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1

Institute of Cognitive Neuroscience, National Central University, Jhongli 32001, Taiwan

2

Department of Physics, National Central University, Jhongli 32001, Taiwan

3

Graduate Institute of Humanities in Medicine, Taipei Medicine University, Taipei 11031, Taiwan





*

Author to whom correspondence should be addressed.



Academic Editor: Wassim M. Haddad

Abstract 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. View Full-Text

Keywords: multiscale entropy; MSE; inhibitory control; stop signal; EEG; complexity; adaptability multiscale entropy; MSE; inhibitory control; stop signal; EEG; complexity; adaptability





Autor: Shih-Lin Huang 1,2, Philip Tseng 3 and Wei-Kuang Liang 1,*

Fuente: http://mdpi.com/



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