Evidence map›Paper›PMID 42699623›Full record

ArticleProceedings. IEEE Southwest Symposium on Image Analysis and Interpretation2026

A Study of Neuroimaging and Genetic Non-linear Associations For Brain Development.

Bhaskar Ray, Dawn Jensen, Ram Sapkota, Jiayu Chen, Vince D Calhoun, Jingyu Liu

Abstract read
In one paragraph

Article in Proceedings. IEEE Southwest Symposium on Image Analysis and Interpretation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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.

Bhaskar RayDepartment of Computer Science, Georgia State University, Atlanta, GA, USA.
Dawn JensenTranslational Research in Neuroimaging and Data Science (TReNDS) center, Atlanta, GA,USA.
Ram SapkotaDepartment of Computer Science, Georgia State University, Atlanta, GA, USA.
Jiayu ChenDepartment of Computer Science, Georgia State University, Atlanta, GA, USA.
Vince D CalhounDepartment of Computer Science, Georgia State University, Atlanta, GA, USA.
Jingyu LiuDepartment of Computer Science, Georgia State University, Atlanta, GA, USA.

Funding

A decentralized macro and micro gene-by-environment interaction analysis of substance use behavior and its brain biomarkers R01DA049238 · NIDA · GEORGIA STATE UNIVERSITY · PI CALHOUN, VINCE D, LIU, JINGYU · 2019 to 2023
$2.9M
Frontal-thalamo-cerebellar circuitry of attention deficit via imaging-genetic-environmental analysesR01MH130595 · NIMH · GEORGIA STATE UNIVERSITY · PI Shihao Ji, Jingyu Liu · 2023 to 2026
$1.4M
NIDA NIH HHS R01 DA049238NIMH NIH HHS R01 MH130595
6 · The paper itself

Abstract

During the transition from childhood to adulthood, the human brain undergoes significant developmental changes that facilitate cognitive maturation, driven by a complex interplay of environmental and genetic factors. Despite abundant studies on neuroimaging for brain development, the specific genetic influences remain unclear. Using brain age estimation, we categorized individuals (N = 7,435, aged 9-10 years) from the Adolescent Brain and Cognitive Development (ABCD) cohort into groups exhibiting either accelerated or delayed brain maturation. This study examines brain imaging and genetic associations within this subpopulation to identify the genetic influences on brain development. We have compared linear association using Sparse Canonical Correlation Analysis (sCCA)-base model and non-linear association with Supervised Contrastive Joint Latent Representation Network (SC-JLRN). Developmentally relevant nonlinear latent patterns between genetic variants highly expressed in the cerebellum and brain regions significantly associated with brain age (cerebellar-hippocamp-frontal circuitry) were extracted.

Indexed as

AdolescenceBrain age estimationBrain developmentFunctional MRIGenetic-brain associationsMulti-modal dataStructural MRISupervised contrastive learning

Identifiers

PMID42699623
PMCPMC13543915

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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.