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Record W4401587023 · doi:10.3389/fpsyt.2024.1419243

Transcranial alternating current stimulation for neuropsychiatric disorders: a systematic review of treatment parameters and outcomes

2024· review· en· W4401587023 on OpenAlexaff
Fatemeh Gholamali Nezhad, Josh Martin, Vanessa K. Tassone, Alyssa Swiderski, Ilya Demchenko, Somieya Khan, Hamzah E. Chaudhry, Annalisa Palmisano, Emiliano Santarnecchi, Venkat Bhat

Bibliographic record

VenueFrontiers in Psychiatry · 2024
Typereview
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsClinical trialTranscranial alternating current stimulationPsycINFOMedicineNeurocognitiveBrain stimulationDorsolateral prefrontal cortexMEDLINETranscranial direct-current stimulationPsychiatryTranscranial magnetic stimulationPrefrontal cortexCognitionInternal medicineStimulation

Abstract

fetched live from OpenAlex

Background: Transcranial alternating current stimulation (tACS) alters cortical excitability with low-intensity alternating current and thereby modulates aberrant brain oscillations. Despite the recent increase in studies investigating the feasibility and efficacy of tACS in treating neuropsychiatric disorders, its mechanisms, as well as optimal stimulation parameters, are not fully understood. Objectives: This systematic review aimed to compile human research on tACS for neuropsychiatric disorders to delineate typical treatment parameters for these conditions and evaluate its outcomes. Methods: A search for published studies and unpublished registered clinical trials was conducted through OVID (MEDLINE, PsycINFO, and Embase), ClinicalTrials.gov, and the International Clinical Trials Registry Platform. Studies utilizing tACS to treat neuropsychiatric disorders in a clinical trial setting were included. Results: In total, 783 published studies and 373 clinical trials were screened; 53 published studies and 70 clinical trials were included. Published studies demonstrated a low risk of bias, as assessed by the Joanna Briggs Institute Critical Appraisal Tools. Neurocognitive, psychotic, and depressive disorders were the most common disorders treated with tACS. Both published studies (58.5%) and registered clinical trials (52%) most commonly utilized gamma frequency bands and tACS was typically administered at an intensity of 2 mA peak-to-peak, once daily for 20 or fewer sessions. Although the targeted brain locations and tACS montages varied across studies based on the outcome measures and specific pathophysiology of the disorders, the dorsolateral prefrontal cortex (DLPFC) was the most common target in both published studies (30.2%) and registered clinical trials (25.6%). Across studies that published results on tACS outcome measures, tACS resulted in enhanced symptoms and/or improvements in overall psychopathology for neurocognitive (all 11 studies), psychotic (11 out of 14 studies), and depressive (7 out of 8 studies) disorders. Additionally, 17 studies reported alterations in the power spectrum of the electroencephalogram around the entrained frequency band at the targeted locations following tACS. Conclusion: Behavioral and cognitive symptoms have been positively impacted by tACS. The most consistent changes were reported in cognitive symptoms following gamma-tACS over the DLPFC. However, the paucity of neuroimaging studies for each neuropsychiatric condition highlights the necessity for replication studies employing biomarker- and mechanism-centric approaches.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.008
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.368
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2024
Admission routes1
Has abstractyes

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