The opportunity to choose enhances long-term episodic memory.


Journal

Memory (Hove, England)
ISSN: 1464-0686
Titre abrégé: Memory
Pays: England
ID NLM: 9306862

Informations de publication

Date de publication:
04 2019
Historique:
pubmed: 5 9 2018
medline: 26 5 2020
entrez: 5 9 2018
Statut: ppublish

Résumé

Episodic memory is typically studied under conditions that treat participants as passive agents. Here we sought to explore how actively engaging in ongoing naturalistic occurrences affects long-term episodic memory. Participants viewed 40 short movie clips that depicted a protagonist that conversed with the participants. In each clip, they were either offered the chance to (supposedly) determine the clip's continuation (active condition), or let the computer decide for them (passive condition). Participants returned either two days or one week after the experience to undergo a true/false memory test for the clips' details and a two-alternative recognition test for the choices made. Memory performance for both groups was superior for information and choices conveyed in the active vs. passive condition. These findings suggest that the sense of actively influencing the unfolding of events is beneficial to long-term memory of the experience at large, baring potential interventions in the fields of education and cognitive enhancement.

Identifiants

pubmed: 30179077
doi: 10.1080/09658211.2018.1515317
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

431-440

Auteurs

Nuphar Rotem-Turchinski (N)

a Sagol Department of Neurobiology , University of Haifa , Haifa , Israel.
b Institute of Information Processing and Decision Making , University of Haifa , Haifa , Israel.

Ayelet Ramaty (A)

a Sagol Department of Neurobiology , University of Haifa , Haifa , Israel.
b Institute of Information Processing and Decision Making , University of Haifa , Haifa , Israel.

Avi Mendelsohn (A)

a Sagol Department of Neurobiology , University of Haifa , Haifa , Israel.
b Institute of Information Processing and Decision Making , University of Haifa , Haifa , Israel.

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Classifications MeSH