Simulation of large scale cortical networks by individual neuron dynamics
- Understanding the functional dynamics of the mammalian brain is one of the central aims of modern neuroscience. Mathematical modeling and computational simulations of neural networks can help in this quest. In recent publications, a multilevel model has been presented to simulate the resting-state dynamics of the cortico-cortical connectivity of the mammalian brain. In the present work we investigate how much of the dynamical behavior of the multilevel model can be reproduced by a strongly simplified model. We find that replacing each cortical area by a single Rulkov map recreates the patterns of dynamical correlation of the multilevel model, while the outcome of other models and setups mainly depends on the local network properties, e. g. the input degree of each vertex. In general, we find that a simple simulation whose dynamics depends on the global topology of the whole network is far from trivial. A systematic analysis of different dynamical models and coupling setups is required.
Author details: | G. Schmidt, Gorka Zamora-LopezGND, Jürgen KurthsORCiDGND |
---|---|
DOI: | https://doi.org/10.1142/S0218127410026149 |
ISSN: | 0218-1274 |
Publication type: | Article |
Language: | English |
Year of first publication: | 2010 |
Publication year: | 2010 |
Release date: | 2017/03/24 |
Source: | International journal of bifurcation and chaos. - ISSN 0218-1274. - 20 (2010), 3, S. 859 - 867 |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie |
Peer review: | Referiert |