Evidence map›Paper›PMID 41109521›Full record

Trial reportBrain stimulation

TMS-induced modulation of brain networks and its associations to rTMS treatment for depression: a concurrent fMRI-EEG-TMS study.

Hengda He, Xiaoxiao Sun, Jayce Doose, Josef Faller, James R McIntosh, Golbarg T Saber, Sarah Huffman, Linbi Hong, Spiro P Pantazatos, Han Yuan and 5 more

Abstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Brain stimulation. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Hengda HeDepartment of Biomedical Engineering, Columbia University, New York, 10027, NY, USA. Electronic address: hengda.he@columbia.edu.
Xiaoxiao SunDepartment of Biomedical Engineering, Columbia University, New York, 10027, NY, USA.
Jayce DooseCenter for Biomedical Imaging, Medical University of South Carolina, Charleston, 29425, SC, USA.
Josef FallerDepartment of Biomedical Engineering, Columbia University, New York, 10027, NY, USA.
James R McIntoshDepartment of Biomedical Engineering, Columbia University, New York, 10027, NY, USA; Department of Orthopedic Surgery, Columbia University Irving Medical Center, New York, 10032, NY, USA.
Golbarg T SaberCenter for Biomedical Imaging, Medical University of South Carolina, Charleston, 29425, SC, USA; Department of Neurology, University of Chicago, Chicago, 60637, IL, USA.
Sarah HuffmanDepartment of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, 29425, SC, USA.
Linbi HongDepartment of Biomedical Engineering, Columbia University, New York, 10027, NY, USA.
Spiro P PantazatosDepartment of Psychiatry, Columbia University Irving Medical Center, New York, 10032, NY, USA.
Han YuanStephenson School of Biomedical Engineering, The University of Oklahoma, Norman, 73019, OK, USA.
Lisa M McTeagueDepartment of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, 29425, SC, USA; Ralph H. Johnson VA Medical Center, Charleston, 29401, SC, USA.
Robin I GoldmanCenter for Healthy Minds, University of Wisconsin-Madison, Madison, 53705, WI, USA.
Truman R BrownCenter for Biomedical Imaging, Medical University of South Carolina, Charleston, 29425, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, 29425, SC, USA.
Mark S GeorgeDepartment of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, 29425, SC, USA; Ralph H. Johnson VA Medical Center, Charleston, 29401, SC, USA.
Paul SajdaDepartment of Biomedical Engineering, Columbia University, New York, 10027, NY, USA; Department of Electrical Engineering, Columbia University, New York, 10027, NY, USA; Department of Radiology, Columbia University Irving Medical Center, New York, 10032, NY, USA; Data Science Institute, Columbia University, New York, 10027, NY, USA. Electronic address: psajda@columbia.edu.

Funding

EEG/fMRI Controlled TMS Real-time Neural Feedback in Anti-Depressive TreatmentR33MH106775 · NIMH · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BROWN, TRUMAN R · 2018 to 2020
$2.3M
EEG/fMRI Controlled TMS Real-time Neural Feedback in Anti-Depressive TreatmentR21MH106775 · NIMH · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BROWN, TRUMAN R · 2015 to 2016
$1.4M
NIMH NIH HHS R21 MH106775NIMH NIH HHS R33 MH106775
6 · The paper itself

Abstract

introductionTranscranial magnetic stimulation (TMS) over the left dorsolateral prefrontal cortex (L-DLPFC) is an established intervention for treatment-resistant depression (TRD), yet the underlying therapeutic mechanisms remain not fully understood.

methodsThis study employs an integrative approach that combines TMS with concurrent functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), aimed at assessing the acute/immediate effects of TMS on brain network dynamics and their correlation with clinical outcomes. Furthermore, this study explored the brain-state dependent effects of TMS, as the brain-state indexed by the phase of EEG prefrontal alpha oscillation.

resultsOur study demonstrates that TMS acutely modulates connectivity within vital brain circuits, particularly the cognitive control and default mode networks. We found that the baseline TMS-evoked responses in the cognitive control and limbic networks significantly predicted clinical improvement in patients receiving a novel EEG-synchronized repetitive TMS treatment. Clinical outcomes in this novel treatment were linked to state-specific TMS-modulated functional connectivity within a pivotal brain circuit of the L-DLPFC and the posterior subgenual anterior cingulate cortex within the limbic system.

conclusionsThese findings contribute to our understanding of the therapeutic effects underlying TMS treatment in depression and support the potential of assessing state-dependent TMS effects. This study emphasizes the importance of personalized timing of TMS for optimizing target engagement of specific clinically relevant brain circuits. Our results are crucial for future research into the development of personalized neuromodulation therapies for TRD patients.

Indexed as

Nerve NetTranscranial Magnetic StimulationAdultBrainDepressive Disorder, Treatment-ResistantElectroencephalographyFemaleHumansMagnetic Resonance ImagingMaleMiddle Aged

Identifiers

PMID41109521
PMCPMC12716231

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.