Using replicator dynamics for analyzing fMRI data of the human brain.
The understanding of brain networks becomes increasingly the focus of current research. In the context of functional magnetic resonance imagery (fMRI) data of the human brain, networks have been mostly detected using standard clustering approaches. In this work, we present a new method of detecting functional networks using fMRI data. The novelty of this method is that these networks have the property that every network member is closely connected with every other member. This definition might to be better suited to model important aspects of brain activity than standard cluster definitions. The algorithm that we present here is based on a concept from theoretical biology called "replicator dynamics."
Lohmann
Gabriele
G
Max-Planck-Institute of Cognitive Neuroscience, Leipzig, Germany. lohmann@cns.mpg.de
Bohn
Stefan
S
D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology / Q000502:physiology; D001931:Brain Mapping / Q000379:methods*; D016000:Cluster Analysis; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015233:Models, Statistical; D009415:Nerve Net / Q000033:anatomy & histology*; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity