支持向量机
计算机科学
功能连接
张力(地质)
类型(生物学)
神经科学
物理医学与康复
人工智能
心理学
医学
物理
生物
经典力学
生态学
力矩(物理)
作者
Mengting Li,Shuxian Zhang,Fulei Chu,Yan Zhan,Mengqi Zhao,Zeqi Hao,Linlin Zhan,Jun Ren,Xize Jia
摘要
ABSTRACT Tension‐type headache (TTH) is a primary headache with the highest prevalence. Previous studies have revealed the local brain abnormalities of TTH patients. However, little is known about its brain connectivity disruption. Based on rs‐fMRI data from 33 TTH patients and 30 healthy controls (HCs), static functional connectivity (FC) and dynamic FC were calculated between the default mode network (DMN) and the whole brain. Regions of interest (ROIs)‐wise FC was performed to explore the connectivity pattern of the circuit established by the static and dynamic FC methods. The support vector machine (SVM) model was applied to distinguish the TTH patients from HCs. Compared with the HCs, TTH patients showed increased FC between the left posterior cingulate cortex (PCC) and the left parahippocampal and left middle frontal gyrus (MFG). Decreased dynamic FC was observed between the left PCC and right middle occipital gyrus (MOG), left precuneus, left inferior parietal gyrus (IPG), right median cingulate and paracingulate gyri (DCG) and right supplementary motor area (SMA) in TTH patients. The ROI‐wise FC results showed that left precuneus‐left IPG, left precuneus‐right DCG, and left IPG‐right SMA generated higher FC in TTH patients. SVM obtained a total accuracy of 70.476%, and the area under the curve (AUC) value was 0.658. TTH patients showed abnormal static and dynamic connectivity in multiple brain regions, and abnormal brain activity was also identified within these brain regions. This novel classification model using the brain connectivity could be useful in detecting neuro‐markers for clinical applications in TTH patients.
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