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| Funder | NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE |
|---|---|
| Recipient Organization | University of Michigan At Ann Arbor |
| Country | United States |
| Start Date | Sep 15, 2023 |
| End Date | Aug 31, 2025 |
| Duration | 716 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10715723 |
PROJECT SUMMARY/ABSTRACT Individuals make choices and prioritize actions using complex processes that assign value to rewards and associated stimuli based on prior experience. In our modern environment, we are surrounded by an abundance of stimuli that fight for our attention and often hinder goal-directed
behavior. Stimuli, or cues in our environment, attain control over behavior via Pavlovian learning, such that previously neutral stimuli that predict reward acquire motivational properties and are thereby transformed into attractive and desirable incentive stimuli. Whether a stimulus acts solely as a predictor
of reward, or also serves as an incentive stimulus, differs between individuals. Across species, individuals vary in the degree to which reward cues bias choice and control behavior. The neural processes that underlie this individual variation, however, remain to be determined. In the proposed studies we will exploit natural variation in cue-motivated behavior in rats and employ novel tools to
identify critical components of the underlying neural circuitry. When rats are exposed to a Pavlovian conditioned approach paradigm, some, termed “goal-trackers”, primarily attribute predictive value to a discrete food-associated cue; whereas others, termed “sign-trackers” also attribute incentive salience to
the cue. This animal model, therefore, allows us to dissociate the neural processes that promote predictive vs. incentive learning and the resultant behaviors. Using this model, the paraventricular nucleus of the thalamus (PVT) has emerged as a key node that acts to integrate input from top-down cortical control centers and bottom-up subcortical arousal centers and, in turn, guide cue-motivated
behavior. Specifically, recent research from the PI’s laboratory suggests that sign-tracking behavior manifests when subcortical input to the PVT is weighed more heavily than cortical input. Thus, stimulation of cortical input to the PVT attenuates sign-tracking behavior, and this presumably occurs
by shifting the control from bottom-up to top-down processes. The neural code within the PVT that reflects the integrated input and results in goal-directed or maladaptive behaviors remains to be determined and will be the focus of the current proposal. Fluorescence-based calcium imaging will be used in conjunction with machine-learning based “deep phenotyping” to determine the neural signature
of the PVT that predicts subsequent cue-motivated behavior and underlies individual variation. In addition, “top-down” input from the prelimbic cortex to the PVT will be stimulated using chemogenetics and the resultant neuronal activity in the PVT and brain-behavior relationship will be assessed. These
studies will generate a pipeline that future studies will rely on to more deeply probe the neural circuits by which stimuli in the environment attain control over, and incite, behavior.
University of Michigan At Ann Arbor
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