Over the past decade there has been a growing awareness of the disabling effects of impaired cognition in individuals with schizophrenia. Along with this new awareness has come an increasing emphasis on the importance of developing new treatments that may positively impact these cognitive deficits. During this same period, the cognitive neuroscience field has seen an explosion of technical advances and new knowledge regarding the neural basis of cognition. Sadly, the translation and application of this cutting edge knowledge and paradigm development to new 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 spawned 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, and the validation and psychometric goals when translating such tasks for use in clinical trials contexts. The current application is a logical and needed extension of the CNTRICS initiative that will begin the translation process for paradigms designed to assess four of the constructs identified as being ripe for translation in the first CNTRICS meeting. We have brought together a collaborative """"""""translation"""""""" team that represents significant expertise from the many fields necessary for the success of this endeavor, including both basic and clinical cognitive neuroscientists, psychometricians, and clinical trials specialists. We have chosen to focus 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. By examining multiple mechanisms, we will be able to establish the generality of the translational approach we propose across different levels and types of cognitive mechanisms.
Specific Aim 1 is to validate (in both individuals with schizophrenia and comparison participants) optimized versions of the paradigms that assess our four constructs of interest, as well as to examine the relationship of task performance to clinical and functional outcomes in schizophrenia. By optimization, we mean examining modifications on already validated paradigms that are designed to: 1) minimize task length;2) simplify task administration across multiple sites;3) maximize sensitivity and selectivity in assessing the specific cognitive mechanisms of interest;and 4) enhance reliability and minimize floor and ceiling effects. By validation, we mean ensuring that such optimizations designed to enhance the psychometric properties of the task do not alter its construct validity.
Specific Aim 2 will be to assess and optimize test-retest reliability and practice effects for the task versions validated in Specific Aim 1. PROJECT NARRATIVE 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.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH084828-03
Application #
7841797
Study Section
Special Emphasis Panel (ZMH1-ERB-Z (04))
Program Officer
Kozak, Michael J
Project Start
2008-09-30
Project End
2012-05-31
Budget Start
2010-06-01
Budget End
2012-05-31
Support Year
3
Fiscal Year
2010
Total Cost
$122,594
Indirect Cost
Name
University of Medicine & Dentistry of NJ
Department
Psychiatry
Type
Schools of Medicine
DUNS #
617022384
City
Piscataway
State
NJ
Country
United States
Zip Code
08854
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
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
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
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
Keane, Brian P; Joseph, Jamie; Silverstein, Steven M (2014) Late, not early, stages of Kanizsa shape perception are compromised in schizophrenia. Neuropsychologia 56:302-11
Sheffield, Julia M; Gold, James M; Strauss, Milton E et al. (2014) Common and specific cognitive deficits in schizophrenia: relationships to function. Cogn Affect Behav Neurosci 14:161-74
Owoso, A; Carter, C S; Gold, J M et al. (2013) Cognition in schizophrenia and schizo-affective disorder: impairments that are more similar than different. Psychol Med 43:2535-45
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

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