Brain-wave music improves the decline in inhibitory control caused by mental fatigue
Poster No:
778
Submission Type:
Abstract Submission
Authors:
Yan Li1, Xinjian Su1, Liju Wang1, Haoyu Bian1, Haohan Yang1, Jing Lu1
Institutions:
1University of Electronic Science and Technology of China, Chengdu, Sichuan
First Author:
Co-Author(s):
Introduction:
Inhibitory control is one of the important cognitive functions, and the prefrontal lobes are thought to be closely related to inhibitory control function(Loftus, Yalcin, Baughman, Vanman, & Hagger, 2015). When people are mentally fatigued, their inhibitory control performance decreases(Guo et al., 2018), and music can improve inhibitory control performance(Mansouri et al., 2017). Previous studies have suggested that improved inhibitory control function with music training may be related to theta oscillations in the mid-frontal region(Lu et al., 2022). Previous research has demonstrated that using brain-wave music to intervene in fatigue has advantages over classical music(Wang et al., 2023). Therefore, we recruited three groups of subjects to explore whether brain-wave music has an advantage in intervening in cognitive fatigue-related declines in inhibitory control and the underlying mechanisms.
Methods:
Three groups of subjects (n=18 in each group) were recruited for the study: a personalized brain-wave music group (BWM), a classical music group (CM), and a blank control group (CTL). The EEG data were preprocessed using the EEGLAB toolbox, after which time-frequency analysis was conducted. The experimental paradigm was designed based on the Go/NoGo graphical and high cognitive load keystroke tasks. The procedure began with a five-minute resting state, followed by the baseline Go/NoGo task. This was followed by the high cognitive load keystroke task, which lasted for 20 minutes. Subsequently, the pre-music Go/NoGo task was administered, followed by 10 minutes of music modulation (with CTL at rest). Finally, the post-music Go/NoGo task was conducted.
Results:
We counted the accuracy of the Go/NoGo task on three occasions and found that there was a significant difference in the accuracy of the three tasks (BWM: p<0.01, F=10.05; CM: p<0.01, F=6.59; CTL: p=0.011, F=6.06), all three groups of subjects showed a significant decrease in the accuracy of the Go/NoGo task after the high cognitive load task (BWM: p=0.013, t=-3.29; CM: p=0.024, t=-3.01; CTL: p=0.035, t=-2.82; Bonferroni-corrected) (Fig.1), and only the BWM group showed a significant increase in the accuracy of the Go/NoGo task after the music intervention (BWM: p<0.01, t=4.58; Bonferroni-corrected) (Fig.1a). We also performed a time-frequency analysis of theta activity in the mid-frontal regions (FC1, FC2), only the BWM group showed a significant increase in the difference in theta power between NoGo and Go trials after music intervention (BWM: p=0.048, t=2.13) (Fig.2c).
·Fig.1: Accuracy of three Go/NoGo tasks performed by three groups of subjects (Bonferroni-corrected).
·Fig.2: A time-frequency analysis of theta activity in the middle frontal region was conducted on three groups of subjects before(pre) and after(post) a musical intervention (NoGo minus Go).
Conclusions:
Our results suggest that the cognitive fatigue-inducing paradigm is effective. In addition, only the BWM group showed a significant increase in accuracy after the intervention using different music. This reflects the unique advantage of personalized brain-wave music for intervening in the decline in inhibitory control. Rhythmic neural electrical activity is the basis of cognitive function, and neural oscillations are generated by the repetitive, rhythmic interactions of single or multiple neurons(Jensen & Colgin, 2007), and neural oscillations are the synchronization of neural oscillations induced by external rhythmic stimuli(Helfrich, Breska, & Knight, 2019). Brain-wave music contains information about the electrophysiological activity of the human brain regarding the principles of brain-wave music generation. We used brain-wave music generated by the subjects' own EEG, so its modulation of neuronal excitability through neural oscillations may be stronger, resulting in a better fatigue intervention effect, which explains why the change in theta activity in the BWM group was higher than that of the other groups after the music intervention. This work will provide a basis for exploring the use of brain-wave music for personalized modulation of cognitive fatigue.
Higher Cognitive Functions:
Executive Function, Cognitive Control and Decision Making 2
Music 1
Keywords:
Cognition
Electroencephaolography (EEG)
Other - Brain-wave Music;Fatigue;Prefrontal Cortex
1|2Indicates the priority used for review
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Provide references using APA citation style.
Helfrich, R. F. (2019). Neural entrainment and network resonance in support of top-down guided attention. Current Opinion in Psychology, 29, 82-89.
Jensen, O. (2007). Cross-frequency coupling between neuronal oscillations. Trends in Cognitive Sciences, 11(7), 267-269.
Loftus, A. M. (2015). The impact of transcranial direct current stimulation on inhibitory control in young adults. Brain and Behavior, 5(5), e00332.
Lu, J. (2022). Music training modulates theta brain oscillations associated with response suppression. Annals of the New York Academy of Sciences, 1516(1), 212-221.
Mansouri, F. A. (2017). Interactive effects of music and prefrontal cortex stimulation in modulating response inhibition. Scientific Reports, 7(1), 18096.
Wang, J. (2023). Effects and Mechanisms of Brain-Wave Music Intervention on Fatigue. Journal of Fudan University(Natural Science), 62(1), 63-68+82.