Evidence map›Paper›PMID 42080854›Full record

ArticlePsychology and aging2026

Process explanations of age-related changes in memory specificity.

Nathaniel R Greene, Dominic Guitard, Moshe Naveh-Benjamin

Abstract read
In one paragraph

Article in Psychology and aging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Nathaniel R GreeneDepartment of Psychological and Brain Sciences, Villanova University.ORCID 0000-0001-6758-6761
Dominic GuitardSchool of Psychology, Cardiff University.ORCID 0000-0002-4658-3585
Moshe Naveh-BenjaminDepartment of Psychological Sciences, University of Missouri.

Funding

An Investigation of the Neurocognitive Mechanisms of Age-Related Declines in Episodic Memory Representational SpecificityF32AG087646 · NIA · UNIVERSITY OF PENNSYLVANIA · PI GREENE, NATHANIEL ROBERT · 2024 to 2025
$155k
NIA NIH HHS F32 AG087646NIH HHS
6 · The paper itself

Abstract

Adult aging is associated with a decline in memory for the specific details of past experiences, but the reasons for these declines remain to be fully elucidated. Here, we consider the potential of computational process models of memory to reveal mechanisms underlying age-related changes in memory specificity. We define empirical benchmarks in the most widely used tasks for studying age differences in memory-recognition and free recall. We then systematically review two broad classes of process models-global matching and retrieved context models-that are well-suited to explaining these benchmarks. We discuss and, at times, illustrate through simulations how age differences in memory specificity can arise from different mechanisms in these models, such as reductions in encoding fidelity, cue-selectivity of retrieval, contextual reinstatement, or retrieval monitoring. These models hold great promise for uncovering the latent mechanisms of age-related memory change, but several explanatory shortcomings must be addressed for a more comprehensive theory to emerge. Because process models often incorporate simplifying shortcuts, they risk advancing descriptive rather than mechanistic explanations for age differences in memory. Furthermore, models that have identified multiple processes of age-related memory impairment have left unaddressed the ways in which these processes affect each other. By illuminating these and other challenges in current process models, our review aims to stimulate future advances that can dramatically reshape our understanding of the processes of age-related changes in memory specificity. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Identifiers

PMID42080854
PMCPMC13477681

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.