Clinical neuroscience is on the verge of a revolution. Traditional conceptualizations of disorders based on phenomenology are increasingly recognized as limited, but we have lacked a clear path toward a more valid approach. The Research Domain Criteria (RDoC) initiative has identified one such pathway;the examination of components of behavior linked to known neural systems that form the basis of core dimensions of psychopathology. This competing renewal will provide new insights into the cognitive and emotional processes underlying core symptom dimensions in major mental illness and provide a new set of valid and reliable tools to facilitate the aims of RDoC and Objective 1.4 of the NIMH Strategic Plan: "Develop new ways of classifying disorders based on dimensions of observable behaviors and brain functions." This application will utilize the CNTRaC's infrastructure and expertise to optimize measures of WM capacity, positive and negative reinforcement learning (both implicit and explicit) and reversal learning, and then apply them together with previously validated measures.
Specific Aim 1 is to validate (in individuals with schizophrenia, schizoaffective disorder and bipolar disorder, as well as comparison participants) optimized versions of the paradigms that assess our six constructs of interest, as well as to examine the relationship of task performance to clinical and functional outcomes in psychosis.
Specific Aim 2 will be to assess and optimize test-retest reliability and practice effects for the task versions validated in Specific Aim 1.
Specific Aim 3 will be to use these optimized measures of working memory capacity and reinforcement learning, along with our previously optimized measures of WM goal maintenance, relational encoding and retrieval, and visual integration to examine the relationship between performance on these measures of core constructs and dimensions of psychopathology across diagnoses (including medicated and un-medicated individuals with schizophrenia and schizoaffective disorders, as well as individuals with bipolar disorder). We hypothesize that impairments in the dorsal frontal- parietal and frontal-temporal systems supporting WM (capacity and goal maintenance) and relational encoding/retrieval contribute to disorganization symptoms and functional impairment and that these impairments and relationships cut across affective and non-affective disorder boundaries, forming a core dimension that helps explain the overlap in function and neurobiology across disorders. We also hypothesize that impairments in orbital frontal-striatal systems supporting reinforcement and reversal learning contribute to the negative symptoms of anhedonia/amotivation, which also cut across diagnostic boundaries. However, we hypothesize that anhedonia/amotivation may involve different aspects of reward processing and circuitry in primary mood versus non-mood disorders with our selection of measures motivated to test this hypothesis. We hypothesize that impaired visual integration, which is thought to reflect reduced horizontal and recurrent feedback, will be related to disorganized symptoms across disorders, but will not relate to mood pathology.

Public Health Relevance

This project has high relevance for public health by developing tools necessary for reliable and valid assessment of core cognitive and affective processes in psychotic and mood disorders, and then using them to provide new insights into how these processes contribute to symptoms and functional impairment. This will provide insights that will allow us to develop more effective treatments.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Special Emphasis Panel (ZMH1-ERB-X (04))
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Kozak, Michael J
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University of Maryland Baltimore
Schools of Medicine
United States
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Poppe, Andrew B; Wisner, Krista; Atluri, Gowtham et al. (2013) Toward a neurometric foundation for probabilistic independent component analysis of fMRI data. Cogn Affect Behav Neurosci 13:641-59
Ragland, John D; Ranganath, Charan; Barch, Deanna M et al. (2012) Relational and Item-Specific Encoding (RISE): task development and psychometric characteristics. Schizophr Bull 38:114-24
Henderson, Dori; Poppe, Andrew B; Barch, Deanna M et al. (2012) Optimization of a goal maintenance task for use in clinical applications. Schizophr Bull 38:104-13
Gold, James M; Barch, Deanna M; Carter, Cameron S et al. (2012) Clinical, functional, and intertask correlations of measures developed by the Cognitive Neuroscience Test Reliability and Clinical Applications for Schizophrenia Consortium. Schizophr Bull 38:144-52