Findings, limitations and new directions in tACS studies in schizophrenia research: A scoping review
Bibliographic record
Abstract
BACKGROUND: Schizophrenia (SZ) is a severe neurodevelopmental spectrum disorder with significant consequences for the individual who is diagnosed and their family, resulting in notable system-level costs associated with the current methods of treatment. With a complex etiology, this syndrome continues to evade our thorough understanding and invites cautious analysis into how the newest research findings may translate into meaningful interventions. Recent explorations of non-invasive interventions in psychiatry suggest that transcranial alternating current stimulation (tACS) is a safe and potentially promising add-on to the current SZ treatment. METHODS: We performed a systematic literature search for tACS studies on SZ in three databases - Embase, Pubmed and Medline. The search yielded 29 titles and abstracts, of which 8 met the criteria for inclusion: experimental use of tACS on patients with SZ. RESULTS: We found 8 publications where findings from tACS were applied on participants with SZ. The most common frequencies used were theta (4.5 Hertz [Hz] and 6 Hz), alpha (10 Hz) and gamma (40 Hz). The main findings resulting from tACS delivery were: (1) decrease in auditory hallucinations; (2) decrease in negative symptoms; (3) cognitive improvement; and, (4) no change. CONCLUSIONS: This scoping review provides a highlight of current protocols used in tACS studies on SZ, their main findings and limitations, and points towards a direction for new approaches. The wide variety of objectives, protocols and assessments used by researchers demonstrates the diversified nature of research currently used in this field, suggesting the need for a more thorough exploration as results continue to emerge.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.109 | 0.274 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.037 | 0.033 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".