820-nm Transcranial near-infrared stimulation on the left DLPFC relieved anxiety: A randomized, double-blind, sham-controlled study

磁刺激 焦虑 随机对照试验 心理学 背外侧前额叶皮质 脑电图 刺激 医学 前额叶皮质 麻醉 内科学 神经科学 精神科 认知
作者
Huicong Wang,Penghui Song,Yue Hou,Jianghong Liu,Wensi Hao,Shimin Hu,Xiaona Dai,Shuqin Zhan,Ning Li,Peng Mao,Hongxing Wang,Hua Lin,Yuping Wang
出处
期刊:Brain Research Bulletin [Elsevier BV]
卷期号:200: 110682-110682 被引量:6
标识
DOI:10.1016/j.brainresbull.2023.110682
摘要

Generalized anxiety disorder (GAD) is a chronic mood disease associated with abnormal brain network connections, including decreased activity in the left dorsolateral prefrontal cortex (DLPFC). Cortical excitability can be increased with 820-nm transcranial near-infrared stimulation (tNIRS), while transcranial magnetic stimulation with electroencephalography (TMS-EEG) can help evaluate time-varying brain network connectivity. A randomized, double-blind, sham-controlled trial was conducted to assess the efficacy of tNIRS on the left DLPFC and the impact on time-varying brain network connections in GAD patients. A total of 36 GAD patients were randomized to receive active or sham tNIRS for 2 weeks. Clinical psychological scales were assessed before, after, and at the 2-, 4-, and 8-week follow-ups. TMS-EEG was performed for 20 min before and immediately after tNIRS treatment. The healthy controls did not receive tNIRS and only had TMS-EEG data collected once in the resting state. The Hamilton Anxiety Scale (HAMA) scores of the active stimulation group decreased post-treatment compared with the sham group (P = 0.021). The HAMA scores of the active stimulation group at the 2-, 4-, and 8-week follow-up assessments were lower than those before treatment (P < 0.05). The time-varying EEG network pattern showed an information outflow from the left DLPFC and the left posterior temporal region after active treatment. Herein, 820-nm tNIRS targeting the left DLPFC had significant positive effects on therapy for GAD that lasted at least 2 months. tNIRS may reverse the abnormality of time-varying brain network connections in GAD.
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