Literature DB >> 24215973

Neural mechanisms supporting the extraction of general knowledge across episodic memories.

Carly C G Sweegers1, Atsuko Takashima2, Guillén Fernández3, Lucia M Talamini4.   

Abstract

General knowledge acquisition entails the extraction of statistical regularities from the environment. At high levels of complexity, this may involve the extraction, and consolidation, of associative regularities across event memories. The underlying neural mechanisms would likely involve a hippocampo-neocortical dialog, as proposed previously for system-level consolidation. To test these hypotheses, we assessed possible differences in consolidation between associative memories containing cross-episodic regularities and unique associative memories. Subjects learned face-location associations, half of which responded to complex regularities regarding the combination of facial features and locations, whereas the other half did not. Importantly, regularities could only be extracted over hippocampus-encoded, associative aspects of the items. Memory was assessed both immediately after encoding and 48 h later, under fMRI acquisition. Our results suggest that processes related to system-level reorganization occur preferentially for regular associations across episodes. Moreover, the build-up of general knowledge regarding regular associations appears to involve the coordinated activity of the hippocampus and mediofrontal regions. The putative cross-talk between these two regions might support a mechanism for regularity extraction. These findings suggest that the consolidation of cross-episodic regularities may be a key mechanism underlying general knowledge acquisition.
Copyright © 2013 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Episodic memory; Hippocampus; Semantic memory; System-level consolidation; fMRI

Mesh:

Year:  2013        PMID: 24215973     DOI: 10.1016/j.neuroimage.2013.10.063

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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