| Literature DB >> 28801273 |
Michael L Mack1, Bradley C Love2, Alison R Preston3.
Abstract
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.Entities:
Keywords: Attention; Computational modeling; Concept learning; Episodic memory; Hippocampus; Prediction error
Mesh:
Year: 2017 PMID: 28801273 PMCID: PMC5803467 DOI: 10.1016/j.neulet.2017.07.061
Source DB: PubMed Journal: Neurosci Lett ISSN: 0304-3940 Impact factor: 3.046