title: On the estimation of the direction of information flow in networks of dynamical systems.
abstract: The inference of the interaction structure in networks of dynamical systems promises novel insights into the functioning or malfunctioning of systems in the neurosciences. This may improve the understanding of mechanisms underlying several diseases like tremor disorders and might eventually help to cure patients. Of particular interest is the estimation of the direction of information flow for which different methods have been suggested and have been applied to data from human tremor. Based on a simulated system motivated by the human tremor application we analyze the performance of three methods. The abilities and limitations of the individual techniques are compared and discussed. An application to essential tremor complements this investigation.
authors.affiliation: Department of Physics, University of Freiburg, Hermann-Herder-Str. 3, 79104 Freiburg, Germany. linda.sommerlade@fdm.uni-freiburg.de
authors.forename: Linda
authors.initials: L
authors.lastname: Sommerlade
authors.forename: Florian
authors.initials: F
authors.lastname: Amtage
authors.forename: Olga
authors.initials: O
authors.lastname: Lapp
authors.forename: Bernhard
authors.initials: B
authors.lastname: Hellwig
authors.forename: Carl Hermann
authors.initials: CH
authors.lastname: Lücking
authors.forename: Jens
authors.initials: J
authors.lastname: Timmer
authors.forename: Björn
authors.initials: B
authors.lastname: Schelter
mesh_terms: D001921:Brain / Q000503:physiopathology*; D003198:Computer Simulation; D001330:Electronic Data Processing / Q000379:methods*; D020329:Essential Tremor / Q000473:pathology / Q000503:physiopathology; D006801:Humans; D018482:Muscle, Skeletal / Q000503:physiopathology; D009415:Nerve Net / Q000503:physiopathology*; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics