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CRCNS: Decision dynamics in cortico-basal ganglia-thalamic networks

Award Number: R01DA059993
ORGANIZATION: NATIONAL INSTITUTE ON DRUG ABUSE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 07/15/2023
PERIOD OF PERFORMANCE END DATE: 05/31/2028

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CRCNS: Decision dynamics in cortico-basal ganglia-thalamic networks - The mammalian brain is particularly well suited for managing streams of (often noisy) evidence, both internally and externally generated, to converge to a decision. This evidence accumulation process can adapt to changing environments and reward opportunities, mediated by cortico-basal-ganglia-thalamic (CBGT) circuits that both contribute to action selection and use feedback signals to modify future decisions. Dysfunction in how these pathways use feedback to guide future decisions is a primary mechanism for many addictive behaviors (e.g., opioid addiction, obesity). Our prior work has identified subsystems, which we call control ensembles, within the CBGT pathways that regulate dimensions of the evidence accumulation process, leading to various neural states with differing receptivity to the evidence streams that drive decisions, encapsulated in a particular decision policy. We propose a series of empirical and theoretical investigations that bridge across levels of analysis to understand the flow of information through CBGT circuits during the decision-making process. On the theory side we will use our models to understand the low-dimensional representational space of CBGT circuits throughout the decision-making process, using energy landscape models coupled with dimensionality reduction. Using computational models we will model decision trajectories through CBGT networks by applying entropy based analyses to the network behavior and building predictions of observed dynamics in both discrete and continuous actions (Specific Aim 1). Empirically, we will test predictions emerging from our network model and provide new observations to support model refinement using experiments in rodents (optogenetics, electrophysiology) as they perform both tasks with dynamic reward contingencies featuring either discrete choices or continuous motor control (Specific Aim 2). Our theoretical and empirical work will evolve in a mutual-development cycle, with theoretical experiments being used to derive novel behavioral and neural predictions and empirical experimental results being used to revise and update the generative model properties that lead to subsequent predictions.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2025 ( Subtotal = $318,458 )
2025	2025	CARNEGIE MELLON UNIVERSITY	5000 FORBES AVE	PITTSBURGH	PA	15213	ALLEGHENY	USA	Drug Use and Addiction Research Programs	000	3	6/18/2025	NON-COMPETING CONTINUATION	$318,458
														Subtotal = $318,458

Issue Date FY: 2024 ( Subtotal = $318,458 )
2024	2024	CARNEGIE MELLON UNIVERSITY	5000 FORBES AVE	PITTSBURGH	PA	15213	ALLEGHENY	USA	Drug Use and Addiction Research Programs	001	2	5/10/2024	NON-COMPETING CONTINUATION	$318,458
2024	2023	CARNEGIE MELLON UNIVERSITY	5000 FORBES AVE	PITTSBURGH	PA	15213	ALLEGHENY	USA	Drug Use and Addiction Research Programs	000	1	1/8/2024	NEW	$0
														Subtotal = $318,458

Issue Date FY: 2023 ( Subtotal = $342,058 )
2023	2023	CARNEGIE MELLON UNIVERSITY	5000 FORBES AVE	PITTSBURGH	PA	15213	ALLEGHENY	USA	Drug Use and Addiction Research Programs	000	1	7/13/2023	NEW	$342,058
														Subtotal = $342,058

Grand Total All Awards = $978,974

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CRCNS: Decision dynamics in cortico-basal ganglia-thalamic networks

Award Number: R01DA059993

ORGANIZATION: NATIONAL INSTITUTE ON DRUG ABUSE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 07/15/2023

PERIOD OF PERFORMANCE END DATE: 05/31/2028

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