A systematic review of ketamine and esketamine-induced long-term potentiation and synaptic scaling: Do the molecular and synaptic plasticity effects inform dosing intervals?
Bibliographic record
Abstract
Ketamine and esketamine exhibit rapid antidepressant effects in persons with treatment-resistant depression (TRD) and bipolar depression (TRBD). However, the synaptic mechanisms governing dose, frequency, and durability of response remain unclear. This review aims to evaluate the dosing parameters, including minimum dose and optimal dosing intervals, that reliably induce or maintain long-term potentiation (LTP) and/or synaptic scaling in humans and preclinical models. A systematic search (database inception to June 2025) was conducted on OVID and PubMed to identify preclinical and clinical studies reporting ketamine-induced clinical symptom changes alongside direct or indirect marker of LTP and/or synaptic scaling. Study selection, quality assessment, and data extraction were conducted by two independent reviewers. Sixty-one clinical and 17 preclinical studies met inclusion criteria. Most clinical studies enrolled persons with TRD, with fewer including TRBD or mixed TRD/TRBD samples. In TRD, a single 0.5 mg/kg intravenous ketamine infusion produced rapid but transient antidepressant effects, peaking at 24-hours and declining over 2-3 days. A similar temporal pattern was observed in TRBD. Early neurophysiological changes emerged within 3-8-hours, consolidated by 24-hours, and were sparsely detected beyond 3-days post-ketamine treatment. Consistent neurophysiological findings were observed in preclinical models. Across clinical trials, twice- versus thrice-weekly dosing yielded comparable four-week outcomes, and weekly maintenance significantly reduced relapse risk. Ketamine may open a plasticity window lasting approximately 2-3 days. Dosing intervals aligned with this window during an acute course of treatment, informed by rapid neurophysiological markers, may optimize antidepressant durability and response while minimizing drug exposure.
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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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".