The Effects and Safety of Gamma Rhythm Stimulation on Cognitive Function in Alzheimer’s Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Objective Researchers have focused on gamma rhythm stimulation, particularly at 40 Hz, to enhance endogenous gamma oscillations and improve cognitive function and outcomes in Alzheimer’s disease (AD). However, some studies disputed these findings. This review aimed to systematically analyze recent randomized controlled trials on the effects of gamma stimulation on cognitive function in AD and to perform a meta-analysis to assess the efficacy, safety, and differences between brain and sensory stimulation. Methods A systematic search was conducted in PubMed, Web of Science, Ovid-Embase, and Ovid-MEDLINE from their inception to April 2024. A meta-analysis was performed to evaluate adverse events and cognitive function assessed using AD Assessment Scale-Cognitive Subscale (ADAS-cog), Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Face-Name Association Test (FNAT). Subgroup analyses were performed to explore the heterogeneity between the brain and sensory stimulation. Results Eight studies involving 291 participants were included. Meta-analysis demonstrated a large benefit in cognitive function: FNAT (standardized mean difference [SMD] = 3.76; 95% confidence interval [CI] = 2.52-4.99; I 2 = 65%), MMSE (SMD = 3.09; 95% CI = 2.37-3.82; I 2 = 0%), ADAS-cog (SMD = −4.16; 95% CI = −6.60 to −2.62; I 2 = 0%), and MoCA (SMD = 2.17; 95% CI = −0.54 to 4.88; I 2 = 0%). There were no significant differences in adverse events between the intervention and sham groups ( P = .06), suggesting the safety of gamma stimulation. Conclusion This review highlights the safety and benefits of gamma stimulation for cognitive improvement in patients with AD, with sensory stimulation proving safe even in individuals with epilepsy.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.034 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".