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Nat Rev Neurosci. 2019 Feb;20(2):117-127. doi: 10.1038/s41583-018-0094-0.

Portraits of communication in neuronal networks.

Author information

1
Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain. gerald.hahn@upf.edu.
2
Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
3
Instituci├│ Catalana de la Recerca i Estudis Avan├žats, Universitat Pompeu Fabra, Barcelona, Spain.
4
Faculty of Biology, University of Freiburg, Freiburg, Germany.
5
Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany.
6
Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany. arvkumar@kth.se.
7
Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden. arvkumar@kth.se.

Abstract

The brain is organized as a network of highly specialized networks of spiking neurons. To exploit such a modular architecture for computation, the brain has to be able to regulate the flow of spiking activity between these specialized networks. In this Opinion article, we review various prominent mechanisms that may underlie communication between neuronal networks. We show that communication between neuronal networks can be understood as trajectories in a two-dimensional state space, spanned by the properties of the input. Thus, we propose a common framework to understand neuronal communication mediated by seemingly different mechanisms. We also suggest that the nesting of slow (for example, alpha-band and theta-band) oscillations and fast (gamma-band) oscillations can serve as an important control mechanism that allows or prevents spiking signals to be routed between specific networks. We argue that slow oscillations can modulate the time required to establish network resonance or entrainment and, thereby, regulate communication between neuronal networks.

PMID:
30552403
DOI:
10.1038/s41583-018-0094-0

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