Evidence map›Paper›PMID 39568548›Full record

ArticleFrontiers in human neuroscience2024

Reproducible routes: reliably navigating the connectome to enrich personalized brain stimulation strategies.

Yilin Liu, Mark H Sundman, Chidi Ugonna, Yu-Chin Allison Chen, Jacob M Green, Lisbeth G Haaheim, Hannah M Siu, Ying-Hui Chou

Abstract read
In one paragraph

Article in Frontiers in human neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. 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

8 authors.

Yilin Liu *Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, Tucson, AZ, United States.
Mark H Sundman *Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, Tucson, AZ, United States.
Chidi UgonnaDepartment of Biomedical Engineering, University of Arizona, Tucson, AZ, United States.
Yu-Chin Allison ChenBrain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, Tucson, AZ, United States.
Jacob M GreenBrain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, Tucson, AZ, United States.
Lisbeth G HaaheimBrain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, Tucson, AZ, United States.
Hannah M SiuBrain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, Tucson, AZ, United States.
Ying-Hui ChouBrain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, Tucson, AZ, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-invasive brain stimulation (NIBS) technologies, such as repetitive transcranial magnetic stimulation (rTMS), offer significant therapeutic potential for a growing number of neuropsychiatric conditions. Concurrent with the expansion of this field is the swift evolution of rTMS methodologies, including approaches to optimize stimulation site planning. Traditional targeting methods, foundational to early successes in the field and still widely employed today, include using scalp-based heuristics or integrating structural MRI co-registration to align the transcranial magnetic stimulation (TMS) coil with anatomical landmarks. Recent evidence, however, supports refining and personalizing stimulation sites based on the target's structural and/or functional connectivity profile. These connectomic approaches harness the network-wide neuromodulatory effects of rTMS to reach deeper brain structures while also enabling a greater degree of personalization by accounting for heterogenous network topology. In this study, we acquired baseline multimodal magnetic resonance (MRI) at two time points to evaluate the reliability and reproducibility of distinct connectome-based strategies for stimulation site planning. Specifically, we compared the intra-individual difference between the optimal stimulation sites generated at each time point for (1) functional connectivity (FC) guided targets derived from resting-state functional MRI and (2) structural connectivity (SC) guided targets derived from diffusion tensor imaging. Our findings suggest superior reproducibility of SC-guided targets. We emphasize the necessity for further research to validate these findings across diverse patient populations, thereby advancing the personalization of rTMS treatments.

Indexed as

diffusion imaging tractographylateral parietal cortexpersonalized brain stimulationresting-state functional connectivitytranscranial magnetic stimulation

Identifiers

PMID39568548
PMCPMC11576443

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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.