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.
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Lohmann, G., von Cramon, D.Y. (2001). Detecting Functionally Coherent Networks in fMRI Data of the Human Brain Using Replicator Dynamics. In: Insana, M.F., Leahy, R.M. (eds) Information Processing in Medical Imaging. IPMI 2001. Lecture Notes in Computer Science, vol 2082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45729-1_23
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DOI: https://doi.org/10.1007/3-540-45729-1_23
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