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Media type:
E-Article
Title:
On the complexity of resting state spiking activity in monkey motor cortex
Contributor:
Dąbrowska, Paulina Anna
[Author];
Voges, Nicole
[Author];
von Papen, Michael
[Author];
Ito, Junji
[Author];
Dahmen, David
[Author];
Riehle, Alexa
[Author];
Brochier, Thomas
[Author];
Grün, Sonja
[Author]
imprint:
Oxford University Press, 2021
Published in:Cerebral Cortex Communications 2(3), tgab033 (2021). doi:10.1093/texcom/tgab033
Language:
English
DOI:
https://doi.org/10.1093/texcom/tgab033
ISSN:
2632-7376
Origination:
Footnote:
Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
Description:
Resting state has been established as a classical paradigm of brain activity studies, mostly based on large scale measurements such as fMRI or M/EEG. This term typically refers to a behavioral state characterized by the absence of any task or stimuli. The corresponding neuronal activity is often called idle or ongoing. Numerous modeling studies on spiking neural networks claim to mimic such idle states, but compare their results to task– or stimulus-driven experiments, or to results from experiments with anesthetized subjects. Both approaches might lead to misleading conclusions. To provide a proper basis for comparing physiological and simulated network dynamics, we characterize simultaneously recorded single neurons' spiking activity in monkey motor cortex at rest and show the differences from spontaneous and task– or stimulus-induced movement conditions. We also distinguish between rest with open eyes and sleepy rest with eyes closed. The resting state with open eyes shows a significantly higher dimensionality, reduced firing rates and less balance between population level excitation and inhibition than behavior-related states.