Evidence map›Paper›PMID 38033550›Full record

SynthesisFrontiers in neuroscience2023

Effortful and effortless training of executive functions improve brain multiple demand system activities differently: an activation likelihood estimation meta-analysis of functional neuroimaging studies.

Chan Tang, Ting Huang, Jipeng Huang, Nuo Xu, Hui Lyu, Yuan Wang, Yifei Cao

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in neuroscience, 2023. 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

7 authors.

Chan Tang *School of Psychology, Northeast Normal University, Changchun, China.
Ting Huang *School of Psychology, Northeast Normal University, Changchun, China.
Jipeng HuangSchool of Psychology, Northeast Normal University, Changchun, China.
Nuo XuSchool of Psychology, Northeast Normal University, Changchun, China.
Hui LyuSchool of Psychology, Northeast Normal University, Changchun, China.
Yuan WangSchool of Psychology, Northeast Normal University, Changchun, China.
Yifei CaoSchool of Psychology, Northeast Normal University, Changchun, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Both effortful and effortless training have been shown to be effective in enhancing individuals' executive functions. Effortful training improves domain-specific EFs, while effortless training improves domain-general EFs. Furthermore, effortful training has significantly higher training effects on EFs than effortless training. The neural mechanism underlying these different effects remained unclear. The present study conducted meta-analysis on neuroimaging studies to explore the changes of brain activations induced by effortful and effortless training. The results showed that effortful training induced greater activation in superior frontal gyrus, while effortless training induced greater activation in middle frontal gyrus, precuneus and cuneus. The brain regions of MD system enhanced by effortful training were more associated with core cognitive functions underlying EFs, while those enhanced by effortless training were more correlated with language functions. In addition, the significant clusters induced by effortful training had more overlaps with the MD system than effortless training. These results provided us with possibility to discuss the different behavioral results brought by effortful and effortless training.

Indexed as

effortful trainingeffortless trainingexecutive functionsfMRImeta-analysismultiple demand system

Identifiers

PMID38033550
PMCPMC10682784

What OpenQuestion holds

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LicenceCC BY
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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.