Detecting functionally coherent networks in fMRI data of the human brain using 
replicator dynamics

Lohmann, Gabriele; von Cramon, D. Yves

doi:10.1007/3-540-45729-1_23

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Detecting functionally coherent networks in fMRI data of the human brain using replicator dynamics

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Lohmann, Gabriele
MPI of Cognitive Neuroscience (Leipzig, -2003), The Prior Institutes, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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von Cramon, D. Yves
MPI of Cognitive Neuroscience (Leipzig, -2003), The Prior Institutes, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Lohmann, G., & von Cramon, D. Y. (2001). Detecting functionally coherent networks in fMRI data of the human brain using replicator dynamics. In M. F. Insana, & R. M. Leahy (Eds.), Information Processing in Medical Imaging (pp. 218-224). Berlin: Springer. doi:10.1007/3-540-45729-1_23.

Cite as: https://hdl.handle.net/21.11116/0000-0003-2961-2

Abstract

We present a new approach to detecting functional networks in fMRI time series data. Functional networks as defined here are characterized by a tight coherence criterion where every network member is closely connected to every other member. This definition of a network closely resembles that of a clique in a graph. We propose to use replicator dynamics for detecting such networks. Our approach differs from standard clustering algorithms in that the entities that are targeted here differ from the traditional cluster concept.