The Time-Varying Causal Coupling in Brain and Organization of Its Networks

Maciej Kaminski , Katarzyna J Blinowska , Aneta Brzezicka , Jan Kamiński , Rafal Kus


For 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.
Author Maciej Kaminski
Maciej Kaminski,,
, Katarzyna J Blinowska
Katarzyna J Blinowska,,
, Aneta Brzezicka (Wydział Psychologii)
Aneta Brzezicka,,
- Wydział Psychologii
, Jan Kamiński
Jan Kamiński,,
, Rafal Kus
Rafal Kus,,
Publication size in sheets0.5
Book Advances in Cognitive Neurodynamics (IV), 2015, Springer Netherlands
Keywords in EnglishFunctional connectivity Causal coupling Directed transfer function Working memory Dynamical EEG propagation Directed networks
Languageen angielski
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