Evaluating Sequential Response Learning in the Rodent Operant Touchscreen System
Bibliographic record
Abstract
Sequential and cue-directed response learning in rodents have been previously shown to depend on intact striatal signaling. In particular, these behaviors rely on striatal dopamine and acetylcholine release, with an impairment of sequential response learning evident in animal models with alterations in the two systems. Here we provide a protocol for testing sequential response/response chain learning using the rodent touchscreen system. Specifically, the present protocol is designed to implement the heterogeneous sequence task, adapted from Keeler et al. (2014), in the rodent touchscreen apparatus. This task has been used previously to assess complex motor learning and response selection in mice. In the following protocol, the task is performed in touchscreen-based automated chambers with five response locations using food reinforcers to maintain performance. The sequence task requires the subject to make five nose pokes to white square stimuli appearing in five different locations sequentially from left to right. © 2021 Wiley Periodicals LLC. Basic Protocol: Implementation of the heterogeneous sequence task Support Protocol: Creation of the heterogeneous sequence task ABET II touchscreen schedule.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| 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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".