Evidence map›Paper›PMID 41379287›Full record

Trial reportGeroScience2026

Cognitive training effects are shaped more by individual brain dynamics than age-evidence from younger and older women.

Zsófia Anna Gaál, Petia Kojouharova, Boglárka Nagy, Gwen van der Wijk, István Czigler, Andrea B Protzner

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in GeroScience, 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
0cells of the map it votes in
0citing 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

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

6 authors.

Zsófia Anna GaálInstitute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary.ORCID http://orcid.org/0000-0002-6615-5393
Petia KojouharovaInstitute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary.ORCID http://orcid.org/0000-0001-6315-4822
Boglárka NagyInstitute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary.ORCID http://orcid.org/0000-0001-7897-839X
Gwen van der WijkDepartment of Clinical Psychological Science, Maastricht University, Maastricht, the Netherlands.ORCID http://orcid.org/0000-0002-8861-8432
István CziglerInstitute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary.ORCID http://orcid.org/0000-0003-1661-3808
Andrea B ProtznerDepartment of Psychology, University of Calgary, Calgary, Alberta, Canada. protzner@ucalgary.ca.ORCID http://orcid.org/0000-0001-8062-2923

Funding

Natural Sciences and Engineering Research Council of Canada 05299-2020Nemzeti Kutatási, Fejlesztési és Innovaciós Alap OTKA K 145940Nemzeti Kutatási, Fejlesztési és Innovaciós Alap OTKA PD 101175
6 · The paper itself

Abstract

Given the well-established structural and functional changes in the aging brain, it is widely assumed that cognitive aging is primarily driven by robust group-level differences between young and older adults. However, our individual-level EEG functional connectivity analysis challenges this notion. We investigated the impact of cognitive training on functional brain connectivity using task-switching paradigms in 39 younger (18-25 years) and 40 older (60-75 years) women. Participants were randomly assigned to either a training group, which completed eight individualized 1-h cognitive training sessions, or a no-contact control group. EEG was recorded at both pre- and post-training sessions across three task-switching paradigms (trained and near-transfer versions). Unique functional connectivity of different sources of variation was examined by calculating how much variance was shared across stable traits (e.g., individual, age, and common factors) or dynamic states (e.g., task and training effects). Our results revealed that age accounted for only a modest proportion of variance, whereas self-similarity was a dominant factor-particularly in older adults. Similarly, group-level training effects were small but strongly modulated by individual neural profiles, suggesting person-specific trajectories. Participants recruited distinct neural networks across tasks, and even within the same task engaged unique, individual-specific network configurations, reflecting personalized brain adaptations to cognitive demands. Importantly, older adults displayed a shift from common to individual network patterns, consistent with increased neural specialization and compensatory mechanisms. These findings underscore the importance of moving beyond group-level contrasts toward models that capture the complexity of individual brain dynamics in cognitive aging and training responsiveness.

Indexed as

AgingBrainCognitionCognitive AgingCognitive TrainingAdolescentAdultAgedAge FactorsCognitive EnhancementElectroencephalographyFemaleHumansMiddle AgedYoung AdultAgingCognitive trainingDeep phenotypingEEGIndividual differences

Identifiers

PMID41379287
PMCPMC13601467

What OpenQuestion holds

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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.