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Dimensional connectomics of anxious misery, a human connectome study related to human disease: Overview of protocol and data quality

Authors :
Darsol Seok
Nathan Smyk
Marc Jaskir
Philip Cook
Mark Elliott
Tommaso Girelli
J. Cobb Scott
Nicholas Balderston
Joanne Beer
Janet Stock
Walid Makhoul
Ruben C. Gur
Christos Davatzikos
Russell Shinohara
Yvette Sheline
Source :
NeuroImage: Clinical, Vol 28, Iss , Pp 102489- (2020)
Publication Year :
2020
Publisher :
Elsevier, 2020.

Abstract

Disparate diagnostic categories from the Diagnostic and Statistical Manual of Mental Disorders (DSM), including generalized anxiety disorder, major depressive disorder and post-traumatic stress disorder, share common behavioral and phenomenological dysfunctions. While high levels of comorbidity and common features across these disorders suggest shared mechanisms, past research in psychopathology has largely proceeded based on the syndromal taxonomy established by the DSM rather than on a biologically-informed framework of neural, cognitive and behavioral dysfunctions. In line with the National Institute of Mental Health’s Research Domain Criteria (RDoC) framework, we present a Human Connectome Study Related to Human Disease that is intentionally designed to generate and test novel, biologically-motivated dimensions of psychopathology. The Dimensional Connectomics of Anxious Misery study is collecting neuroimaging, cognitive and behavioral data from a heterogeneous population of adults with varying degrees of depression, anxiety and trauma, as well as a set of healthy comparators (to date, n = 97 and n = 24, respectively). This sample constitutes a dataset uniquely situated to elucidate relationships between brain circuitry and dysfunctions of the Negative Valence construct of the RDoC framework. We present a comprehensive overview of the eligibility criteria, clinical procedures and neuroimaging methods of our project. After describing our protocol, we present group-level activation maps from task fMRI data and independent components maps from resting state data. Finally, using quantitative measures of neuroimaging data quality, we demonstrate excellent data quality relative to a subset of the Human Connectome Project of Young Adults (n = 97), as well as comparable profiles of cortical thickness from T1-weighted imaging and generalized fractional anisotropy from diffusion weighted imaging. This manuscript presents results from the first 121 participants of our full target 250 participant dataset, timed with the release of this data to the National Institute of Mental Health Data Archive in fall 2020, with the remaining half of the dataset to be released in 2021.

Details

Language :
English
ISSN :
22131582
Volume :
28
Issue :
102489-
Database :
Directory of Open Access Journals
Journal :
NeuroImage: Clinical
Publication Type :
Academic Journal
Accession number :
edsdoj.b774de28a1784a69a3de9d15179717b4
Document Type :
article
Full Text :
https://doi.org/10.1016/j.nicl.2020.102489