Memory Reactivation Predicts Resistance to Retroactive Interference: Evidence from Multivariate Classification and Pattern Similarity Analyses

Koen, J. D. and Rugg, M. D. (2016) Memory Reactivation Predicts Resistance to Retroactive Interference: Evidence from Multivariate Classification and Pattern Similarity Analyses. The Journal of Neuroscience, 36 (15). pp. 4389-4399. ISSN 0270-6474

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Abstract

Memory reactivation—the reinstatement of processes and representations engaged when an event is initially experienced—is believed to play an important role in strengthening and updating episodic memory. The present study examines how memory reactivation during a potentially interfering event influences memory for a previously experienced event. Participants underwent fMRI during the encoding phase of an AB/AC interference task in which some words were presented twice in association with two different encoding tasks (AB and AC trials) and other words were presented once (DE trials). The later memory test required retrieval of the encoding tasks associated with each of the study words. Retroactive interference was evident for the AB encoding task and was particularly strong when the AC encoding task was remembered rather than forgotten. We used multivariate classification and pattern similarity analysis (PSA) to measure reactivation of the AB encoding task during AC trials. The results demonstrated that reactivation of generic task information measured with multivariate classification predicted subsequent memory for the AB encoding task regardless of whether interference was strong and weak (trials for which the AC encoding task was remembered or forgotten, respectively). In contrast, reactivation of neural patterns idiosyncratic to a given AB trial measured with PSA only predicted memory when the strength of interference was low. These results suggest that reactivation of features of an initial experience shared across numerous events in the same category, but not features idiosyncratic to a particular event, are important in resisting retroactive interference caused by new learning.

Item Type: Article
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 13 Nov 2018 15:30
Last Modified: 09 Sep 2020 23:55
URI: https://ueaeprints.uea.ac.uk/id/eprint/68868
DOI: 10.1523/JNEUROSCI.4099-15.2016

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