The Ornstein-Uhlenbeck Process In Neural Decision-Making: Mathematical Foundations And Simulations Suggesting The Adaptiveness Of Robustly Integrating Stochastic Neural Evidence

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dc.contributor.advisorShea-Brown, Ericen_US
dc.contributor.authorWojnowicz, Michael Thomasen_US
dc.date.accessioned2013-02-25T17:49:54Z
dc.date.available2013-02-25T17:49:54Z
dc.date.issued2013-02-25
dc.date.submitted2012en_US
dc.descriptionThesis (Master's)--University of Washington, 2012en_US
dc.description.abstractThis master's thesis reviews the concepts behind a stochastic process known as the Ornstein-Uhlenbeck Process, and then uses that process as a way to investigate neural decision making. In particular, MATLAB simulations suggest the usefulness of robustly integrating neural evidence to make a cognitive decision.en_US
dc.embargo.termsNo embargoen_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.otherWojnowicz_washington_0250O_10917.pdfen_US
dc.identifier.urihttp://hdl.handle.net/1773/21760
dc.language.isoen_USen_US
dc.rightsCopyright is held by the individual authors.en_US
dc.subject.otherMathematicsen_US
dc.subject.otherApplied mathematicsen_US
dc.subject.otherMathematicsen_US
dc.titleThe Ornstein-Uhlenbeck Process In Neural Decision-Making: Mathematical Foundations And Simulations Suggesting The Adaptiveness Of Robustly Integrating Stochastic Neural Evidenceen_US
dc.typeThesisen_US

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