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CCN Brown Bag Series

Wednesday, January 23, 2019,

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  • Location: Wilson 115
  • Room: 115

Timothy P. McNamara, PhD

Department of Psychology

Vanderbilt University

"Bayesian Decision Theory and Navigation"

Effective spatial navigation depends on the ability to combine information from multiple sources or cues to estimate properties of the environment, such as the location of a goal.  Spatial cues include landmarks, and other visible features of the environment, and body-based cues generated by self-motion (e.g., vestibular, proprioceptive, & efferent information).  A number of recent experiments have investigated the extent to which visual cues and body-based cues are combined optimally according to statistical principles.  Although several of these studies have documented optimal or near-optimal cue combination, other studies have shown that navigators sometimes fail to combine cues optimally or even at all.  Possible limitations of all of these investigations are that they have not accounted for navigators’ prior experiences with or assumptions about spatial cues and have not tested fully-specified decision models.  In this presentation, I will examine whether apparent violations of optimal cue combination can be explained by incorporating informative priors or appropriate loss functions in Bayesian decision-theoretic models.