Memory and aging: Selected research directions and application issues.
Notice bibliographique
Résumé
Abstract Everyday memory failures and long-term memory changes are among the most empirically established, socially expected, personally disconcerting, and widely misinterpreted aspects of human aging. A large, sophisticated, and still growing theoretical research base on memory aging has accumulated over the last several decades. Following a brief summary of a broad swath of selected basic memory aging phenomena, we identify a small subset of relatively recent but well-researched topics that may hold promise for optimizing memory adaptation in late life. Linking research with potential application, we sketch key objectives for three potential directions of intervention in memory and aging. Research on memory and aging is focused on processes through which individuals may recall previously experienced events or information, the extent to which these processes change with advancing age, and the conditions, correlates, or predictors of such changes. Reflecting the sheer volume of research in this field, numerous reviews of memory and aging have been published in recent decades (e.g., Craik & Salthouse, 2000; Hultsch, Hertzog, Dixon, & Small, 1998; Prull, Gabrieli, & Bunge, 2000; Zacks, Hasher, & Li, 2000). Of all aspects of the many cognitive changes that occur with aging, memory may be the one that has most captivated the interest of both aging individuals and our society in general (Bialystok & Craik, 2006; Dixon, Backman, & Nilsson, 2004; NavehBenjamin, Moscovitch, & Roediger, 2001; Park & Schwarz, in press; Zacks & Hasher, 2006). Reviewers often include several important facts about memory and aging: * Memory is viewed as a functional, if not essential, tool of successful lifespan development; * Memory failures and loss are among the most frequently mentioned complaints of older adults; * Memory loss is one of the most feared signs and implications of normal aging; * Late-life memory changes, both subtle and dramatic, can be the early indicators of cognitive impairment, including that associated with neurodegenerative diseases; * Widespread stereotypes in the Western world hold that, whereas memory abilities improve through childhood, they decline with aging. For these and other reasons, many researchers, practitioners, and aging adults are profoundly interested in understanding changes in memory abilities throughout adulthood, including answers to simple questions such as how, when, why, and to what extent memory may decline in late life. Over the last several decades, research on memory and aging has revealed provocative patterns of results. Whereas some memory tasks are associated with robust findings of aging-related deficits, other tasks are associated with less pronounced losses or even equivalent performance by younger and older adults. To understand why such divergent patterns might occur, it is useful to consider briefly both memory tasks and general memory theory. Memory tasks typically associated with aging-related decline include remembering lists of information, expository texts, faces and names, picture characteristics, spatial locations, and those that tap the limits of online memory processing. Tasks often associated with relatively unimpaired performance include memory for facts, words, and knowledge, and those that reflect familiar situations that include substantial environmental or human support. One well-developed theoretical treatment of memory per se has proven helpful in organizing this multidimensional pattern of results. Specifically, the memory systems perspective has been especially influential in research on memory and aging (Craik & Salthouse, 2000; Nyberg et al., 2003; Tulving, 1995). Positing that there are multiple systems of memory, a central goal of this perspective is to explicate the organization of, and relationships among, the systems. A memory system is defined as a set of related processes, linked by common brain mechanisms, information processes, and operational principles (Schacter & Tulving, 1994). …
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».