Deep learning identification of reward-related neural substrates of preadolescent irritability: A novel 3D CNN application for fMRI.

Johanna C Walker, Conner Swineford, Krupali R Patel, Lea R Dougherty, Jillian Lee Wiggins

Abstract read

In one paragraph

Article in Neuroimage. Reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

Advances in artificial intelligence for neuroimaging.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026
Review

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

5 authors.

Johanna C WalkerJoint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, San Diego, CA, USA.

Conner SwinefordDepartment of Psychology, San Diego State University, San Diego, CA, USA.

Krupali R PatelDepartment of Psychology, San Diego State University, San Diego, CA, USA.

Lea R DoughertyDepartment of Psychology, University of Maryland, College Park, MD, USA.

Jillian Lee WigginsJoint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, San Diego, CA, USA.

Funding

Neural mechanisms of risk for irritability across the transition to adolescenceR01MH122487 · NIMH · SAN DIEGO STATE UNIVERSITY · PI DOUGHERTY, LEA R, WIGGINS, JILLIAN LEE · 2021 to 2025

$1.8M

NIMH NIH HHS R01 MH122487

6 · The paper itself

Abstract

The recent emergence of deep learning methods, particularly convolutional neural networks (CNNs), applied to fMRI data presents a promising avenue in psychiatry research, offering advantages over traditional analyses by requiring minimal assumptions and enabling detection of higher-level patterns and intricate, nonlinear relationships within inherently complex fMRI data. Irritability, defined as a lowered threshold for angry responses to blocked rewards, is a promising neurodevelopmental marker for mental health risk due to its robust, transdiagnostic predictive power in youth. In this study, data from the Adolescent Brain and Cognitive Development (ABCD) baseline sample (

Indexed as

BrainDeep learningIrritabilityPreadolescencePsychopathologyReward

Identifiers

PMID40567457

DOI10.1016/j.ynirp.2025.100259

PMCPMC12172733

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

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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.