Scholarlink

<p>Non-suicidal self-injury (NSSI) has a huge impact on the physical and mental health of adolescents, and the changes in the brain network functional connectivity pattern of NSSI are still unclear. Electroencephalogram (EEG) has been widely used in the study of brain function in mental disorders due to its high temporal resolution. Thus, it is of great significance to investigate the brain network functional connectivity (FC) and network characteristics changes in NSSI adolescents. Fifty NSSI adolescents with depressive episodes and 25 healthy controls (HCs) were assessed using eye-open resting state EEG signals and clinical scales. Phase locking value (PLV), weighted Phase Lag Index (wPLI), and graph theory analysis and machine learning analysis were combined to explore the brain functional connectivity and topological properties of adolescents with NSSI. Compared with HCs, adolescents with NSSI revealed significantly decreased connectivity in the alpha band based on the wPLI/PLV-derived network, and significantly increased connectivity and network efficiency in the theta bands in PLV-derived brain network. Reduced characteristic path length and enhanced clustering coefficient/global efficiency/local efficiency were found in the delta/theta band for PLV-derived network, which related to the clinical scale score (i.e. Toronto Alexithymia Scale). The best classification performance was achieved using comprehensive features (combined PLV- and wPLI-derived) and logistic regression classifier. Overall, these findings present novel evidence to understand NSSI neuropathological mechanisms and provide potential targets for NSSI treatment.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Altered functional brain network in adolescents with non-suicidal self-injury: a resting-state EEG study

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月16日

查看全文
  • Liqin Zheng,
  • Na Du,
  • Shusheng Bao,
  • Yufeng Deng,
  • Zedong Wang,
  • Linqi Chen,
  • Zhanjiang Sun,
  • Chunya Li,
  • Ya’nan Li,
  • Yu Xiao,
  • Jia Chen,
  • Yunge Li,
  • Kai Chen,
  • Tao Zhang,
  • Hesong Wang,
  • Tao Zhang

摘要

Non-suicidal self-injury (NSSI) has a huge impact on the physical and mental health of adolescents, and the changes in the brain network functional connectivity pattern of NSSI are still unclear. Electroencephalogram (EEG) has been widely used in the study of brain function in mental disorders due to its high temporal resolution. Thus, it is of great significance to investigate the brain network functional connectivity (FC) and network characteristics changes in NSSI adolescents. Fifty NSSI adolescents with depressive episodes and 25 healthy controls (HCs) were assessed using eye-open resting state EEG signals and clinical scales. Phase locking value (PLV), weighted Phase Lag Index (wPLI), and graph theory analysis and machine learning analysis were combined to explore the brain functional connectivity and topological properties of adolescents with NSSI. Compared with HCs, adolescents with NSSI revealed significantly decreased connectivity in the alpha band based on the wPLI/PLV-derived network, and significantly increased connectivity and network efficiency in the theta bands in PLV-derived brain network. Reduced characteristic path length and enhanced clustering coefficient/global efficiency/local efficiency were found in the delta/theta band for PLV-derived network, which related to the clinical scale score (i.e. Toronto Alexithymia Scale). The best classification performance was achieved using comprehensive features (combined PLV- and wPLI-derived) and logistic regression classifier. Overall, these findings present novel evidence to understand NSSI neuropathological mechanisms and provide potential targets for NSSI treatment.