This exploration aims to solve the problems of imperfect psychological health education system and poor educational effects on college students. Here, ideological and political education is integrated with mental health education to investigate the role of collaborative intervention in guiding college students to resist negative emotions. First, an overview is offered of research on ideological and political education, mental health education, and negative emotions by the literature survey method. Moreover, a comprehensive investigation is also conducted on research objects, through the questionnaire, to understand the current situation of negative emotions of college students. And finally, an intervention experiment is taken on the negative emotions of college students by combining ideological and political education with mental health education. The results show that after 10 weeks of intervention experiment by combining ideological and political education with mental health education, there are significant differences in depression, negative emotions, somatization symptoms, and interpersonal problems between the treatment group and the control group (P < 0.01). Besides, there are significant differences in depression, negative emotions, somatization symptoms, and interpersonal problems between sophomores in the treatment group and the control group (P < 0.01). Moreover, there are significant differences in depression, negative emotions, somatization symptoms, and interpersonal problems between male participants in the treatment group and the control group (P < 0.01). In summary, ideological and political education integrated with mental health education has a positive guidance effect on the negative emotions of college students, greatly improving the negative emotions of the students, helping the students to regulate their emotions, and benefiting their study and life a lot. The purpose of integrating ideological and political education with mental health education is to provide reference for refining the mental health education system of college students and strengthening the positive guidance of negative emotions of college students.

This study was aimed at the application of a deep graph convolutional neural network (GCNN) in cerebral magnetic resonance imaging (MRI) analysis of patients with depression and the effect of Western medicine combined with music therapy in the treatment of depression. A total of 120 patients with different degrees of depression were divided into the test group with 60 cases (western medicine+music therapy) and the control group with the other 60 cases (western medicine only). All these patients underwent MRI scanning. On the basis of the deep GCNN, an optimized algorithm (O-GCNN) for depression recognition was proposed. It was found that the accuracy, sensitivity, and specificity for classification of the O-GCNN algorithm were significantly higher than those of the convolutional neural network (CNN) model, the back propagation (BP) algorithm, and the forward propagation (FP) algorithm ([Formula: see text]). The scores of somatization, interpersonal sensitivity, depression, psychoticism, and anxiety of the test group were significantly lower than those of the control group during and after treatment ([Formula: see text]). The scores of the Self-rating Depression Scale (SDS) and Hamilton depression scale (HAMD) of patients in the test group were also significantly lower than those in the control group during and after treatment; the differences were statistically significant ([Formula: see text]). The values of left hippocampal regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuation (fALFF) of patients in the test group were significantly lower than those in the control group during and after treatment ([Formula: see text]). The 24-h urinary free cortisol (UFC) content in the test group was remarkably lower during and after treatment, and the difference was statistically significant ([Formula: see text]). The results showed that the improved depression recognition algorithm O-GCNN proposed in this work had a high application value in the auxiliary diagnosis of depression. Music therapy combined with Western medicine treatment can more effectively improve the anxiety and negative mental state of patients with depression and promote the improvement of patients’ conditions.