The Time-Varying Causal Coupling in Brain and Organization of Its Networks
Maciej Kaminski , Katarzyna J Blinowska , Aneta Brzezicka , Jan Kamiński , Rafal Kus
AbstractFor investigation of time-varying brain networks an approach based on estimation of causal coupling by means of multivariate method was applied. Two cognitive experiments: Constant Attention Test and Working Memory task are considered. Time varying version of a multivariate estimator—Directed Transfer Function was used for calculating dynamically changing patterns of transmission during the tasks. Well-defined centers of activity congruent with imaging, anatomical and electrophysiological evidence were found. These centers exchanged the information only during short epochs. The strengths of coupling inside the tightly connected modules and between them was found by means of assortative mixing. The results point out to the well determined, far from randomness structure of brain networks in cognitive tasks. Very dense and disorganized structure of networks reported in literature may be explained by the presence of spurious connections produced by bi-variate measures of connectivity and further enhanced by giving all connections equal weights.
|Objętość publikacji w arkuszach wydawniczych||0.5|
|Książka||Advances in Cognitive Neurodynamics (IV), 2015, Springer Netherlands|
|Słowa kluczowe w języku angielskim||Functional connectivity Causal coupling Directed transfer function Working memory Dynamical EEG propagation Directed networks|
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