Simple Protocol for Distinguishing Drug-induced Effects on Spatial Memory Acquisition, Consolidation and Retrieval in Mice Using the Morris Water Maze
Bibliographic record
Abstract
The Morris water maze (MWM) is one of the most commonly used tests for assessing spatial learning and memory in mice. While the MWM is highly amenable to testing the effects of memory modifying drugs, most studies do not consider the timing or duration of drug exposure when conducting the MWM assay; factors that can strongly influence the effect of the drug on different stages of memory and interfere with data interpretation. Herein we describe a MWM protocol which offers the advantage of distinguishing the impact of a fast acting intraperitoneally (IP) injected drug on the different stages of spatial memory: acquisition, consolidation, and retrieval. Mice initially undergo habituation to both the MWM apparatus and IP injection procedure over the course of three days. For assessing the effect of a drug on memory acquisition, mice are injected with the drug prior to training sessions over four consecutive days, where mice learn to find an escape platform in a circular water tank using distal spatial cues. To determine the effect of the drug on memory consolidation, mice are injected with the drug immediately after each training session. For testing the effect of a drug on memory retrieval, mice receive mock IP injections on each training day and the drug is IP injected only once, prior to a probe trial, where mice attempt to locate the platform following its removal from the tank. This protocol provides a simple strategy for distinguishing the effect(s) of a CNS acting drug on the different stages of memory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".