Repetitive TMS-based Identification of Methamphetamine-Dependent Individuals Using EEG Spectra

Personal use is permitted, but republication/redistribution requires IEEE permission. Abstract -- 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 gam ma 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 distinguishi ng 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. Introduction DDICTION is defined as an overwhelming urge to use a particular substance or engage in a specific behavior, often leading to harmful consequences. Addiction to one such substance, methamphetamine (METH), is termed as methamphetamine use disorder or dependence (MUD); this has been listed as a serious public health concern [1] . METH is a highly addictive synthetic central nervous system stimulant. METH users experience positive feelings such as euphoria, increased self -confidence, and heightened energy levels in the short-term following use. This study was supported by Westlake University, Zhejiang Key R&D Program ( Grant No. 2021C03002) and "Pioneer" and "Leading Goose" R&D Program of Zhejiang (Grant No. 2024C03040). Z. Zeng and Y.- H. Chen contributed equally and are the co-first authors. There is currently no approved pharmacotherapy treatment available for MUD [4]; however, behavioral interv entions have proved effective [5] . One commo n type of behavioral intervention for MUD is abstinence-based treatment in rehabilitation centers, but relapse rates among MUD individuals remain substantial. A study examining youth using ketamine and METH suggests that METH users are more prone to relaps e than those in the ketamine group [6] .