Journal
NEUROSCIENCE LETTERS
Volume 680, Issue -, Pages 31-38Publisher
ELSEVIER IRELAND LTD
DOI: 10.1016/j.neulet.2017.07.061
Keywords
Hippocampus; Concept learning; Episodic memory; Attention; Prediction error; Computational modeling
Categories
Funding
- Natural Sciences and Engineering Research Council
- National Institute of Mental Health [F32-MH100904, R01-MH100121]
- Leverhulme Trust [RPG-2014-075]
- Wellcome Trust [WT106931MA]
- National Institute of Child Health and Human Development [1P01HD080679]
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Concepts organize our experiences and allow for meaningful inferences in novel situations. Acquiring new concepts requires extracting regularities across multiple learning experiences, a process formalized in mathematical models of learning. These models posit a computational framework that has increasingly aligned with the expanding repertoire of functions associated with the hippocampus. Here, we propose the Episodes-to-Concepts (EpCon) theoretical model of hippocampal function in concept learning and review evidence for the hippocampal computations that support concept formation including memory integration, attentional biasing, and memory-based prediction error. We focus on recent studies that have directly assessed the hippocampal role in concept learning with an innovative approach that combines computational modeling and sophisticated neuroimaging measures. Collectively, this work suggests that the hippocampus does much more than encode individual episodes; rather, it adaptively transforms initially-encoded episodic memories into organized conceptual knowledge that drives novel behavior. (C) 2017 Elsevier B.V. All rights reserved.
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