Relating network connectivity to dynamics: opportunities and challenges for theoretical neuroscience

Carina Curto; Katherine Morrison

doi:10.1016/j.conb.2019.06.003

Relating network connectivity to dynamics: opportunities and challenges for theoretical neuroscience

Curr Opin Neurobiol. 2019 Oct:58:11-20. doi: 10.1016/j.conb.2019.06.003. Epub 2019 Jul 15.

Authors

Carina Curto¹, Katherine Morrison²

Affiliations

¹ The Pennsylvania State University, PA 16802, United States. Electronic address: cpc16@psu.edu.
² School of Mathematical Sciences, University of Northern Colorado, Greeley, CO 80639, USA.

Abstract

We review recent work relating network connectivity to the dynamics of neural activity. While concepts stemming from network science provide a valuable starting point, the interpretation of graph-theoretic structures and measures can be highly dependent on the dynamics associated to the network. Properties that are quite meaningful for linear dynamics, such as random walk and network flow models, may be of limited relevance in the neuroscience setting. Theoretical and computational neuroscience are playing a vital role in understanding the relationship between network connectivity and the nonlinear dynamics associated to neural networks.

Publication types

Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.
Review

MeSH terms

Models, Neurological*
Nerve Net
Neural Networks, Computer
Neurosciences*
Nonlinear Dynamics

Grants and funding

R01 EB022862/EB/NIBIB NIH HHS/United States