2018 Conference on Cognitive Computational Neuroscience

5-8 September 2018    Philadelphia, Pennsylvania

Technical Program

Paper Detail

Paper: PS-1A.39
Session: Poster Session 1A
Location: Symphony/Overture
Session Time: Thursday, September 6, 16:30 - 18:30
Presentation Time:Thursday, September 6, 16:30 - 18:30
Presentation: Poster
Publication: 2018 Conference on Cognitive Computational Neuroscience, 5-8 September 2018, Philadelphia, Pennsylvania
Paper Title: Dopaminergic changes in striatal pathway competition modify specific cognitive decision parameters
Manuscript:  Click here to view manuscript
DOI: https://doi.org/10.32470/CCN.2018.1034-0
Authors: Kyle Dunovan, Carnegie Mellon University, United States; Catalina Vich, Universitat de les Illes Balears, Spain; Matthew Clapp, University of South Carolina, Spain; Jonathan Rubin, University of Pittsburgh, United States; Timothy Verstynen, Carnegie Mellon University, United States
Abstract: Cortico-basal-ganglia-thalamic (CBGT) networks are critical for adaptive decision-making, yet it remains unclear how their circuit-level properties manifest as cognitive processes. Using a multilevel, biologically plausible modeling approach we simulate CBGT networks to illustrate how (1) dopamine (DA) signals modify the strength of striatal direct (D) and indirect (I) pathways in accordance with a simple reinforcement learning model and (2) learning induced asymmetries in D/I efficacy map to specific cognitive parameters. Simulations of corticostriatal synapses show that DA feedback leads to asymmetrical weights for D and I pathways within a given action channel. The ratio of these weights (wD/wI) effectively encodes the action’s expected value (Q). We then simulated the full CBGT network in the context of a 2-choice value-based decision task, varying the corticostriatal weighting schemes (i.e., wD/wI) for one action channel. The response times from these simulations were fit with a drift-diffusion model (DDM). As wD/wI increased, both drift rate (v) and boundary height (a) parameters changed in the DDM model, with v associated with differences in between-channel D pathway activity, while a modulated with overall I pathway activity. These simulations show how microscale plasticity at corticostriatal synapses can alter specific macroscale properties of cognitive decision processes.