Evidence map›Paper›PMID 41820527›Full record

ArticleNPJ digital medicine2026

Meta-analysis of computerised working memory training: behavioural gains, training parameters, transfer mechanisms, and neural correlates.

Geng Li, Yang Liu, Antao Chen

Abstract read
In one paragraph

Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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.

Geng LiBrain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine and School of Psychology, Shanghai, China.
Yang LiuSchool of Sports Science, Jishou University, Jishou, China.
Antao ChenBrain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine and School of Psychology, Shanghai, China. antao.chen@sjtu.edu.cn.ORCID http://orcid.org/0000-0001-9321-681X

Funding

the National Natural Science Foundation of China 32171040
6 · The paper itself

Abstract

Working memory training (WMT) is widely used to enhance cognitive task performance, yet traditional delivery poses challenges for sustained implementation; computerised working memory training (CWMT) provides a scalable digital format with standardised delivery and integrated monitoring and feedback. We conducted the first meta-analysis integrating behavioural and neuroimaging evidence to quantify the behavioural effects and neural correlates of CWMT, drawing on 45 neuroimaging studies. Multivariate meta-analysis indicated a moderate benefit of CWMT relative to controls (Hedges' g = 0.503, 95% CI [0.363-0.642]). Seed-based d mapping (SDM) identified training-related decreases in activation in the left angular gyrus (L-AG), bilateral superior frontal gyrus (SFG), right inferior parietal lobule (R-IPL), left cerebellum, and right middle frontal gyrus (R-MFG), a pattern compatible with reduced recruitment following training. Moderator analyses showed significant effects of task type, training compliance, total training dose, and age, but not cognitive status and sex. Moreover, CWMT-induced brain activation changes were associated with behavioural improvements, and significant co-activation was observed among the brain regions identified in the overall analysis. Together, these findings provide convergent evidence that CWMT is associated with improved cognitive task performance and reproducible modulation of task-related activation, supporting its relevance as a scalable digital approach to cognitive health.

Identifiers

PMID41820527
PMCPMC13121830

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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.