing the ~20% most informative EXC neurons, however presenting less information redundancy – a result which was consistent when applying both theoretical information measurements and linear discriminant analysis classifiers. These results suggest that a consortium of INH neurons dominates the information conveyed to the neocortical network, thereby efficiently processing incoming sensory activity. This conclusion extends our view on the role of the inhibitory system to orchestrate cortical activity.
DDC-Sachgruppe:	610 Medizin 610 Medical sciences
Veröffentlichende Institution:	Johannes Gutenberg-Universität Mainz
Organisationseinheit:	FB 04 Medizin
Veröffentlichungsort:	Mainz
ROR:	https://ror.org/023b0x485
DOI:	http://doi.org/10.25358/openscience-7822
Version:	Published version
Publikationstyp:	Zeitschriftenaufsatz
Nutzungsrechte:	CC BY
Informationen zu den Nutzungsrechten:	https://creativecommons.org/licenses/by/4.0/
Zeitschrift:	PLoS Computational Biology 11 6
Seitenzahl oder Artikelnummer:	e1004121
Verlag:	Public Library of Science
Verlagsort:	San Francisco, Calif.
Erscheinungsdatum:	2015
ISSN:	1553-7358 1553-734X
URL der Originalveröffentlichung:	http://dx.doi.org/10.1371/journal.pcbi.1004121
DOI der Originalveröffentlichung:	10.1371/journal.pcbi.1004121
Enthalten in den Sammlungen:	DFG-OA-Publizieren (2012 - 2017)