The R-fMRI Maps Project - Consortium for Depression and Bipolar Disorders (RMP-CDBD)

Submitted by YAN Chao-Gan on
Consortium for Depression and Bipolar Disorders (RMP-CDBD)
 
Clinical diagnosis in mental disorders, different from most of medicine, is still restricted to observable signs and subjective symptoms. Clinicians categorize patients with depression, bipolar disorder or other types of mental disorders through their empathic listening and well-honed observational skills (Insel & Cuthbert, 2015, Science, 348, 499-500). However, mental disorders are heterogeneous syndromes, i.e., combinations of symptoms in the hundreds. Beyond subtyping patients on the basis of co-occurring clinical symptoms, subtyping patients based on their shared signatures of brain dysfunction (i.e., neurophysiological subtypes, or biotypes) is a crucial way to enhance the diagnosis and treatment of mental disorders. Recently, Drysdale and colleagues (2016, Nat Med, nm4246) reported the successful use of resting-state brain connectivity biomarkers to define neurophysiological subtypes of depression. The key for neuroscience-based biotypes of mental disorders, as called for by the NIMH RDoC Project, is to accumulate big brain imaging data across a large variety of psychiatric illnesses. 
 
Data-sharing initiatives (e.g., grassroots efforts such as FCP/INDI, openfMRI, and fMRIDC, and coordinated efforts such as ADNI, HCP, NDAR, and PING) are enabling future efforts to biotype mental disorders. However, sharing raw data requires intensive coordinating efforts, huge manpower demands and large-amounts of data storing/management facilities. Furthermore, sharing raw data is mired with privacy concerns arising from the possibility of being able to identify participants from high dimensional raw data. These concerns, together with the demands of data organization and the limit of large data uploading, is impeding wider imaging community sharing of valuable brain imaging datasets.
 
Here, based on the success of DPABI/DPARSF (which has been cited more than 900 times and was the second leading software (29%) used in the R-fMRI literature according to Waheed et al., 2016, Brain Connect, 6(9):663-668), we designed the R-fMRI Maps Project (RMP) to address the above concerns by only sharing the final R-fMRI indices, which only need light data storing/uploading requirements and removes the privacy concerns regarding raw data. The project provides a convenient data organizer GUI integrated in DPABI/DPARSF to facilitate efficient data organization. Furthermore, by sharing the processed R-fMRI indices, the project removes the barriers of computational resources as well as analytic knowledge for the users, thus allowing a wider scientific community (especially machine learning experts) to join in the endeavor of understanding mental disorders.
 
The initial effort of the RMP is the Consortium for Depression and Bipolar Disorders (RMP-CDBD). We identified 118 research articles which utilized DPABI/DPARSF to process their depression and bipolar disorder R-fMRI data, and invited the corresponding authors to join the RMP-CDBD. We are asking all consortium members to contribute their DPARSF-processed R-fMRI maps (without any individually identifiable data) to the Consortium. Founding consortium members will have initial exclusive access to all the shared R-fMRI map data, and will be free to perform their own research based on this unique resource. All founding consortium members (including up to 5 co-authors from each center) will be included as co-authors on an announcing consortium paper which will aim to analyze all the R-fMRI maps together. We anticipate that such a paper, presenting a reliable and reproducible multi-site international collaborative study on depression and bipolar disorders will have high impact, which will be further enhanced by our making the Consortium dataset openly accessible to the entire scientific community one year after publication of the announcing paper. 
 
We sincerely hope you will join us in this exciting endeavor to improve the utility of R-fMRI for the diagnosis and treatment of depression and bipolar disorders, if you are doing related research. By sharing tens or hundreds of R-fMRI maps, you will have access to thousands of R-fMRI maps. Up to now, there were tens of centers have agreed to join the RMP-CDBD as founding consortium members. 
 
Please fill the attached form and email Dr. Chao-Gan Yan if you would like to join the RMP-CDBD.
 
Best wishes and hope you have a prosperous 2017!
 
Chao-Gan YAN, Ph.D.
Professor, Principal Investigator, Deputy Director, MRI Research Center, Institute of Psychology, Chinese Academy of Sciences
Xi-Nian ZUO, Ph.D.
Professor, Principal Investigator, Director, MRI Research Center, Institute of Psychology, Chinese Academy of Sciences
Yu-Feng ZANG, M.D.
Professor, Deputy Director, Center for Cognition and Brain Disorders, Hangzhou Normal University
 
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Consortium Form.docx 46.65 KB