Evidence map›Paper›PMID 40172075›Full record

ArticleHuman brain mapping2025

The Impact of Atlas Parcellation on Functional Connectivity Analysis Across Six Psychiatric Disorders.

Xiaoya Wu, Chuang Liang, Juan Bustillo, Peter Kochunov, Xuyun Wen, Jing Sui, Rongtao Jiang, Xiao Yang, Zening Fu, Daoqiang Zhang and 2 more

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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

12 authors.

Xiaoya WuCollege of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Chuang LiangCollege of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Juan BustilloDepartment of Neurosciences and Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, New Mexico, USA.
Peter KochunovDepartment of Psychiatry and Behavioral Sciences, University of Texas Health Science Center Houston, Houston, Texas, USA.
Xuyun WenCollege of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, China.ORCID 0000-0003-2230-8658
Jing SuiState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Rongtao JiangDepartment of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut, USA.
Xiao YangHuaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China.
Zening FuTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA.
Daoqiang ZhangCollege of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Vince D CalhounTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA.
Shile QiCollege of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, China.

Funding

SOLAR-Eclipse Computational Tools for Imaging GeneticsR01EB015611 · NIBIB · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI KOCHUNOV, PETER V. · 2012 to 2024
$5.0M
Amish Connectome Project on Mental IllnessU01MH108148 · NIMH · UNIVERSITY OF MARYLAND BALTIMORE · PI HONG, L ELLIOT ELLIOT, KOCHUNOV, PETER V. · 2015 to 2018
$4.3M
Towards Multisystem-Brain Successful Aging in Schizophrenia SpectrumR01MH116948 · NIMH · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI HONG, L ELLIOT ELLIOT · 2018 to 2022
$3.7M
Lifespan Vascular Biology on White MatterRF1NS114628 · NINDS · UNIVERSITY OF MARYLAND BALTIMORE · PI HONG, L ELLIOT ELLIOT, KOCHUNOV, PETER V. · 2020 to 2020
$3.1M
The Vascular Axis in Schizophrenia Brain-Body AgingR01MH133812 · NIMH · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI L Elliot Elliot Hong · 2024 to 2026
$2.2M
Redefine Trans-Neuropsychiatric Disorder Brain Patterns through Big-Data and Machine LearningRF1MH123163 · NIMH · UNIVERSITY OF MARYLAND BALTIMORE · PI KOCHUNOV, PETER V., THOMPSON, PAUL M · 2021 to 2021
$1.2M
Lifespan Vascular Biology on White MatterR01NS114628 · NINDS · UNIVERSITY OF MARYLAND BALTIMORE · PI HONG, L ELLIOT ELLIOT, KOCHUNOV, PETER V. · 2024 to 2024
$770k
Hybrid GPU/CPU Computing Resource to Support Connectomic and GenomicsS10OD023696 · OD · UNIVERSITY OF MARYLAND BALTIMORE · PI KOCHUNOV, PETER V. · 2018 to 2018
$593k
Jiangsu Provincial Key Research and Development Program BE2023668National Natural Science Foundation of China 62376124Natural Science Foundation of Jiangsu Province BK20220889NIBIB NIH HHS R01 EB015611NIH HHS S10 OD023696NIMH NIH HHS R01 MH116948NIMH NIH HHS R01 MH133812NIMH NIH HHS RF1 MH123163NIMH NIH HHS U01 MH108148NINDS NIH HHS R01 NS114628NINDS NIH HHS RF1 NS114628
6 · The paper itself

Abstract

Neuropsychiatric disorders are associated with altered functional connectivity (FC); however, the reported regional patterns of functional alterations suffered from low replicability and high variability. This is partly because of differences in the atlas and delineation techniques used to measure FC-related deficits within/across disorders. We systematically investigated the impact of the brain parcellation approach on the FC-based brain network analysis. We focused on identifying the replicable FCs using three structural brain atlases, including Automated Anatomical Labeling (AAL), Brainnetome atlas (BNA) and HCP_MMP_1.0, and four functional brain parcellation approaches: Yeo-Networks (Yeo), Gordon parcel (Gordon) and two Schaefer parcelletions, among correlation, group difference, and classification tasks in six neuropsychiatric disorders: attention deficit and hyperactivity disorder (ADHD, n = 340), autism spectrum disorder (ASD, n = 513), schizophrenia (SZ, n = 200), schizoaffective disorder (SAD, n = 142), bipolar disorder (BP, n = 172), and major depression disorder (MDD, n = 282). Our cross-atlas/disorder analyses demonstrated that frontal-related FC deficits were reproducible in all disorders, independent of the atlasing approach; however, replicable FC extraction in other areas and the classification accuracy were affected by the parcellation schema. Overall, functional atlases with finer granularity performed better in classification tasks. Specifically, the Schaefer atlases generated the most repeatable FC deficit patterns across six illnesses. These results indicate that frontal-related FCs may serve as potential common and robust neuro-abnormalities across 6 psychiatric disorders. Furthermore, in order to improve the replicability of rsfMRI-based FC analyses, this study suggests the use of functional templates at larger granularity.

Indexed as

Atlases as TopicBrainBrain MappingConnectomeMagnetic Resonance ImagingMental DisordersAdultBipolar DisorderFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedNeural PathwaysYoung Adultbrain atlasesbrain network analysisfunctional connectivitypsychiatryreplicability

Identifiers

PMID40172075
PMCPMC11963075

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.