Synchrony timescales underlie irregular neocortical spiking

Pattadkal JJ(1), O’Shea RT(2), Hansel D(3), Taillefumier T(4), Brager DH(5),Priebe NJ(6).

Author information:
(1)Department of Neuroscience, The University of Texas at Austin, Austin, TX,
USA; Center for Learning and Memory, The University of Texas at Austin, Austin,
TX, USA. Electronic address: .
(2)Department of Neuroscience, The University of Texas at Austin, Austin, TX,
USA.
(3)Cerebral Dynamics, Plasticity and Learning Laboratory, CNRS, University Paris
Cité, Paris, France.
(4)Department of Neuroscience, The University of Texas at Austin, Austin, TX,
USA; Department of Mathematics, The University of Texas at Austin, Austin, TX,
USA.
(5)Department of Life Sciences, The University of Nevada, Las Vegas, Las Vegas,
NV, USA.
(6)Department of Neuroscience, The University of Texas at Austin, Austin, TX,
USA; Center for Learning and Memory, The University of Texas at Austin, Austin,
TX, USA. Electronic address: .

Update of
bioRxiv. 2024 Oct 16:2024.10.15.618398. doi: 10.1101/2024.10.15.618398.

Cortical neurons are characterized by their variable spiking patterns. Here, we
examine the specific hypothesis that cortical synchrony drives spiking
variability in vivo. Using dynamic clamps, we demonstrate that intrinsic
neuronal properties do not contribute substantially to spiking variability, but
rather spiking variability emerges from weakly synchronous network drive. With
large-scale electrophysiology, we quantify the degree of synchrony and its
timescale in cortical networks in vivo. The timescale of synchrony shifts in a
range from 25 to 200 ms, depending on the presence of external sensory input. In
particular, when the network moves from spontaneous to driven modes, the
synchrony timescales shift from slow to fast, leading to a natural reduction in
response variability across cortical areas. Finally, while an individual neuron
exhibits reliable responses to physiological drive, different neurons respond in
a distinct fashion according to their intrinsic properties, contributing to
stable synchrony across the neural network.

Copyright © 2025 The Author(s). Published by Elsevier Inc. All rights reserved.

DOI: 10.1016/j.neuron.2025.11.005
PMCID: PMC12768470
PMID: 41412130 [Indexed for MEDLINE]

Conflict of interest statement: Declaration of interests The authors declare no
competing interests.

Auteurs Bordeaux Neurocampus