Condition, the only difference getting the threshold employed. Ordinarily, hyperbrain coherence maps are composed of four quadrants, two of which correspond towards the within-brain condition, and two towards the buy HOE 239 between-brains condition. On the basis with the procedure followed to reconstruct the hyperbrain EEG data sets, the upper left and reduce suitable quadrants correspond towards the individual coherence maps (within-brain) in the two jugglers, and have been considered for additional hyperbrain analysis. The other two quadrants (upper correct and reduced left) refer for the hyperbrain coherence maps representing the functional connections involving the two jugglers’ brains. Because of the symmetry of these coherence maps, only 1 between-brains map was thought of for subsequent analysis.Filho et al. (2016), PeerJ, DOI 10.7717/peerj.12/Figure three Illustration of coherence maps obtained utilizing two different thresholds at values 0.five and 0.eight inside the alpha band. In these maps precisely the same threshold was applied for within-brain and between-brain coherence values. The maps are normalized immediately after thresholding to improve the differences across the retained functional connections. It may be seen that variation in the threshold value doesn’t adjust the basic path of observed coherence patterns.Estimate of the error variance within the point estimates of coherence is needed to draw any conclusion on connectivity variations among subjects or circumstances. Coherence standard error maps had been then calculated employing a bootstrapping process applied to the coherence values of all channel pairs (within- and between-brains) for each and every difficulty level and every single frequency band. Two hundred bootstrap samples had been drawn to estimate the regular errors (Efron Tibshirani, 1993; Hesterberg et al., 2003). Measures of functional organization Graph Theory describes the topology of functional brain networks, and characterizes their regional and global efficiency in terms of facts segregation and integration properties. Within this framework, patterns of functional connections are represented as graphs exactly where the elements on the network, the nodes (in our case the electrodes), are linkedFilho et al. (2016), PeerJ, DOI 10.7717/peerj.13/with edges that represent the relationships (or functional interactions) PubMed ID:http://www.ncbi.nlm.nih.gov/pubmed/20011050 among nodes. We applied graph theoretical ideas to study the topological options of your within-brain and between-brains functional networks represented by the individual and dyadic imply coherence maps, respectively. For every juggler (or for the dyad), for each juggling phase (i.e., difficulty level) and for each frequency band (i.e., alpha and theta), the cortical functional organization was characterized by indicates of segregation and integration measures calculated around the connected mean coherence maps, where each coherence worth (when diverse from zero) represents the strength of the functional connection between two provided cortical websites (identified by the electrodes’ positions). In the brain, functional segregation refers to specialized details processing that occurs inside densely interconnected groups of brain regions (Rubinov Sporns, 2010). Since coherence maps are calculated in the sensor space, segregated neural processing will be suggested by statistical dependencies among clustered electrodes. We calculated functional segregation by signifies with the mean clustering coefficient C, that is a weighted measure on the prevalence of clustered connectivity about individual nodes (Watts Strogatz, 1.