Hand-preference training in the mouse reveals key elements of its learning and memory process and resolves the phenotypic complexity in the behaviour
Bibliographic record
Abstract
Handedness in the mouse comprises 2 different behaviours. Some strains have a conditional behaviour, in that the mice learn a direction of hand preference in response to reaching for food, whereas other strains have an innate or constitutive behaviour, and prior experience has no measurable effect on their hand preference. However, hybrids from different strains have revealed both recessive and dominant forms of constitutive hand preference. We proposed that kinetic parameters of the learning process would resolve this genetic heterogeneity as well as the phenotypic complexity in the behaviour. We conducted and report here a detailed kinetic analysis of hand-preference training in the C57BL/6J strain. It revealed elements of the fundamental process of learning and long-term memory that underlies the behaviour by documenting consolidation of memory, blocking of this consolidation by an inhibitor of protein synthesis, retention of memory, and speed of learning in response to training reaches. Furthermore, speed of learning is clearly described by 2 parameters that we call "capacity" (or maximum amount of learned preference) and "ability" (or number of training reaches to achieve half the capacity). These 2 kinetic parameters can vary independently among genetically different strains that learn a preference, and we used them to demonstrate that the respective recessive and dominant forms of constitutive hand-preference may be the consequence of a true null or loss of function and a gain of function, possibly a memory regulator, in the learning process. The quantitative measures provide a sensitive and selective method to establish the fundamental learning process underlying mouse hand preference and to demonstrate empirically how genes and contextual environment shape its phenotypic complexity.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".