Evidence map›Paper›PMID 39972946›Full record

ArticleHuman brain mapping2025

Transdiagnostic Connectome-Based Prediction of Response Inhibition.

Qiuyu Lv, Xuanyi Wang, Ning Kang, Xiang Wang, Pan Lin

Abstract read
In one paragraph

Article in Human brain mapping, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Qiuyu LvCenter for Mind & Brain Sciences and Institute of Interdisciplinary Studies, Hunan Normal University, Changsha, Hunan, People's Republic of China.
Xuanyi WangCenter for Mind & Brain Sciences and Institute of Interdisciplinary Studies, Hunan Normal University, Changsha, Hunan, People's Republic of China.
Ning KangCenter for Mind & Brain Sciences and Institute of Interdisciplinary Studies, Hunan Normal University, Changsha, Hunan, People's Republic of China.
Xiang WangMedical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People's Republic of China.
Pan LinCenter for Mind & Brain Sciences and Institute of Interdisciplinary Studies, Hunan Normal University, Changsha, Hunan, People's Republic of China.

Funding

National Natural Science Foundation of China 32371136National Natural Science Foundation of China 62071177
6 · The paper itself

Abstract

Response inhibition (RI) deficits are a core feature across diagnostic categories of mental disorders. However, it remains unclear whether the brain networks underlying different forms of RI deficits are disorder-shared or disorder-specific, and how they interact with aberrant brain connectivity across disorders. Connectome-based predictive modeling (CPM) provides a novel approach for exploring the brain networks associated with RI abnormalities across diagnostic categories of mental disorders. Publicly available resting-state functional magnetic resonance imaging data from individuals with schizophrenia (n = 47), bipolar disorder (n = 47), and attention-deficit/hyperactivity disorder (n = 40), as well as healthy controls (n = 121), were utilized to construct whole-brain network predictive models for different forms of RI (action cancellation and action restraint). The brain networks of different forms of RI were further compared with abnormal brain networks in the diagnostic groups. Action restraint and action cancellation exhibited both shared and distinct brain networks. There was a dissociation in the relationship between the brain networks underlying different forms of RI and the aberrant connectivity patterns observed across diagnostic categories. Our models successfully predicted action restraint performance across diagnostic categories, whereas the model failed to effectively predict action cancellation due to the influence of disease-related aberrant connectivity on the brain networks underlying action cancellation. Nevertheless, the action cancellation model demonstrated generalizability to novel, healthy participants (n = 220) from an independent dataset. Our study clarifies the complex relationship between deficits in RI and the neuropathology of mental disorders and provides a foundation for more accurate cognitive assessment and targeted interventions. Our findings highlight the importance of refining RI constructs and emphasize the value of applying connectome methods to reveal cross-diagnostic neural mechanisms.

Indexed as

Attention Deficit Disorder with HyperactivityBipolar DisorderBrainConnectomeInhibition, PsychologicalNerve NetPsychomotor PerformanceSchizophreniaAdultFemaleHumansMagnetic Resonance ImagingMaleYoung Adultconnectome‐based predictive modelingmachine learningresponse inhibitiontransdiagnostic

Identifiers

PMID39972946
PMCPMC11839765

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.