[Graph convolution-based brain network analysis of visual mismatch negativity in adults with attention-deficit/hyperactivity disorder].

内容摘要

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Adults with ADHD continue to exhibit deficits in attention and executive function, whereas the neural mechanisms underlying visual mismatch negativity (vMMN)-related processing remain unclear. This study investigated the functional brain connectivity characteristics of adults with ADHD by combining standardized low-resolution brain electromagnetic tomography (sLORETA), phase-locking value (PLV) analysis, and a graph convolutional network (GCN) based on a visual Oddball paradigm that elicited vMMN responses. Electroencephalography (EEG) data were collected from 10 adults with ADHD and 10 healthy controls using a 128-channel recording system. Source signals from 68 brain regions defined by the Desikan-Killiany atlas were reconstructed using sLORETA. Functional connectivity networks were constructed using PLV and subsequently classified by the GCN model. The results showed that the accuracy, precision, recall, and F1-score of the GCN model under five-fold cross-validation were (85.13 ± 1.94)%, (80.58 ± 2.08)%, (86.04 ± 1.76)%, and (83.21 ± 1.89)%, respectively. Node feature weights and classification contribution analyses identified the lingual gyrus, calcarine fissure and surrounding cortex, parahippocampal gyrus, and precuneus as highly discriminative brain regions. These findings indicate that adults with ADHD exhibit abnormal functional connectivity patterns during vMMN-related processing and provide evidence for the auxiliary identification and neural mechanism investigation of ADHD. 注意缺陷多动障碍（ADHD）是一种常见的神经发育障碍，成人患者仍存在注意缺陷和执行功能障碍，但其视觉失匹配负波（vMMN）相关脑功能机制尚未明确。本文基于视觉Oddball范式诱发vMMN，结合标准化低分辨率脑电磁断层成像（sLORETA）源定位、相位锁定值（PLV）功能连接分析与图卷积神经网络（GCN），研究成人ADHD患者的脑功能连接特征。采集10名成人ADHD患者和10名健康对照组（HC）的128通道脑电数据，利用sLORETA获得Desikan-Killiany模板68个脑区的源信号；基于脑区信号计算PLV构建功能连接网络，并输入GCN进行分类。结果表明，在五折交叉验证下，GCN模型准确率、精确率、召回率和F1分数分别为（85.13 ± 1.94）%、（80.58 ± 2.08）%、（86.04 ± 1.76）%和（83.21 ± 1.89）%。结合节点特征权重与分类贡献度分析发现，舌回、距状裂及其周围皮层、海马旁回和楔前叶等脑区具有较高判别能力。研究结果表明，成人ADHD患者在vMMN相关加工过程中存在异常脑功能连接模式，可为其辅助识别及神经机制研究提供参考。.