Evidence map›Paper›PMID 42710367›Full record

ArticleNeuroImage. Clinical2026

An Epicenter-guided computational framework for personalized target of repetitive transcranial magnetic stimulation in schizophrenia.

Yingjie Tang, Sisi Jiang, Huan Huang, Xueqing Sun, Chao Mu, Mingjun Duan, Roberto Rodríguez-Labrada, Dezhong Yao, Cheng Luo

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NeuroImage. Clinical, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

9 authors.

Yingjie TangThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China; China-Cuba Belt and Road Joint Laboratory on Neurotechnology and Brain-Apparatus Communication, University of Electronic Science and Technology of China, Chengdu 610054, PR China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, PR China.
Sisi JiangThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China; China-Cuba Belt and Road Joint Laboratory on Neurotechnology and Brain-Apparatus Communication, University of Electronic Science and Technology of China, Chengdu 610054, PR China.
Huan HuangThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China; China-Cuba Belt and Road Joint Laboratory on Neurotechnology and Brain-Apparatus Communication, University of Electronic Science and Technology of China, Chengdu 610054, PR China.
Xueqing SunThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China; China-Cuba Belt and Road Joint Laboratory on Neurotechnology and Brain-Apparatus Communication, University of Electronic Science and Technology of China, Chengdu 610054, PR China.
Chao MuThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China; Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, PR China.
Mingjun DuanThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China; Department of Psychiatry, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, PR China.
Roberto Rodríguez-LabradaCuban Neuroscience Center, La Habana, Cuba.
Dezhong YaoThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China; China-Cuba Belt and Road Joint Laboratory on Neurotechnology and Brain-Apparatus Communication, University of Electronic Science and Technology of China, Chengdu 610054, PR China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, PR China.
Cheng LuoThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China; China-Cuba Belt and Road Joint Laboratory on Neurotechnology and Brain-Apparatus Communication, University of Electronic Science and Technology of China, Chengdu 610054, PR China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, PR China; Department of Radiology, The Fourth People's Hospital of Chengdu, Chengdu 610056, PR China. Electronic address: chengluo@uestc.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe clinical efficacy of repetitive transcranial magnetic stimulation (rTMS) in schizophrenia is limited by significant inter-individual heterogeneity, largely due to the lack of personalized targeting. HYPOTHESIS: To develop and validate an epicenter-guided computational framework that identifies personalized rTMS targets by integrating individual neuroanatomical and connectome profiles. STUDY

designWe established an epicenter-guided framework in a discovery cohort including 532 schizophrenia and 526 healthy controls. The pipeline involved: (1) identifying subject-specific pathological epicenters by correlating regional gray-matter volume reductions with normative functional connectivity profiles; (2) mapping the voxels within the left dorsolateral prefrontal cortex that exhibited maximal functional connectivity to these epicenters; and (3) computing the harmonic centroid of these voxels to define the optimal personalized target. The framework was retrospectively validated in a cohort of schizophrenia receiving a 4-week rTMS treatment. STUDY

resultsThe epicenter-guided framework defined a personalized candidate target for each participant with an identifiable individual epicenter. Individual epicenters converged within higher-order association cortices and subcortical structures, consistent with previous findings in schizophrenia. In the retrospective treatment cohort, nodal integration capability within individual epicenter regions increased significantly after rTMS. Smaller target distance was associated with greater concordance between activity-flow-predicted and observed FC changes and with greater improvement in PANSS negative symptoms.

conclusionsWe developed an epicenter-guided framework to derive personalized DLPFC targets and, in retrospective validation, found that target proximity relates to both FC normalization and symptom improvement. These findings support further prospective testing of connectivity-informed personalized targeting for rTMS in schizophrenia.

Indexed as

Activity-flow mappingEpicenterPersonalized targetrTMSSchizophrenia

Identifiers

PMID42710367
PMCPMC13573745

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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.