A variant of the Morris water task for assessing learning and memory processes in mice
Bibliographic record
Abstract
Abstract The Morris water task (MWT) is commonly used to assess rodent spatial learning and memory. Our goal was to develop a 3-phase variant of the hidden goal water task to assess old and new spatial memories acquired in the same context using various measures of spatial learning in C57BL/6 mice. In the first phase, mice were pre-trained to an initially hidden location. The second phase consisted of a massed training session to a new location in the same apparatus and context. The final phase consisted of a competition test between the original and new platform locations. App NL-G-F/NL-G-F mice, a novel transgenic mouse model for Alzheimer’s disease (AD), were also used as an independent variable to validate this 3-phase variant of MWT. The results of the present study showed that C57 mice acquired and retained both the old and new location representations; however, App NL-G-F/NL-G-F mice retained a recently acquired spatial memory but did not remember the old location acquired in the same apparatus and context. The results showed that C57 mice can show precise place learning and memory with the right amount of training and acquire and retain multiple spatial memory locations in the same environment whereas this ability was impaired in App NL-G-F/NL-G-F mice. In the visible platform test, however, all groups of mice showed normal sensorimotor ability and motivation. These findings indicate that this new version of the MWT provides a robust way for assessment of old and new memories in mice. This paradigm could also be exploited to assess manipulations of neural circuits implicated in learning and memory processes as well as for research investigating human brain diseases.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".