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000877339 1001_ $$0P:(DE-Juel1)171408$$aDąbrowska, Paulina Anna$$b0$$eCorresponding author
000877339 245__ $$aOn the complexity of resting state spiking activity in monkey motor cortex
000877339 260__ $$aCold Spring Harbor$$bCold Spring Harbor Laboratory, NY$$c2020
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000877339 520__ $$aResting state has been established as a classical paradigm of brain activity studies, mostly based on large scale measurements such as fMRI or M/EEG. This term typically refers to a behavioral state characterized by the absence of any task or stimuli. The corresponding neuronal activity is often called idle or ongoing. Numerous modeling studies on spiking neural networks claim to mimic such idle states, but compare their results to task- or stimulus-driven experiments, which might lead to misleading conclusions. To provide a proper basis for comparing physiological and simulated network dynamics, we characterize simultaneously recorded single neurons' spiking activity in monkey motor cortex and show the differences from spontaneous and task-induced movement conditions. The resting state shows a higher dimensionality, reduced firing rates and less balance between population level excitation and inhibition than behavior-related states. Additionally, our results stress the importance of distinguishing between rest with eyes open and closed.
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000877339 7001_ $$0P:(DE-Juel1)168479$$aVoges, Nicole$$b1
000877339 7001_ $$0P:(DE-Juel1)171972$$avon Papen, Michael$$b2
000877339 7001_ $$0P:(DE-Juel1)144576$$aIto, Junji$$b3
000877339 7001_ $$0P:(DE-Juel1)156459$$aDahmen, David$$b4
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000877339 7001_ $$00000-0001-6948-1234$$aBrochier, Thomas$$b6
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000877339 773__ $$0PERI:(DE-600)2766415-6$$a10.1101/2020.05.28.121095$$y2020
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