用脑电波识别冰毒成瘾者，验证治疗效果更客观。
Repetitive TMS-based Identification of Methamphetamine-Dependent Individuals Using EEG Spectra
- 通过脑电γ波功率变化区分成瘾者与健康人。
- 治疗后γ波功率接近健康人水平，准确率达90%。
- 适合研究神经反馈和个性化戒毒疗法的团队。
重复经颅磁刺激（rTMS）对冰毒成瘾者渴求程度的影响常依赖问卷评估。本研究探索利用神经信号实现更客观的评估。分析20名冰毒成瘾者在rTMS前（MBT）和后（MAT）以及20名健康对照者（HC）的脑电数据。每个受试者观看15张冰毒相关图像和15张中性图像，提取各频段相对功率（RBP）。分析31个通道的平均RBP及不同脑区变化。结果显示，MAT状态下α、β、γ频段的RBP更接近HC，功率拓扑图支持该结论。采用随机森林（RF）模型，γ频段RBP在区分MBT与HC时达到90%准确率。区分MAT与HC的分类性能较低，表明可用γRBP验证rTMS疗效。此外，TP10和CP2通道的γRBP在面对冰毒相关图像时主导了MBT与HC的分类任务。因此，暴露于冰毒相关线索时的γRBP可作为区分成瘾者与健康人的生物标志物，并用于评估rTMS效果。实时监测γRBP变化，有望用于构建个性化闭环神经调控系统治疗冰毒成瘾。
原文摘要 · Abstract (English)
The impact of repetitive transcranial magnetic stimulation (rTMS) on methamphetamine (METH) users' craving levels is often assessed using questionnaires. This study explores the feasibility of using neural signals to obtain more objective results. EEG signals recorded from 20 METH-addicted participants Before and After rTMS (MBT and MAT) and from 20 healthy participants (HC) are analyzed. In each EEG paradigm, participants are shown 15 METH-related and 15 neutral pictures randomly, and the relative band power (RBP) of each EEG sub-band frequency is derived. The average RBP across all 31 channels, as well as individual brain regions, is analyzed. Statistically, MAT's alpha, beta, and gamma RBPs are more like those of HC compared to MBT, as indicated by the power topographies. Utilizing a random forest (RF), the gamma RBP is identified as the optimal frequency band for distinguishing between MBT and HC with a 90% accuracy. The performance of classifying MAT versus HC is lower than that of MBT versus HC, suggesting that the efficacy of rTMS can be validated using RF with gamma RBP. Furthermore, the gamma RBP recorded by the TP10 and CP2 channels dominates the classification task of MBT versus HC when receiving METH-related image cues. The gamma RBP during exposure to METH-related cues can serve as a biomarker for distinguishing between MBT and HC and for evaluating the effectiveness of rTMS. Therefore, real-time monitoring of gamma RBP variations holds promise as a parameter for implementing a customized closed-loop neuromodulation system for treating METH addiction.
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