Identification of the pathogenic mechanism of mental and neurological disorders through acquisition and analysis of cerebral MRI-scan images and clinical data, etc.
M.D., Ph.D., Professor, Graduate School of Medicine, The University of Tokyo
The onset of many psychiatric disorders usually occurs in adolescents and young adults (AYA). The substrates of brain maturation in the AYA generation largely remain undiscovered. In our current research project, we will acquire longitudinal MRI data of patients with schizophrenia, those with developmental disorders, and typical developing individuals using the Human Connectome Project (HCP) protocol. In addition, we will share MRI data with our international collaborators. Through these approaches, we aim to elucidate mechanisms regarding the onset of psychiatric disorders in the AYA generation and to identify brain-circuit-based biomarkers that will be useful in diagnosis and predicting treatment outcomes.
M.D., Ph.D., Professor, Graduate School of Biomedical Medical Sciences, Hiroshima University
We obtain longitudinal MRI data and the associated clinical data targeting mood disorders (depression and bipolar disorders), anxiety disorders, obsessive-compulsive disorders, schizophrenia, subthreshold depression and healthy individuals in adulthood. By using this data and applying AI technology to the analyses, we propose a method to distinguish between bipolar disorder and depression, a method for predicting responses to treatment (clinical course) and biotypes based on the five diseases. We also contribute to the elucidation of the pathogenic mechanism by assessing MRI images showing changes from subthreshold depression to depression.
M.D., Ph.D., Director, Department of Advanced Neuroimaging, Integrative Brain Imaging Center, National Center of Neurology and Psychiatry
Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the most common neurodegenerative disorders involving the elderly population. In this multi-center study, we aim to collect MRI data from participants with either AD or PD, “super-healthy” elderly people defined as being at risk of AD or PD, and intermediate states such as mild cognitive impairment (MCI). Simultaneously, we will develop an MRI reference panel representing the healthy elderly population derived from a mega-scale cohort study including 10,000 participants. By combining a cutting-edge MRI analysis of the multi-center data and the reference panel, we will clarify the similarities and differences of the neural circuits responsible for AD and PD.