Encoding uncertainty in the hippocampus

The medial temporal lobe may play a critical role in binding successive events into memory while encoding contextual information in implicit and explicit memory tasks. Information theory provides a quantitative basis to model contextual information engendered by conditional dependence between, or co...

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Bibliographic Details
Published in:Neural networks 2006-06, Vol.19 (5), p.535-546
Main Authors: Harrison, L.M., Duggins, A., Friston, K.J.
Format: Article
Language:English
Subjects:
1st order Markov sequence
Adult
Applied sciences
Artificial intelligence
Bayesian observer
Choice Behavior - physiology
Computer science
control theory
systems
Connectionism. Neural networks
Entropy
Exact sciences and technology
Female
Hippocampus - anatomy & histology
Hippocampus - physiology
Humans
Implicit learning
Information Theory
Learning - physiology
Magnetic Resonance Imaging - methods
Male
Medial temporal lobe
Nerve Net - physiology
Neuropsychological Tests - statistics & numerical data
Predictability
Reaction Time - physiology
Sequential reaction time task (SRTT)
Uncertainty
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Summary:The medial temporal lobe may play a critical role in binding successive events into memory while encoding contextual information in implicit and explicit memory tasks. Information theory provides a quantitative basis to model contextual information engendered by conditional dependence between, or conditional uncertainty about, consecutive events in a sequence. We show that information theoretic indices characterizing contextual dependence within a sequential reaction time task (SRTT) predict regional responses, measured by fMRI, in areas associated with sequence learning and navigation. Specifically, activity of a distributed paralimbic system, centered on the left hippocampus, correlated selectively with predictability as measured with mutual information. This is clear evidence that the brain is sensitive to the probabilistic context in which events are encountered. This is potentially important for theories about how the brain represents uncertainty and makes perceptual inferences, particularly those based on predictive coding and hierarchical Bayes.
ISSN:0893-6080
1879-2782
DOI:10.1016/j.neunet.2005.11.002