wPLI for Pre-Training Desynchronization Identification

EasyChair Preprint no. 7751

Abstract

Motor processing can result in coordinated changes of   ongoing/decreasing brain neural activity, or event-related de/synchronization (ERD/S), over both lateral brain hemispheres. Because of Motor processing can result in coordinated changes of ongoing/decreasing brain neural activity, or event-related de/synchronization (ERD/S), over both lateral brain hemispheres. Because of the affordability and time resolution provided, Electroencephalographic (EEG) signals are commonly used to acquire motor imagery paradigms. However, the widely known condition of low-noise signals makes detection and spatial localization of ERD/S challenging. Here, to deal with the high variability between subjects, we propose to perform group analysis of graph representations extracted from the weighted Phase lock Index. Statistical thresholding of the functional connectivity estimates is also accomplished to improve the assessments of phase synchronization between electrodes. The obtained results on a real-world database with $50$ individuals show that the proposed methodology improves interpretation of ERD/S, allowing better prediction of motor imagery ability in subjects having low skills for practicing this paradigm.

Keyphrases: functional connectivity, Group Analysis, synchronization, wPLI

@Booklet{EasyChair:7751,
  author = {F.Y. Zapata and O.W. Gómez and A.M. Alvarez and C.G. Castellanos},
  title = {wPLI for Pre-Training Desynchronization Identification},
  howpublished = {EasyChair Preprint no. 7751},

  year = {EasyChair, 2022}}