Evidence map›Paper›PMID 40675965›Full record

ArticleTranslational psychiatry2025

Neural correlates differ between crystallized and fluid intelligence in adolescents.

Bowen Qiu, Rui Qian, Baorong Gu, Zichao Li, Zhifan Chen, Xinyi Xu, Huaijin Gao, Yiwei Chen, Ruoke Zhao, Ruike Chen and 5 more

Abstract read
In one paragraph

Article in Translational psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

15 authors.

Bowen QiuKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.ORCID http://orcid.org/0009-0003-8426-5005
Rui QianKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
Baorong GuKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
Zichao LiKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
Zhifan ChenKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
Xinyi XuKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
Huaijin GaoKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
Yiwei ChenKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
Ruoke ZhaoKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
Ruike ChenKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
Yuqi ZhangKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
Lingxuan ZhangKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
Zhiyong ZhaoKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
Mingyang LiKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China. mylee_postdoc@zju.edu.cn.ORCID http://orcid.org/0000-0002-1639-9891
Dan WuKey Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China. danwu.bme@zju.edu.cn.ORCID http://orcid.org/0000-0002-9303-5821

Funding

Chinese Ministry of Science and Technology | Department of S and T for Social Development (Department of S&T for Social Development) 2021ZD0200202National Natural Science Foundation of China (National Science Foundation of China) 32427802, U24A200313
6 · The paper itself

Abstract

Fluid and crystallized intelligence are acknowledged as distinct facets of cognitive ability during brain development, but the specific neural substrates and molecular mechanisms underlying them remain unclear. This study used a sample comprising 7471 young adolescents (mean age 9.87 ± 0.62 years) from the ABCD cohort to elucidate the differential neural correlates of fluid and crystallized intelligence. Our findings indicated that micro-level brain MRI phenotypes such as water diffusivity were closely associated with fluid intelligence, whereas macro-level brain MRI phenotypes such as gray matter cortical thickness were indicative of crystallized intelligence. We further investigated the molecular mechanisms underlying fluid and crystallized intelligence by correlating the characteristic MRI markers with spatial transcriptome profiles and PET imaging. Results showed that fluid intelligence had significant associations with serotonin and glutamate system, while crystallized intelligence was related to serotonin, dopamine and acetylcholine system. Furthermore, we examined the impacts of lifestyle factors on these two forms of intelligence and how the molecular pathways mediated these impacts. Our investigation suggested that physical activities, screen use and sleep duration influenced fluid intelligence mainly through mGlu5 receptors and crystallized intelligence through 5HT1a and D2 receptors. In conclusion, these findings illustrated a distinct neural basis between fluid and crystallized intelligence from the perspectives of neuroimaging, neurotransmitters, and lifestyles in young adolescents.

Indexed as

BrainIntelligenceAdolescentChildFemaleGray MatterHumansMagnetic Resonance ImagingMalePositron-Emission Tomography

Identifiers

PMID40675965
PMCPMC12271475

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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.