This is a competitive revision in response to NOT-OD-09-058, the ARRA call for Competitive Supplement Applications. In the past decade there has been a growing awareness of the disabling effects of impaired cognition in individuals with schizophrenia and the importance of developing new treatments that target cognitive deficits. During this same period, the cognitive neuroscience field has seen an explosion of new knowledge regarding the neural basis of cognition. The application of this new knowledge to drug development in schizophrenia has lagged significantly behind overall progress in cognitive neuroscience, in large part due to the lack of data on the measurement properties of tasks used in cognitive neuroscience. This concern led to the Cognitive Neuroscience Research To Improve Cognition in Schizophrenia (CNTRICS) initiative, which conducted a series of conferences designed to develop consensus on the constructs and paradigms from cognitive neuroscience that are ripe for translation for use in clinical trials contexts. We were recently funded to start this translation process (Cognitive Neuroscience Task Reliability &Clinical Applications (CNTRACs) Consortium."""""""") for behavioral paradigms. We brought together a collaborative team that represents significant expertise from the many fields necessary for the success of this endeavor. We are focusing on four constructs that span both early (gain control and visual integration in perception) and higher-level (goal maintenance, relational encoding and retrieval) components of human cognitive processing. Is this competitive revision we will extend this work in a highly critical and significant direction that the field has identified as a growing need - the development of well validated, and reliable functional neuroimaging paradigms that can serve as biomarkers for predicting and assessing drug and intervention response to treatments designed to enhance cognition. This focus meets one of the key topic areas for Competitive Supplements identified by the NIMH, namely Biomaterials and Biological Measures for the Study of Mental Disorders, which includes """"""""Systematically collecting and analyzing biological measures (e.g., genetic polymorphisms, brain imaging indexes), which could be used, also in combination with clinically derived variables, to identify predictors of outcome, moderators of treatment response and adverse effects, or mediators and patterns of treatment effects."""""""" The end goal for these expanded aims will be to provide the field with: 1) easy to use imaging paradigms of these three cognitive functions that: 2) have been optimized for use in a clinical trials context (efficient, reliable, robust);while 3) maintaining their validity as specific measures of the cognitive and neural processes of interest. We believe that it is feasible to complete this added Aim in the time frame of the ARRA announcement, given that we have an established infrastructure. This set of collaborative R01 proposals meet the goals of the ARRA stimulus by providing for funding for 9 new positions, 3 positions that would allow us to retain staff that would otherwise need to be let go, and 1 position that we can increase from part to full time.

Public Health Relevance

This project has high relevance for public health by significantly improving our ability to translate paradigms developed into the basic cognitive neuroscience literature for use in clinical trials aimed at improving cognition in schizophrenia. Cognitive deficits in schizophrenia are a major predictor of functional outcome in this debilitating illness. Thus, we need to improve our methods for detecting and enhancing cognitive function in schizophrenia in order to help individuals with this illness lead more productive and fulfilling lives.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Study Section
Special Emphasis Panel (ZMH1-ERB-Z (A1))
Program Officer
Kozak, Michael J
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Washington University
Schools of Arts and Sciences
Saint Louis
United States
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Barch, Deanna M; Carter, Cameron S; Gold, James M et al. (2017) Explicit and implicit reinforcement learning across the psychosis spectrum. J Abnorm Psychol 126:694-711
Ermel, Julia; Carter, Cameron S; Gold, James M et al. (2017) Self versus informant reports on the specific levels of functioning scale: Relationships to depression and cognition in schizophrenia and schizoaffective disorder. Schizophr Res Cogn 9:1-7
Luby, Joan L; Belden, Andy C; Jackson, Joshua J et al. (2016) Early Childhood Depression and Alterations in the Trajectory of Gray Matter Maturation in Middle Childhood and Early Adolescence. JAMA Psychiatry 73:31-8
Poppe, Andrew B; Barch, Deanna M; Carter, Cameron S et al. (2016) Reduced Frontoparietal Activity in Schizophrenia Is Linked to a Specific Deficit in Goal Maintenance: A Multisite Functional Imaging Study. Schizophr Bull 42:1149-57
Lopez-Garcia, Pilar; Lesh, Tyler A; Salo, Taylor et al. (2016) The neural circuitry supporting goal maintenance during cognitive control: a comparison of expectancy AX-CPT and dot probe expectancy paradigms. Cogn Affect Behav Neurosci 16:164-75
Barch, Deanna M; Gotlib, Ian H; Bilder, Robert M et al. (2016) Common Measures for National Institute of Mental Health Funded Research. Biol Psychiatry 79:e91-6
Silverstein, Steven M; Harms, Michael P; Carter, Cameron S et al. (2015) Cortical contributions to impaired contour integration in schizophrenia. Neuropsychologia 75:469-80
Ragland, J Daniel; Ranganath, Charan; Harms, Michael P et al. (2015) Functional and Neuroanatomic Specificity of Episodic Memory Dysfunction in Schizophrenia: A Functional Magnetic Resonance Imaging Study of the Relational and Item-Specific Encoding Task. JAMA Psychiatry 72:909-16
Sheffield, Julia M; Repovs, Grega; Harms, Michael P et al. (2015) Fronto-parietal and cingulo-opercular network integrity and cognition in health and schizophrenia. Neuropsychologia 73:82-93
Strauss, Milton E; McLouth, Christopher J; Barch, Deanna M et al. (2014) Temporal stability and moderating effects of age and sex on CNTRaCS task performance. Schizophr Bull 40:835-44

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