Literature DB >> 22875859

Category-specific neural oscillations predict recall organization during memory search.

Neal W Morton1, Michael J Kahana, Emily A Rosenberg, Gordon H Baltuch, Brian Litt, Ashwini D Sharan, Michael R Sperling, Sean M Polyn.   

Abstract

Retrieved-context models of human memory propose that as material is studied, retrieval cues are constructed that allow one to target particular aspects of past experience. We examined the neural predictions of these models by using electrocorticographic/depth recordings and scalp electroencephalography (EEG) to characterize category-specific oscillatory activity, while participants studied and recalled items from distinct, neurally discriminable categories. During study, these category-specific patterns predict whether a studied item will be recalled. In the scalp EEG experiment, category-specific activity during study also predicts whether a given item will be recalled adjacent to other same-category items, consistent with the proposal that a category-specific retrieval cue is used to guide memory search. Retrieved-context models suggest that integrative neural circuitry is involved in the construction and maintenance of the retrieval cue. Consistent with this hypothesis, we observe category-specific patterns that rise in strength as multiple same-category items are studied sequentially, and find that individual differences in this category-specific neural integration during study predict the degree to which a participant will use category information to organize memory search. Finally, we track the deployment of this retrieval cue during memory search: Category-specific patterns are stronger when participants organize their responses according to the category of the studied material.

Entities:  

Keywords:  category clustering; episodic memory; free recall; neural integration; pattern classification

Mesh:

Year:  2012        PMID: 22875859      PMCID: PMC3767960          DOI: 10.1093/cercor/bhs229

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


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