The Mechanisms Behind Rapid Antidepressant Effects of Ketamine: A Systematic Review With a Focus on Molecular Neuroplasticity
Bibliographic record
Abstract
The mechanism of action underlying ketamine's rapid antidepressant effects in patients with depression, both suffering from major depressive disorder (MDD) and bipolar disorder (BD), including treatment resistant depression (TRD), remains unclear. Of the many speculated routes that ketamine may act through, restoring deficits in neuroplasticity may be the most parsimonious mechanism in both human patients and preclinical models of depression. Here, we conducted a literature search using PubMed for any reports of ketamine inducing neuroplasticity relevant to depression, to identify cellular and molecular events, relevant to neuroplasticity, immediately observed with rapid mood improvements in humans or antidepressant-like effects in animals. After screening reports using our inclusion/exclusion criteria, 139 publications with data from cell cultures, animal models, and patients with BD or MDD were included (registered on PROSPERO, ID: CRD42019123346). We found accumulating evidence to support that ketamine induces an increase in molecules involved in modulating neuroplasticity, and that these changes are paired with rapid antidepressant effects. Molecules or complexes of high interest include glutamate, AMPA receptors (AMPAR), mTOR, BDNF/TrkB, VGF, eEF2K, p70S6K, GSK-3, IGF2, Erk, and microRNAs. In summary, these studies suggest a robust relationship between improvements in mood, and ketamine-induced increases in molecular neuroplasticity, particularly regarding intracellular signaling molecules.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".