000009133 001__ 9133
000009133 005__ 20231129124947.0
000009133 0247_ $$2DOI$$a10.6083/gm80hw03b
000009133 037__ $$aETD
000009133 245__ $$aExpected uncertainty drives phasic and tonic exploration in Rhesus Macaques during probabilistic learning
000009133 260__ $$bOregon Health and Science University
000009133 269__ $$a2021
000009133 336__ $$aThesis
000009133 502__ $$bM.S.
000009133 520__ $$aIn changing environments, adaptive decision-making requires balancing when to choose familiar, known options with when to explore new, unknown options. This balancing act, known as the explore-exploit tradeoff, is critical to how we make choices that can maximize reward. Specifically, exploration supports optimal decision-making by reducing the uncertainty associated with previously unknown choices.
000009133 650__ $$aReversal Learning$$025419
000009133 650__ $$aDecision Making$$017417
000009133 650__ $$aBayes Theorem$$015392
000009133 650__ $$aUncertainty$$034655
000009133 650__ $$aReward$$025422
000009133 691__ $$aSchool of Medicine$$041369
000009133 692__ $$aDepartment of Behavioral Neuroscience$$041394
000009133 7001_ $$aRoth Bindas, Sylvia
000009133 8564_ $$998b1a496-1d9e-4f17-96d5-3a5bdb5b3e87$$s1297899$$uhttps://digitalcollections.ohsu.edu/record/9133/files/Bindas.Sylvie.2021.pdf
000009133 905__ $$a/rest/prod/gm/80/hw/03/gm80hw03b
000009133 909CO $$ooai:digitalcollections.ohsu.edu:9133$$pstudent-work
000009133 980__ $$aTheses and Dissertations