Journal
ENTROPY
Volume 17, Issue 10, Pages 6834-6853Publisher
MDPI
DOI: 10.3390/e17106834
Keywords
multiscale entropy; MSE; inhibitory control; stop signal; EEG; complexity; adaptability
Categories
Funding
- Ministry of Science and Technology, Taiwan
- Veterans General Hospitals, Taiwan
- University System of Taiwan [MOST 103-2410-H-008-082, MOST 104-2420-H-008-003-MY2, MOST 103-2410-H-008-023-MY3, VGHUST 104-G4-1-1, NSC 102-2420-H-008-001-MY3, NSC 101-2628-H-008-001-MY4]
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The ability to inhibit impulses and withdraw certain responses are essential for human's survival in a fast-changing environment. These processes happen fast, in a complex manner, and require our brain to make a fast adaptation to inhibit the impulsive response. The present study employs multiscale entropy (MSE) to analyzing electroencephalography (EEG) signals acquired alongside a behavioral stop-signal task to theoretically quantify the complexity (indicating adaptability and efficiency) of neural systems to investigate the dynamical change of complexity in the brain during the processes of inhibitory control. We found that the complexity of EEG signals was higher for successful than unsuccessful inhibition in the stage of peri-stimulus, but not in the pre-stimulus time window. In addition, we found that the dynamical change in the brain from pre-stimulus to peri-stimulus stage for inhibitory control is a process of decreasing complexity. We demonstrated both by sensor-level and source-level MSE that the processes of losing complexity is temporally slower and spatially restricted for successful inhibition, and is temporally quicker and spatially extensive for unsuccessful inhibition.
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