TY - JOUR
T1 - Relating network connectivity to dynamics
T2 - opportunities and challenges for theoretical neuroscience
AU - Curto, Carina
AU - Morrison, Katherine
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/10
Y1 - 2019/10
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85068842579&partnerID=8YFLogxK
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U2 - 10.1016/j.conb.2019.06.003
DO - 10.1016/j.conb.2019.06.003
M3 - Review article
C2 - 31319287
AN - SCOPUS:85068842579
SN - 0959-4388
VL - 58
SP - 11
EP - 20
JO - Current Opinion in Neurobiology
JF - Current Opinion in Neurobiology
ER -