Open AccessMoving correlations and chaos in the brain during closed eyes basal conditions
Author(s) -
Hernán Díaz M.,
Fernando Maureira,
Gonzalo Flores,
Ignacio Fuentes,
Fernando García,
Pablo Maertens,
Sergio Muñoz,
Felipe Parra,
Felisa M. Córdova
Publication year - 2018
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2018.10.248
Subject(s) - hurst exponent , electroencephalography , detrended fluctuation analysis , computer science , estimator , nonlinear system , series (stratigraphy) , resting state fmri , oscillation (cell signaling) , artificial intelligence , pattern recognition (psychology) , mathematics , statistical physics , statistics , psychology , neuroscience , physics , paleontology , geometry , quantum mechanics , scaling , biology , genetics
In this work we explored the use of linear and nonlinear, statistical approaches to studying basal EEG brain activity. To do this, we used the Moving Correlation Coefficient (MCC), and the Hurst exponent estimator to visualize short and long term EEG behavior during 2 minutes of EEG recording in closed eyes basal conditions. The EEG of 8 subjects served as data source for exploring the time series organization of the EEG in resting state. We found inter-subjects shared network patterns of high synchronic functional connectivity in frontal and right temporo-occipital regions. We also found a diversity of individual different networks of variable degree of synchronicity in the range of -0.5 0.5 for all channels. The short-term approximation to the chaos oscillation (M-Hurst) revealed several individual differences and a potential tool for subject’s characterization.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom