Psychology typically makes a conceptual distinction between motivation -- processes that drive an individual to act -- and cognition -- processes by which information is processed. Despite the separation of these factors within Psychology, there are good reasons to believe that research on motivation and cognition need to be brought together more closely. Because motivation drives action, 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. The goal of our proposed work is to reunite research on motivation and cognition. This goal is crucial both for our understanding of normal functioning and, more importantly for the mission of NIMH, for our ability to understand and treat cognitive deficits in patients with disorders. Our motivational framework, which derives from regulatory focus theory, assumes that people's motivational states can be focused on potential gains in the environment (a promotion focus) or on potential losses in the environment (a prevention focus). Our emphasis is 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 (Project 1) and implicit similarity-based learning (Project 2). We also propose to introduce social focus into the regulatory focus-learning framework (Projects 3 and 4). 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. ? ? ?
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