1-F-126 - Conditioned effects of a ketamine-paired context: implications for its antidepressant mechanism
Bibliographic record
Abstract
Authors: Brett Melanson¹, Michael Wolter¹, Zion Leatham¹, Thomas Lapointe¹, Francesco Leri¹ ¹University of Guelph Abstract: It has been proposed that a context paired with ketamine (KET) can elicit an antidepressant response through principles of Pavlovian conditioning. This raises the question as to whether this conditioned antidepressant response is unique to KET, or whether it can be generalized to other antidepressant drugs with known pharmacological mechanisms like the serotonin reuptake inhibitor, escitalopram (ESC), or the norepinephrine-dopamine reuptake inhibitor, bupropion (BUP). Thus, the current study investigated whether a context paired with KET, ESC, or BUP could influence the immobility response to forced swimming stress (FSS; 10 mins/session, 3 sessions total), which is a preclinical tool used to assess the antidepressant efficacy of drugs. To do this, male Sprague-Dawley rats were injected with 0.9% saline (w/v; SAL) and placed in a vehicle-paired context (CS-) and injected with SAL, KET (10 or 20 mg/kg, IP), ESC (10 mg/kg, IP), or BUP (10 mg/kg, IP) and placed in a drug-paired context (CS+) on alternating days (10 days total, 5 pairings each in the CS- and CS+). One week later, rats were exposed to 3 sessions of FSS over 3 consecutive days (FSS1-3; exposure to CS- and CS+ prior to FSS2 and FSS3, respectively). Exposure to a KET-paired context prior to FSS3 significantly reduced immobility without affecting general locomotor activity in comparison to contexts paired with SAL or BUP, but not ESC. These findings support the notion that a KET-paired context elicits a conditioned antidepressant response, and that this response may partially involve serotonergic mechanisms.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".