Psychology makes a distinction between motivation-processes that drive an individual to act-and cognition-processes by which information is processed. Despite their separation within Psychology, research on motivation and cognition need to be brought together because there is no cognition in the absence of motivational influences. Furthermore, cognitive neuroscience and clinical neuropsychology suggest that the brain areas responsible for motivational influences are not anatomically or functionally separable from those responsible for information processing. Our proposed work reunites research on motivation and cognition. This goal is crucial for understanding of normal functioning and for our ability to understand and treat cognitive deficits in clinical patients. Our motivational framework (derived from regulatory focus theory) assumes that people's motivational states can be focused on potential gains (a promotion focus) or on potential losses (a prevention focus). Our emphasis in on motivational influences on classification learning. Classification learning provides an ideal testbed for our studies because (a) much is known about the neurobiological systems and cognitive processes involved, (b) these neurobiological systems overlap extensively with those implicated in patients with clinical disorders, and (c) the Pis have over 25 years of combined experience in this field.
The specific aims are to examine the effects of regulatory focus on explicit hypothesis-testing learning and implicit similarity-based learning. We also introduce social focus into the regulatory focus-learning framework. Social motivational factors are likely critical to an understanding of many neuropsychological disorders (e.g., anxiety and depression). The public health implications of this work are many. First, without understanding normal functioning, we cannot determine whether clinical patients (e.g., those with anxiety, depression, schizophrenia, etc) perform poorly because their disorder leads to cognitive impairments, or because it leads to a motivational mismatch. Second, a more detailed understanding of the motivation-learning interface will lead to improved neuropsychological testing measures and rehabilitation training strategies. Little is known about the motivational factors in clinicial disorders and about the motivation-cognition interface. This proposal reunites research on motivation and cognition to better understanding their effects on functioning in clinical populations.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH077708-04
Application #
7800473
Study Section
Cognition and Perception Study Section (CP)
Program Officer
Rossi, Andrew
Project Start
2007-04-20
Project End
2012-03-31
Budget Start
2010-04-01
Budget End
2011-03-31
Support Year
4
Fiscal Year
2010
Total Cost
$300,205
Indirect Cost
Name
University of Texas Austin
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
170230239
City
Austin
State
TX
Country
United States
Zip Code
78712
Reno, James M; Thakore, Neha; Cormack, Lawrence K et al. (2017) Negative Affect-Associated USV Acoustic Characteristics Predict Future Excessive Alcohol Drinking and Alcohol Avoidance in Male P and NP Rats. Alcohol Clin Exp Res 41:786-797
Thakore, Neha; Reno, James M; Gonzales, Rueben A et al. (2016) Alcohol enhances unprovoked 22-28 kHz USVs and suppresses USV mean frequency in High Alcohol Drinking (HAD-1) male rats. Behav Brain Res 302:228-36
Grimm, Lisa R; Lewis, Benjamin; Maddox, W Todd et al. (2016) Stereotype Fit Effects for Golf Putting Nonexperts. Sport Exerc Perform Psychol 5:39-51
Reno, James M; Thakore, Neha; Gonzales, Rueben et al. (2015) Alcohol-preferring P rats emit spontaneous 22-28 kHz ultrasonic vocalizations that are altered by acute and chronic alcohol experience. Alcohol Clin Exp Res 39:843-52
Chandrasekaran, Bharath; Yi, Han-Gyol; Maddox, W Todd (2014) Dual-learning systems during speech category learning. Psychon Bull Rev 21:488-95
Maddox, W Todd; Chandrasekaran, Bharath (2014) Tests of a Dual-systems Model of Speech Category Learning. Biling (Camb Engl) 17:709-728
Chandrasekaran, Bharath; Koslov, Seth R; Maddox, W T (2014) Toward a dual-learning systems model of speech category learning. Front Psychol 5:825
Worthy, Darrell A; Markman, Arthur B; Todd Maddox, W (2013) Feedback and stimulus-offset timing effects in perceptual category learning. Brain Cogn 81:283-93
Maddox, W Todd; Chandrasekaran, Bharath; Smayda, Kirsten et al. (2013) Dual systems of speech category learning across the lifespan. Psychol Aging 28:1042-56
Gorlick, Marissa A; Maddox, W Todd (2013) Priming for performance: valence of emotional primes interact with dissociable prototype learning systems. PLoS One 8:e60748

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