NeuroCLIP: A Multimodal Contrastive Learning Method for rTMS-treated Methamphetamine Addiction Analysis
Wang, Chengkai, Wu, Di, Liao, Yunsheng, Zheng, Wenyao, Zeng, Ziyi, Gao, Xurong, Wu, Hemmings, Zhu, Zhoule, Yang, Jie, Zhong, Lihua, Cheng, Weiwei, Chen, Yun-Hsuan, Sawan, Mohamad
–arXiv.org Artificial Intelligence
-- Methamphetamine dependence poses a significant global health challenge, yet its assessment and the evaluation of treatments like repetitive transcranial magnetic stimulation (rTMS) frequently depend on subjective self-reports, which may introduce uncertainties. While objective neuroimaging modalities such as electroen-cephalography (EEG) and functional near-infrared spectroscopy (fNIRS) offer alternatives, their individual limitations and the reliance on conventional, often hand-crafted, feature extraction can compromise the reliability of derived biomarkers. To overcome these limitations, we propose NeuroCLIP, a novel deep learning framework integrating simultaneously recorded EEG and fNIRS data through a progressive learning strategy. This approach offers a robust and trustworthy biomarker for methamphetamine addiction. Validation experiments show that NeuroCLIP significantly improves discriminative capabilities among the methamphetamine-dependent individuals and healthy controls compared to models using either EEG or only fNIRS alone. Furthermore, the proposed framework facilitates objective, brain-based evaluation of rTMS treatment efficacy, demonstrating measurable shifts in neural patterns towards healthy control profiles after treatment. Critically, we establish the trustworthiness of the multimodal data-driven biomarker by showing its strong correlation with psychometrically validated craving scores. These findings suggest that biomarker derived from EEG-fNIRS data via NeuroCLIP offers enhanced robustness and reliability over single-modality approaches, providing a valuable tool for addiction neuroscience research and potentially improving clinical assessments. Ziyi Zeng is also with the School of Data Science, Xiamen University Malaysia, Selangor 43900, Malaysia. Hemmings Wu and Zhoule Zhu are with Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, China. Lihua Zhong is with the Department of Education and Correction, Zhejiang Gongchen Compulsory Isolated Detoxification Center, Hangzhou 310011, China. Weiwei Cheng is with Zhejiang Liangzhu Compulsory Isolated Detoxification Center, Hangzhou 311115, China. ETHAMPHET AMINE addiction represents a significant and growing public health concern globally.
arXiv.org Artificial Intelligence
Jul-29-2025
- Country:
- Asia
- China
- Fujian Province > Xiamen (0.24)
- Zhejiang Province > Hangzhou (0.64)
- Malaysia (0.44)
- China
- Europe
- North America > United States (0.28)
- Asia
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