Among the major mental illnesses of early adulthood, people with schizophrenia spectrum disorders (SSDs) (i.e., schizophrenia, schizoaffective disorder, schizophreniform disorder) exhibit a continuum of impairment in social functioning. Treatment is minimally effective, and impairments tend to persist. Knowledge on the neurobiology of social cognitive (SCog) process impairment will foster therapeutic discovery. At each of our sites, pilot data show that people with SSDs who are among the most socially impaired have a low likelihood of functional recovery and manifest impairment in discrete brain circuits that are known to be involved in the neurobiology of SCog processes in healthy individuals. Leveraging our pilot data, which is consistent across three sites, and the expertise of our group in SSD research related to phenomenology, outcomes, multi-site neuroimaging, and treatment innovation, we propose to use the Research Domain Criteria (RDoC) investigational framework in people with SSDs to comprehensively and definitively delineate the neurobiology of SCog process impairment. Our approach will employ advanced structural and functional neuroimaging approaches to identify the neural circuitry (along a continuum from healthy controls to people with SSDs) that predict impairments in SCog processes and concomitant social function. We plan to use advanced neuroimaging and network analysis approaches including: 1) gray matter morphology approaches to map the thickness of the cortex and examine cortical thickness network topology, 2) DTI acquisition and analytic approaches to map white matter circuits in the brain; and 3) fMRI-based approaches to engage these same circuits, including functional connectivity measures to obtain detailed measures of circuit function. We will then use our group's expertise in sophisticated multivariate neuroimaging statistics (partial least squares), to extract dimensional features relating brain structure ->brai function -> behavior and provide a comprehensive understanding of the neurobiology of social processes from circuit to behavior across normal and abnormal (SSDs) domains. Our proposal is modeled directly within the RDoC framework; specifically, we are using a Matrix of Analysis as our guiding structure to identify the neurobiology of SCog process constructs from normal controls across the entire schizophrenia spectrum. We anticipate identifying substantially abnormal brain-behavior relationships starting from the level of circuit characterization. The ultimate goal of our collaborative team is to identify new therapeutic targets for the treatment of social impairments by identifying the underlying neural circuitry and pathophysiology of impaired social function.

Public Health Relevance

Using advanced neuroimaging and multivariate analytic approaches we will identify impairments in brain circuit structure and function that predict social cognitive process impairment in healthy controls and people with schizophrenia spectrum disorders (SSDs). Our proposed study will identify the full range of dimensional brain- behavior relationships starting from the level of circuit characterization through to social cognitive performance and social function. Our group's ultimate goal is to identify new therapeutic targets for the treatment of social impairments in the SSDs (and other psychiatric disorders) through the delineation of their underlying neural circuitry and pathophysiology.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH102318-05
Application #
9459994
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Morris, Sarah E
Project Start
2014-07-16
Project End
2019-03-31
Budget Start
2018-04-01
Budget End
2019-03-31
Support Year
5
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Maryland Baltimore
Department
Psychiatry
Type
Schools of Medicine
DUNS #
188435911
City
Baltimore
State
MD
Country
United States
Zip Code
21201
Chavez, Sofia; Viviano, Joseph; Zamyadi, Mojdeh et al. (2018) A novel DTI-QA tool: Automated metric extraction exploiting the sphericity of an agar filled phantom. Magn Reson Imaging 46:28-39
Stefanik, Laura; Erdman, Lauren; Ameis, Stephanie H et al. (2018) Brain-Behavior Participant Similarity Networks Among Youth and Emerging Adults with Schizophrenia Spectrum, Autism Spectrum, or Bipolar Disorder and Matched Controls. Neuropsychopharmacology 43:1180-1188
Kochunov, Peter; Dickie, Erin W; Viviano, Joseph D et al. (2018) Integration of routine QA data into mega-analysis may improve quality and sensitivity of multisite diffusion tensor imaging studies. Hum Brain Mapp 39:1015-1023
Viviano, Joseph D; Buchanan, Robert W; Calarco, Navona et al. (2018) Resting-State Connectivity Biomarkers of Cognitive Performance and Social Function in Individuals With Schizophrenia Spectrum Disorder and Healthy Control Subjects. Biol Psychiatry 84:665-674
Carpenter Jr, William T; Buchanan, Robert W (2017) Negative Symptom Therapeutics. Schizophr Bull 43:681-682
Hawco, Colin; Kovacevic, Natasa; Malhotra, Anil K et al. (2017) Neural Activity while Imitating Emotional Faces is Related to Both Lower and Higher-Level Social Cognitive Performance. Sci Rep 7:1244