Kv4.2 knockout mice display learning and memory deficits in the Lashley maze
Bibliographic record
Abstract
Background : Potassium channels have been shown to be involved in neural plasticity and learning. Kv4.2 is a subunit of the A-type potassium channel. Kv4.2 channels modulate excitability in the dendrites of pyramidal neurons in the cortex and hippocampus. Deletion of Kv4.2 results in spatial learning and conditioned fear deficits; however, previous studies have only examined deletion of Kv4.2 in aversive learning tests. Methods : For the current study, we used the Lashley maze as an appetitive learning test. We examined Kv4.2 wildtype (WT) and knockout (KO) mice in the Lashley maze over 4 days during adulthood. The first day consisted of habituating the mice to the maze. The mice then received five trials per day for the next 3 days. The number of errors and the time to the goal box was recorded for each trial. The goal box contained a weigh boat with an appetitive reward (gelatin with sugar). There was an intertrial interval of 15 minutes. Results : We found that Kv4.2 KO mice committed more errors across the trials compared to the WT mice p <0.001. There was no difference in the latency to find the goal box over the period. Discussion : Our finding that deletion of Kv4.2 resulted in more errors in the Lashley maze across 15 trials contribute to a growing body of evidence that Kv4.2 channels are significantly involved in learning and memory.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".