City Research Online

Abstract

Making inference under uncertainty requires an optimal weighting of prior expectations and observations. How this weighting is realized in the brain remains elusive. To investigate this, we recorded functional neuroimaging data while participants estimated a number based on noisy observations. Crucially, the prior expectation about the variability of observations (an expected variability) was manipulated. Consistent with normative models, when novel observations were characterized by higher expected or observed variability, participants’ estimates relied more on expectations than novel observations and were characterized by higher stochasticity. Activity in hippocampus increased when novel evidence was characterized by higher expected or observed variability. Response in superior parietal cortex reflected a precision-weighted prediction error signal (i.e., the distance between observations and expectations) that was modulated by hippocampal activity. Our findings implicate the hippocampus during inference under uncertainty, suggesting a role in weighting prior representations over observations and in modulating responsivity of superior parietal cortex to prediction error.

Publication Type:	Article
Additional Information:	©2019 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Publisher Keywords:	Hippocampus, Inference, Bayesian, Prior, Uncertainty
Subjects:	B Philosophy. Psychology. Religion > BF Psychology R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Departments:	School of Health & Psychological Sciences > Psychology
SWORD Depositor:	Symplectic Administrator

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