T. V. Zakharova | Searcharxiv

arXiv2020

Application of statistical analysis to working memory problem

This article is devoted to EEG studying of connectivity cortical areas involved in keeping vision information in working memory. VAR-modeling was used for describing signals got from connected with working memory brain zones. Brain connections were estimated by based in Granger Causality Partial Directed Coherence (PDC) and then compared by Wilcoxon signed-rank test. In paper connection intensity dependence on executing task was found.

eess.SP↗

arXiv2015

Statistical detection of movement activities in a human brain by separation of mixture distributions

One of most popular experimental techniques for investigation of brain activity is the so-called method of evoked potentials: the subject repeatedly makes some movements (by his/her finger) whereas brain activity and some auxiliary signals are recorded for further analysis. The key problem is the detection of points in the myogram which correspond to the beginning of the movements. The more precisely the points are detected, the more successfully the magnetoencephalogram is processed aiming at the identification of sensors which are closest to the activity areas. The paper proposes a statistical approach to this problem based on mixtures models which uses a specially modified method of moving separation of mixtures of probability distributions (MSM-method) to detect the start points of the finger's movements. We demonstrate the correctness of the new procedure and its advantages as compared with the method based on the notion of the myogram window variance.

stat.AP↗