Please use this identifier to cite or link to this item:
Authors: Reyes-Puerta, Vicente
Kim, Suam
Sun, Jyh-Jang
Imbrosci, Barbara
Kilb, Werner
Luhmann, Heiko
Title: High stimulus-related information in barrel cortex inhibitory interneurons
Online publication date: 4-Oct-2022
Year of first publication: 2015
Language: english
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: 610 Medizin
610 Medical sciences
Institution: Johannes Gutenberg-Universität Mainz
Department: FB 04 Medizin
Place: Mainz
Version: Published version
Publication type: Zeitschriftenaufsatz
License: CC BY
Information on rights of use:
Journal: PLoS Computational Biology
Pages or article number: e1004121
Publisher: Public Library of Science
Publisher place: San Francisco, Calif.
Issue date: 2015
ISSN: 1553-7358
Publisher URL:
Publisher DOI: 10.1371/journal.pcbi.1004121
Appears in collections:DFG-OA-Publizieren (2012 - 2017)

Files in This Item:
  File Description SizeFormat
high_stimulusrelated_informat-20220914001929405.pdf2.93 MBAdobe PDFView/Open