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Analysis of generic coupling between EEG activity and PETCO2 in free breathing and breath-hold tasks using Maximal Information Coefficient (MIC).


ABSTRACT: Brain activations related to the control of breathing are not completely known. The respiratory system is a non-linear system. However, the relationship between neural and respiratory dynamics is usually estimated through linear correlation measures, completely neglecting possible underlying nonlinear interactions. This study evaluate the linear and nonlinear coupling between electroencephalographic (EEG) signal and variations in carbon dioxide (CO2) signal related to different breathing task. During a free breathing and a voluntary breath hold tasks, the coupling between EEG power in nine different brain regions in delta (1-3 Hz) and alpha (8-13 Hz) bands and end-tidal CO2 (PET CO2) was evaluated. Specifically, the generic associations (i.e. linear and nonlinear correlations) and a "pure" nonlinear correlations were evaluated using the maximum information coefficient (MIC) and MIC-ρ2 between the two signals, respectively (where ρ2 represents the Pearson's correlation coefficient). Our results show that in delta band, MIC indexes discriminate the two tasks in several regions, while in alpha band the same behaviour is observed for MIC-ρ2, suggesting a generic coupling between delta EEG power and PETCO2 and a pure nonlinear interaction between alpha EEG power and PETCO2. Moreover, higher indexes values were found for breath hold task respect to free breathing.

SUBMITTER: Morelli MS 

PROVIDER: S-EPMC5851981 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Analysis of generic coupling between EEG activity and P<sub>ET</sub>CO<sub>2</sub> in free breathing and breath-hold tasks using Maximal Information Coefficient (MIC).

Morelli Maria Sole MS   Greco Alberto A   Valenza Gaetano G   Giannoni Alberto A   Emdin Michele M   Scilingo Enzo Pasquale EP   Vanello Nicola N  

Scientific reports 20180314 1


Brain activations related to the control of breathing are not completely known. The respiratory system is a non-linear system. However, the relationship between neural and respiratory dynamics is usually estimated through linear correlation measures, completely neglecting possible underlying nonlinear interactions. This study evaluate the linear and nonlinear coupling between electroencephalographic (EEG) signal and variations in carbon dioxide (CO<sub>2</sub>) signal related to different breath  ...[more]

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