Correlated neuronal activity and its relationship to coding, dynamics and network architecture

98.8K

views

51

authors

16

articles

Correlated neuronal activity and its relationship to coding, dynamics and network architecture

98.8K

views

51

authors

16

articles

Editorial

27 August 2014

Robert Rosenbaum

,

Tatjana Tchumatchenko

and

Rubén Moreno-Bote

8,337 views

9 citations

Editors

3

Robert Rosenbaum

University of Notre Dame

Tatjana Tchumatchenko

Max Planck Institute for Brain Research

Ruben Moreno-Bote

Pompeu Fabra University

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Correlated and synchronous activity in populations of neurons has been observed in many brain regions and has been shown to play a crucial role in cortical coding, attention, and network dynamics. Accurately measuring and estimating spiking correlations and synchrony in vivo presents several methodological difficulties. For example, despite recent advances in multicellular recording techniques, the
number of neurons from which spiking activity can be simultaneously recorded remains orders magnitude smaller than the size of local networks. In addition, there is a lack of consensus on the distribution of pairwise spike cross correlations obtained in extracellular multi-unit recordings in any brain region. These limitations highlight the need for theoretical and modeling approaches to understand how correlations emerge and to decipher the functional role of correlated and synchronous activity in the brain.

Contributions to this special topic should advance our understanding of how correlations and synchrony are shaped by neuronal dynamics and network structure. Contributions addressing the impact of coordinated activity on coding and network dynamics are also welcome.

Examples include
1. Sources of spiking synchrony and correlations in recurrent networks.
2. The impact of cellular and synaptic dynamics on the coordinated activity of neuronal populations.
3. The role of network structure and connectivity motifs in network dynamics.
4. Ensemble encoding strategies in interconnected neuronal populations.

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Editors

Robert Rosenbaum

University of Notre Dame

Tatjana Tchumatchenko

Max Planck Institute for Brain Research

Ruben Moreno-Bote

Pompeu Fabra University

Impact

98,784 Total views

70,844 Article views

21,352 Article downloads

6,588 Topic views

Published In

Frontiers in Computational Neuroscience

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