Investigating the Role of Alpha and Beta Rhythms in Functional Motor Networks. (15th May 2018)

• Record Type: Journal Article
• Authors: Athanasiou, Alkinoos; Klados, Manousos A.; Styliadis, Charis; Foroglou, Nicolas; Polyzoidis, Konstantinos; Bamidis, Panagiotis D.
• Is Part Of: Neuroscience. Volume 378(2018)
• Page Start: 54
• Page End: 70
• Publication Date: 2018-05-15
• Subjects: BCIs Brain-Computer Interfaces -- CC clustering coefficient -- CCD Cortical Current Density -- CPL characteristic path length -- D density -- DTF Directed Transfer Function -- EEG electroencephalography -- FME foot motor execution -- FMI foot motor imagery -- HME hand motor execution -- HMI Hand motor imagery -- MNI Montreal Neurological Institute -- MRI Magnetic Resonance Imaging -- MVAR multivariate autoregressive -- PCC Pearson's Correlation Coefficient -- ROIs regions of interest -- SW small-world-ness; brain waves -- electroencephalography -- functional connectivity -- motor imagery -- motor network -- sensorimotor cortex; Neurochemistry -- Periodicals; Neurophysiology -- Periodicals; Neurology -- Periodicals; Neurochimie -- Périodiques; Neurophysiologie -- Périodiques; Neurochemistry; Neurophysiology; Electronic journals; Periodicals; Electronic journals; 612.8
• DOI: 10.1016/j.neuroscience.2016.05.044
• Languages: English
• ISSNs: 0306-4522

Abstract

Highlights: We investigated alpha and beta functional networks in motor execution and imagery. Characteristic path length and clustering coefficient were lower for beta networks. Alpha uses greater wiring costs and assumes local processing of information. Beta forms denser networks and assumes the coordination of the sensorimotor task. Our findings in part contradict traditional concepts on brain rhythms' roles. Abstract: It is recognized that lower electroencephalography (EEG) frequencies correspond to distributed brain activity over larger spatial regions than higher frequencies and are associated with coordination. In motor processes it has been suggested that this is not always the case. Our objective was to explore this contradiction. In our study, seven healthy subjects performed four motor tasks (execution and imagery of right hand and foot) under EEG recording. Two cortical source models were defined, model «A» with 16 regions of interest (ROIs) and model «B» with 20 ROIs over the sensorimotor cortex. Functional connectivity was calculated by Directed Transfer Function for alpha and beta rhythm networks. Four graph properties were calculated for each network: characteristic path length (CPL), clustering coefficient (CC), density (D) and small-world-ness (SW). Different network modules and in-degrees of nodes were also calculated and depicted in connectivity maps. Analysis of variance was used to determine statistical significance of observed differences in the network properties between tasks, between rhythms and between ROI models. Consistently on both models, CPL and CC were lower and D was higher in beta rhythm networks. No statistically significant difference was observed for SW between rhythms or for any property between tasks on any model. Comparing the models we observed lower CPL for both rhythms, lower CC in alpha and higher CC in beta when the number of ROIs increased. Also, denser networks with higher SW were correlated with higher number of ROIs. We propose a non-exclusive model where alpha rhythm uses greater wiring costs to engage in local information progression while beta rhythm coordinates the neurophysiological processes in sensorimotor tasks.