Altered brain activity and functional connectivity in psychogenic erectile dysfunction: Combining findings from...

Psychogenic erectile dysfunction (pED) is often accompanied by abnormal brain activities. This study aimed to develop an automaticclassifier to distinguish pED from healthy controls (HCs) by identified brain-basedcharacteristics. Resting-state functional magnetic resonance imaging data were acquired from 45 pED patients and 43 HCs. Regional homogeneity (ReHo) and functional connectivity (FC) values were calculated and compared between groups. Moreover, based on altered ReHo and FC values, support vector machine (SVM) classifier, incorporating recursive feature elimination (RFE), an SVM-RFE diagnostic model was established using leave-one-out cross-validation. Patients demonstrated reduced ReHo values in the left middle temporal gyrus (had decreased FC values with the left medial superior frontal gyrus and cuneus), orbital part of inferior frontal gyrus (had decreased FC values within the same region), triangular part of inferior frontal gyrus, anterior cingulate gyrus (had decreased FC values with the left inferior temporal gyrus, anterior cingulate gyrus, cuneus and right supplementary motor area) and middle frontal gyrus. The right calcarine fissure displayed increased ReHo values. The diagnostic model demonstrated excellent performance, achieving an accuracy rate of 90.80%. This study identified altered regional activity and FC in specific brain regions of pED patients, which might be related to the development of pED. The application of machine learning confirmed the distinctive characteristics of these functional changes in the brain. The high accuracy of our diagnostic model suggested a promising direction for developing objective diagnostic tools for psychological disorders.