Multi-modal MRI Mapping Aberrant Neural Circuits of Treatment-resistant Depression (TRD) at Fine-grained Subregional Scale
Abstract: Treatment-resistant depression (TRD) is one subtype of depression, which is with the greatest difficulty in treatment, the most difficult of social function recovery, and the heaviest disease burden. Currently, there is lack of objective standard to recognize TRD from non-TRD early. There is also lack of quantitative, objective biological indicators to assess the treatment effects on TRD. Therefore, understanding the abnormal mechanism of neural circuits in TRD and finding effective objective biomarkers are urgently needed for basic research and clinical practice of depression disorder. This project will use multimodal MRI datasets acquired from different clinical diagnosis and treatment phases to perform the following three studies: 1) to map the abnormal brain sub-regions and related neural circuits of TRD at a more fine-grained subregional scale; 2) By fusing multimodality MRI findings and extracting effective features, to identify the potential imaging biomarkers for early diagnosis and treatment assessment of TRD based on machine learning; 3) Based on the above findings, we will observe the structural and functional changes of TRD related neural circuits during repetitive TMS (rTMS) treatment, and try to optimize the precise stimulation localization of rTMS. Through the above studies, the current project will provide a scientific basis for diagnosis, treatment methods, and will provide potential biomarker for the clinical treatment and prognosis of TRD.
Keywords: treatment-resistant depression; multi-modal MRI; brain parcellation; neural circuit; Brain connectivity
Contact:
FAN Lingzhong
E-mail: lzfan@ia.ac.cn