On the existence of phase-synchronised states during motor imagery tasks. (September 2019)

• Record Type: Journal Article
• Authors: Santamaria, Lorena; James, Christopher
• Is Part Of: Biomedical signal processing and control. Volume 54(2019)
• Publication Date: 2019-09
• Subjects: EEG -- Clustering -- Motor imagery tasks -- Schematic emotional faces -- Functional brain connectivity -- Synchrostates; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2019.101630
• Languages: English
• ISSNs: 1746-8094

Abstract

Graphical abstract: Abstract: Phase synchronization as a mechanism to measure functional connectivity has been widely used in the literature. However, these studies largely assume that functional connectivity remains constant across a cognitive task and assesses the changes in connectivity across the whole block, hence losing the temporal evolution of phase synchrony. We applied a wavelet-based phase analysis on EEG data during the performance of two motor imagery tasks. This method showed the existence of a reduced number of unique phase-synchronised states during the performance of motor imagery tasks using novel stimuli; schematic faces showing different emotions ("emoticons"). For all participants, these states remained stable for a few milliseconds before switching to the next state following a well-defined sequence. This results demonstrate that the occurrence of these phase states and their temporal stability (switching patterns) are task specific indicating existence of different processing dynamics for the two motor imagery task when are lock to a stimulus. The novel proposed methodology of study the temporal dynamics of brain connectivity can be seen as new method to characterise the dynamics of the underlying cognitive process occurring specifically for each one of the motor tasks. Therefore, this method can be potentially used for brain computer interface purposes.