Evidence map›Paper›PMID 29962049›Full record

ArticleHuman brain mapping2018

Statistical harmonization corrects site effects in functional connectivity measurements from multi-site fMRI data.

Meichen Yu, Kristin A Linn, Philip A Cook, Mary L Phillips, Melvin McInnis, Maurizio Fava, Madhukar H Trivedi, Myrna M Weissman, Russell T Shinohara, Yvette I Sheline

Abstract readMulticenter Study
In one paragraph

Article in Human brain mapping, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 281 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
281citing papers in PubMed, 3 pooled it
–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

281 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  11. Negative affect and peripheral inflammation: The role of cognitive reappraisal and expressive suppression.Health psychology : official journal of the Division of Health Psychology, American Psychological Association · 2026
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  14. Auditory Network Discoherence in Chronic Tinnitus.medRxiv : the preprint server for health sciences · 2026
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  17. Review
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221 more citing papers are in PubMed but not listed here.

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

10 authors.

Meichen YuCenter for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Kristin A LinnCenter for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Philip A CookCenter for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Mary L PhillipsDepartment of Psychiatry, University of Pittsburgh School of Medicine, Philadelphia, Pennsylvania.
Melvin McInnisDepartment of Psychiatry, University of Michigan School of Medicine, Ann Arbor, Michigan.
Maurizio FavaDepartment of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts.
Madhukar H TrivediDepartment of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas.ORCID 0000-0002-2983-1110
Myrna M WeissmanDepartment of Psychiatry, Columbia University College of Physicians & Surgeons, New York, New York.
Russell T ShinoharaCenter for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Yvette I ShelineCenter for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.ORCID 0000-0002-6929-9659

Funding

Biosignatures of Treatment Remission in Major DepressionU01MH092250 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MCGRATH, PATRICK J, PARSEY, RAMIN V. · 2010 to 2015
$8.9M
Statistical Methods for Multilevel Multivariate Functional StudiesR01NS060910 · NINDS · JOHNS HOPKINS UNIVERSITY · PI Ciprian M Crainiceanu · 2009 to 2026
$8.3M
Inter-modal Coupling Image AnalyticsR01MH112847 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Theodore Satterthwaite, Russell Takeshi Shinohara · 2017 to 2026
$5.9M
Statistical methods for large and complex databases of ultra-high-dimensionalR01NS085211 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI SHINOHARA, RUSSELL TAKESHI · 2013 to 2017
$1.8M
NIMH NIH HHS R01 MH112847NIMH NIH HHS U01 MH092250NINDS NIH HHS R01 NS060910NINDS NIH HHS R01 NS085211
6 · The paper itself

Abstract

Acquiring resting-state functional magnetic resonance imaging (fMRI) datasets at multiple MRI scanners and clinical sites can improve statistical power and generalizability of results. However, multi-site neuroimaging studies have reported considerable nonbiological variability in fMRI measurements due to different scanner manufacturers and acquisition protocols. These undesirable sources of variability may limit power to detect effects of interest and may even result in erroneous findings. Until now, there has not been an approach that removes unwanted site effects. In this study, using a relatively large multi-site (4 sites) fMRI dataset, we investigated the impact of site effects on functional connectivity and network measures estimated by widely used connectivity metrics and brain parcellations. The protocols and image acquisition of the dataset used in this study had been homogenized using identical MRI phantom acquisitions from each of the neuroimaging sites; however, intersite acquisition effects were not completely eliminated. Indeed, in this study, we found that the magnitude of site effects depended on the choice of connectivity metric and brain atlas. Therefore, to further remove site effects, we applied ComBat, a harmonization technique previously shown to eliminate site effects in multi-site diffusion tensor imaging (DTI) and cortical thickness studies. In the current work, ComBat successfully removed site effects identified in connectivity and network measures and increased the power to detect age associations when using optimal combinations of connectivity metrics and brain atlases. Our proposed ComBat harmonization approach for fMRI-derived connectivity measures facilitates reliable and efficient analysis of retrospective and prospective multi-site fMRI neuroimaging studies.

Indexed as

AdolescentAdultAgedBiological Variation, PopulationBrainConnectomeData Interpretation, StatisticalHumansMagnetic Resonance ImagingMajor Depressive DisorderMiddle AgedYoung AdultagingatlasComBatfMRIfunctional connectivitygraph theoryharmonizationmulti-sitenetwork efficiency

Identifiers

PMID29962049
PMCPMC6179920

What OpenQuestion holds

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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.