This proposal explores the interaction of processes involved in action selection and action execution. This interaction is essential for understanding how people learn to make optimal decisions and develop complex skills, as well as for explicating how disorders of the motor system may impact cognition, a question that has been of central interest in studies of degenerative diseases of the cerebellum and basal ganglia. The interaction can be appreciated by considering that successful decision making requires (at least) two fundamental abilities. First, an agent must be able to evaluate the value of different options in the environment, using that information to choose the option that will maximize reward. Second, the agent must be able to execute a response to indicate the selected option. Traditionally, models of decision making have focused on the former and ignored the latter. However, in many real-world situations, errors in execution are the primary impediment to successful outcomes. A tennis player may correctly opt to use a backhand swing instead of a forehand to return a serve, but fail to execute the action properly. Or in a more mundane example, a person might choose to take a sip from the wine glass rather than the water glass, but fail to reap the expected reward because she knocks over the glass by reaching in a clumsy manner. In this example, the issue is whether a person values wine less (due to the failure to obtain the expected reinforcement) after the clumsy reach, or whether the error is attributed to the execution system, with the outcome precluded from influencing future choice behavior (assuming we are equally competent in reaching for water or wine). The proposed work will examine the psychological processes and neural systems through which action execution and action selection interact. To this end, two specific aims will be addressed. 1) Our pilot work demonstrates a striking difference in choice behavior depending on whether failed outcomes are attributed to a property of the object or a limitation of the execution system. A series of computational models will be developed that have the potential to account for this difference. In a symbiotic manner, behavioral data from a series of experiments will be used to evaluate the models, and the models will be used to generate and test specific predictions. 2) Identify the neural regions involved in the interaction of action errors and selection processes. Of special note here is the idea that cerebellar-based representations of action execution errors might serve a dual-purpose, improving future action execution and providing a gating signal to constrain learning processes that underlie action selection dynamics. The experimental plan for this aim entails the integrated use of functional imaging and neuropsychological studies. At the completion of this project, the studies will help provide an integrated picture of how action selection and action execution processes interact in the human brain to optimize behavior.

Public Health Relevance

This proposal will explore how people learn to make optimal decisions and how disorders of the nervous system impact this ability. A core issue of concern here is to examine the interface between motor and cognitive processes in decision making given that successful learning requires distinguishing between whether an error should be attributed to problems in selection (e.g., poor choices) or problems in execution (e.g., poor motor control). The results should significantly advance our understanding of how disorders of the motor system may impact cognition, a question that has been the focus of considerable debate in research on degenerative diseases of the cerebellum and basal ganglia.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
9R01NS092079-20
Application #
8888798
Study Section
Cognition and Perception Study Section (CP)
Program Officer
Babcock, Debra J
Project Start
2015-04-01
Project End
2020-03-31
Budget Start
2015-04-01
Budget End
2016-03-31
Support Year
20
Fiscal Year
2015
Total Cost
Indirect Cost
Name
University of California Berkeley
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94704
Breska, Assaf; Ivry, Richard B (2018) Double dissociation of single-interval and rhythmic temporal prediction in cerebellar degeneration and Parkinson's disease. Proc Natl Acad Sci U S A 115:12283-12288
Parvin, Darius E; McDougle, Samuel D; Taylor, Jordan A et al. (2018) Credit Assignment in a Motor Decision Making Task Is Influenced by Agency and Not Sensory Prediction Errors. J Neurosci 38:4521-4530
Kim, Hyosub E; Morehead, J Ryan; Parvin, Darius E et al. (2018) Invariant errors reveal limitations in motor correction rather than constraints on error sensitivity. Commun Biol 1:19
Parrell, Benjamin; Agnew, Zarinah; Nagarajan, Srikantan et al. (2017) Impaired Feedforward Control and Enhanced Feedback Control of Speech in Patients with Cerebellar Degeneration. J Neurosci 37:9249-9258
Duque, Julie; Greenhouse, Ian; Labruna, Ludovica et al. (2017) Physiological Markers of Motor Inhibition during Human Behavior. Trends Neurosci 40:219-236
Butcher, Peter A; Ivry, Richard B; Kuo, Sheng-Han et al. (2017) The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks. J Neurophysiol 118:1622-1636
Stark-Inbar, Alit; Raza, Meher; Taylor, Jordan A et al. (2017) Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning. J Neurophysiol 117:412-428
Sokolov, Arseny A; Miall, R Chris; Ivry, Richard B (2017) The Cerebellum: Adaptive Prediction for Movement and Cognition. Trends Cogn Sci 21:313-332
Morehead, J Ryan; Taylor, Jordan A; Parvin, Darius E et al. (2017) Characteristics of Implicit Sensorimotor Adaptation Revealed by Task-irrelevant Clamped Feedback. J Cogn Neurosci 29:1061-1074
Moberget, Torgeir; Ivry, Richard B (2016) Cerebellar contributions to motor control and language comprehension: searching for common computational principles. Ann N Y Acad Sci 1369:154-71

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