Autobiographical Memory Content and Recollection Frequency: Public Release of Quantitative Datasets and Representative Classification Analysis.
Episodic memory
autobiographical memory content
experience sampling
human cognition
prospective memory
word-cue technique
Journal
Journal of cognition
ISSN: 2514-4820
Titre abrégé: J Cogn
Pays: England
ID NLM: 101732790
Informations de publication
Date de publication:
17 Jun 2020
17 Jun 2020
Historique:
entrez:
27
6
2020
pubmed:
27
6
2020
medline:
27
6
2020
Statut:
epublish
Résumé
Autobiographical memory (AM), the recollection of personally-experienced events, has several adaptive functions and has been studied across numerous dimensions. We previously introduced two methods to quantify across the life span AM content (the amount and types of retrieved details) and the everyday occurrence of its recollection. The CRAM (cue-recalled autobiographical memory) test used naturalistic word prompts to elicit AMs. Subjects dated the memories to life periods and reported the numbers of details recalled across eight features (e.g., spatial detail, temporal detail, people, and emotions). In separate subjects, an experience sampling method quantified in everyday settings the frequency of AM retrieval and of mental representation of future personal events or actions (termed prospective memory: PM); these data permit evaluation of the temporal orientation of episodic recollection. We describe these datasets now publicly released in open access (CRAM: doi.org/10.6084/m9.figshare.10246958; AM-PM experience-sampling: doi.org/10.6084/m9.figshare.10246940). We also present examples of data mining, using cluster analyses of CRAM (14,242 AMs scored for content from 4,244 subjects). Analysis of raw feature scores yielded three AM clusters separated by total recalled content. Normalizing for total content revealed three classes of AM based on the relative contributions of each feature: AMs containing a relatively large number of details related to people, AMs containing a high degree of spatial information, and AMs with details equally distributed across features. Differences in subject age, memory age, and total content were detected across feature clusters. These findings highlight the value in additional mining of these datasets to further our understanding of autobiographical recollection.
Identifiants
pubmed: 32587941
doi: 10.5334/joc.105
pmc: PMC7304452
doi:
Banques de données
figshare
['10.6084/m9.figshare.10246958']
Types de publication
Journal Article
Langues
eng
Pagination
14Informations de copyright
Copyright: © 2020 The Author(s).
Déclaration de conflit d'intérêts
The authors have no competing interests to declare.
Références
Psychol Aging. 2015 Jun;30(2):209-19
pubmed: 25799004
Neural Plast. 2007;2007:90472
pubmed: 18274617
Conscious Cogn. 2019 Jul;72:31-48
pubmed: 31078046
Mem Cognit. 1997 Nov;25(6):859-66
pubmed: 9421572
Q J Exp Psychol (Hove). 2015;68(1):192-204
pubmed: 25191929
Mem Cognit. 2008 Jul;36(5):920-32
pubmed: 18630199
Psychol Aging. 2002 Dec;17(4):677-89
pubmed: 12507363
J Neurosci. 2009 Mar 11;29(10):3073-82
pubmed: 19279244
Memory. 1998 Mar;6(2):113-41
pubmed: 9640425
Conscious Cogn. 2004 Dec;13(4):844-58
pubmed: 15522635
Psychol Aging. 2009 Jun;24(2):397-411
pubmed: 19485657
Mem Cognit. 2019 Jan;47(1):47-62
pubmed: 30128646
Psychol Aging. 1990 Mar;5(1):119-26
pubmed: 2317290
J Exp Psychol Gen. 1988 Dec;117(4):371-6
pubmed: 2974863
PLoS One. 2012;7(9):e44809
pubmed: 23028629
Mem Cognit. 2011 Jan;39(1):1-11
pubmed: 21264610
Memory. 2009 Oct;17(7):760-73
pubmed: 19657960
Front Behav Neurosci. 2013 May 23;7:47
pubmed: 23734109
J Exp Psychol Gen. 2007 Feb;136(1):112-32
pubmed: 17324087
Front Psychol. 2015 May 19;6:631
pubmed: 26042064
Psychol Rev. 2000 Apr;107(2):261-88
pubmed: 10789197
Memory. 2011 Jul;19(5):470-86
pubmed: 21864212