Evidence map›Paper›PMID 35254408›Full record

ArticleCerebral cortex (New York, N.Y. : 1991)2023

A connectome-based neuromarker of nonverbal number acuity and arithmetic skills.

Dai Zhang, Liqin Zhou, Anmin Yang, Shanshan Li, Chunqi Chang, Jia Liu, Ke Zhou

Open access · hybridAbstract read
In one paragraph

Article in Cerebral cortex (New York, N.Y. : 1991), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.0field-weighted citation impact, top 13% of its field
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

5 citing papers in PubMed, 8 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

Dai ZhangBeijing Key Laboratory of Applied Experimental Psychology, School of Psychology, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District, Beijing 100875, China.
Liqin ZhouBeijing Key Laboratory of Applied Experimental Psychology, School of Psychology, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District, Beijing 100875, China.
Anmin YangBeijing Key Laboratory of Applied Experimental Psychology, School of Psychology, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District, Beijing 100875, China.
Shanshan LiBeijing Key Laboratory of Applied Experimental Psychology, School of Psychology, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District, Beijing 100875, China.
Chunqi ChangGuangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Health Science Center, No. 1066, Xueyuan Street, Nanshan District, Shenzhen 518060, China.
Jia LiuDepartment of Psychology & Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, No. 30, Shuangqing Street, Haidian District, Beijing 100084, China.
Ke ZhouBeijing Key Laboratory of Applied Experimental Psychology, School of Psychology, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District, Beijing 100875, China.ORCID 0000-0003-4773-758X
Beijing Normal University · CNShenzhen University Health Science Center · CNTsinghua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The approximate number system (ANS) is vital for survival and reproduction in animals and is crucial for constructing abstract mathematical abilities in humans. Most previous neuroimaging studies focused on identifying discrete brain regions responsible for the ANS and characterizing their functions in numerosity perception. However, a neuromarker to characterize an individual's ANS acuity is lacking, especially one based on whole-brain functional connectivity (FC). Here, based on the resting-state functional magnetic resonance imaging (rs-fMRI) data obtained from a large sample, we identified a distributed brain network (i.e. a numerosity network) using a connectome-based predictive modeling (CPM) analysis. The summed FC strength within the numerosity network reliably predicted individual differences in ANS acuity regarding behavior, as measured using a nonsymbolic number-comparison task. Furthermore, in an independent dataset of the Human Connectome Project (HCP), we found that the summed FC strength within the numerosity network also specifically predicted individual differences in arithmetic skills, but not domain-general cognitive abilities. Therefore, our findings revealed that the identified numerosity network could serve as an applicable neuroimaging-based biomarker of nonverbal number acuity and arithmetic skills.

Indexed as

ConnectomeAnimalsBrainCognitionHumansMagnetic Resonance ImagingNeuroimagingapproximate number systemarithmetic skillsconnectome-based predictive modelingindividual differencesresting-state fMRI

Identifiers

PMID35254408
PMCPMC9890459
OpenAlexW4213435142

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.