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Neuroimage. 2014 Apr 15;90:218-34. doi: 10.1016/j.neuroimage.2013.12.048. Epub 2013 Dec 31.

Revealing the brain's adaptability and the transcranial direct current stimulation facilitating effect in inhibitory control by multiscale entropy.

Author information

1
Institute of Cognitive Neuroscience, National Central University, Jhongli, Taiwan. Electronic address: weikuangliang@gmail.com.
2
Center for Dynamical Biomarkers and Translational Medicine, National Central University, Jhongli, Taiwan; Research Center for Adaptive Data Analysis, National Central University, Chungli, Taiwan.
3
Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan; Division of Interdisciplinary Medicine & Biotechnology and Margret & H.A. Rey Institute for Nonlinear Dynamics in Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
4
Center for Dynamical Biomarkers and Translational Medicine, National Central University, Jhongli, Taiwan; Division of Interdisciplinary Medicine & Biotechnology and Margret & H.A. Rey Institute for Nonlinear Dynamics in Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
5
Institute of Cognitive Neuroscience, National Central University, Jhongli, Taiwan.
6
Institute of Cognitive Neuroscience, National Central University, Jhongli, Taiwan. Electronic address: chijuan@cc.ncu.edu.tw.

Abstract

The abilities to inhibit impulses and withdraw certain responses are critical for human's survival in a fast-changing environment. These processes happen fast, in a complex manner, and sometimes are difficult to capture with fMRI or mean electrophysiological brain signal alone. Therefore, an alternative measure that can reveal the efficiency of the neural mechanism across multiple timescales is needed for the investigation of these brain functions. The present study employs a new approach to analyzing electroencephalography (EEG) signal: the multiscale entropy (MSE), which groups data points with different timescales to reveal any occurrence of repeated patterns, in order to theoretically quantify the complexity (indicating adaptability and efficiency) of neural systems during the process of inhibitory control. From this MSE perspective, EEG signals of successful stop trials are more complex and information rich than that of unsuccessful stop trials. We further applied transcranial direct current stimulation (tDCS), with anodal electrode over presupplementary motor area (preSMA), to test the relationship between behavioral modification with the complexity of EEG signals. We found that tDCS can further increase the EEG complexity of the frontal lobe. Furthermore, the MSE pattern was found to be different between high and low performers (divided by their stop-signal reaction time), where the high-performing group had higher complexity in smaller scales and less complexity in larger scales in comparison to the low-performing group. In addition, this between-group MSE difference was found to interact with the anodal tDCS, where the increase of MSE in low performers benefitted more from the anodal tDCS. Together, the current study demonstrates that participants who suffer from poor inhibitory control can efficiently improve their performance with 10min of electrical stimulation, and such cognitive improvement can be effectively traced back to the complexity within the EEG signals via MSE analysis, thereby offering a theoretical basis for clinical intervention via tDCS for deficits in inhibitory control.

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