Evidence map›Paper›PMID 38853941›Full record

ArticlebioRxiv : the preprint server for biology2024

Real-time optimization to enhance noninvasive cortical excitability assessment in the human dorsolateral prefrontal cortex.

Sara Parmigiani, Christopher C Cline, Manjima Sarkar, Lily Forman, Jade Truong, Jessica M Ross, Juha Gogulski, Corey J Keller

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Sara ParmigianiDepartment of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA.ORCID 0000-0001-9783-9029
Christopher C ClineDepartment of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Manjima SarkarDepartment of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Lily FormanDepartment of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Jade TruongDepartment of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Jessica M RossDepartment of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Juha GogulskiDepartment of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Corey J KellerDepartment of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA.ORCID 0000-0003-0529-3490

Funding

Closing the loop: development of real-time, personalized brain stimulationR01MH126639 · NIMH · STANFORD UNIVERSITY · PI KELLER, COREY J · 2021 to 2024
$1.6M
CRCNS US-France Research Proposal: Probing the Dorsolateral Prefrontal Cortex and Central Executive Network for Improving Neuromodulation in DepressionR01MH129018 · NIMH · STANFORD UNIVERSITY · PI KELLER, COREY J · 2021 to 2025
$1.1M
NIMH NIH HHS R01 MH126639NIMH NIH HHS R01 MH129018
6 · The paper itself

Abstract

Objective: We currently lack a robust noninvasive method to measure prefrontal excitability in humans. Concurrent TMS and EEG in the prefrontal cortex is usually confounded by artifacts. Here we asked if real-time optimization could reduce artifacts and enhance a TMS-EEG measure of left prefrontal excitability. Methods: This closed-loop optimization procedure adjusts left dlPFC TMS coil location, angle, and intensity in real-time based on the EEG response to TMS. Our outcome measure was the left prefrontal early (20-60 ms) and local TMS-evoked potential (EL-TEP). Results: In 18 healthy participants, this optimization of coil angle and brain target significantly reduced artifacts by 63% and, when combined with an increase in intensity, increased EL-TEP magnitude by 75% compared to a non-optimized approach. Conclusions: Real-time optimization of TMS parameters during dlPFC stimulation can enhance the EL-TEP. Significance: Enhancing our ability to measure prefrontal excitability is important for monitoring pathological states and treatment response.

Indexed as

dorsolateral prefrontal cortex (dlPFC)electroencephalogram (EEG)evoked potentialsreal-time optimizationTEPTMS-EEGTranscranial magnetic stimulation (TMS)

Identifiers

PMID38853941
PMCPMC11160722

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.