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神经网络动力学与异常抑制控制下的互联网成瘾的大脑振荡。

Neural Network Dynamics and Brain Oscillations Underlying Aberrant Inhibitory Control in Internet Addiction.

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2024;32:946-955. doi: 10.1109/TNSRE.2024.3363756. Epub 2024 Feb 28.


DOI:10.1109/TNSRE.2024.3363756
PMID:38335078
Abstract

Previous studies have reported a role of alterations in the brain's inhibitory control mechanism in addiction. Mounting evidence from neuroimaging studies indicates that its key components can be evaluated with brain oscillations and connectivity during inhibitory control. In this study, we developed an internet-related stop-signal task with electroencephalography (EEG) signal recorded to investigate inhibitory control. Healthy controls and participants with Internet addiction were recruited to participate in the internet-related stop-signal task with 19-channel EEG signal recording, and the corresponding event-related potentials and spectral perturbations were analyzed. Brain effective connections were also evaluated using direct directed transfer function. The results showed that, relative to the healthy controls, participants with Internet addiction had increased Stop-P3 during inhibitory control, suggesting that they have an altered neural mechanism in impulsive control. Furthermore, participants with Internet addiction showed increased low-frequency synchronization and decreased alpha and beta desynchronization in the middle and right frontal regions compared to healthy controls. Aberrant brain effective connectivity was also observed, with increased occipital-parietal and intra-occipital connections, as well as decreased frontal-paracentral connection in participants with Internet addiction. These results suggest that physiological signals are essential in future implementations of cognitive assessment of Internet addiction to further investigate the underlying mechanisms and effective biomarkers.

摘要

先前的研究报告指出,大脑抑制控制机制的改变与成瘾有关。越来越多的神经影像学研究证据表明,其关键组成部分可以通过抑制控制期间的脑振荡和连通性来评估。在这项研究中,我们开发了一个基于互联网的停止信号任务,使用脑电图 (EEG) 信号记录来研究抑制控制。招募了健康对照组和网络成瘾参与者参与基于互联网的停止信号任务,并记录了 19 通道 EEG 信号,分析了相应的事件相关电位和频谱扰动。还使用直接定向传递函数评估了大脑有效连接。结果表明,与健康对照组相比,网络成瘾者在抑制控制期间的停止 P3 增加,表明他们在冲动控制方面存在改变的神经机制。此外,与健康对照组相比,网络成瘾者在中额和右侧额区显示出低频同步增加和 alpha 和 beta 去同步减少。还观察到异常的大脑有效连接,网络成瘾者的枕顶和颅内连接增加,而额顶中央连接减少。这些结果表明,生理信号在未来的网络成瘾认知评估实施中至关重要,以进一步研究潜在机制和有效的生物标志物。

相似文献

[1]
Neural Network Dynamics and Brain Oscillations Underlying Aberrant Inhibitory Control in Internet Addiction.

IEEE Trans Neural Syst Rehabil Eng. 2024

[2]
Altered Inhibitory Control Mechanism of Internet Addiction: An Electroencephalogram Study of Brain Oscillations and Connectivity.

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[3]
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[4]
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[5]
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Neuroimage Clin. 2020

[6]
Spontaneous brain microstates correlate with impaired inhibitory control in internet addiction disorder.

Psychiatry Res Neuroimaging. 2023-9

[7]
EEG components of inhibitory control ability in internet gaming disorder: A systematic review and meta-analysis of randomized controlled trials.

Brain Behav. 2024-1

[8]
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Psychol Med. 2022-8

[9]
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Int J Psychophysiol. 2013-6-14

[10]
Age-related and individual variations in altered prefrontal and cerebellar connectivity associated with the tendency of developing internet addiction.

Hum Brain Mapp. 2021-10-1

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