The effects of bilateral lesions to the dorsal tegmental nucleus on spatial learning in rats.
Bibliographic record
Abstract
The head-direction (HD) signal is believed to originate in the dorsal tegmental nucleus (DTN) and lesions to this structure have been shown to disrupt HD cell firing in other areas along the HD cell circuit. To investigate the role of the DTN in spatial navigation, rats with bilateral, electrolytic (Experiment 1), or neurotoxic (Experiment 2) lesions to the DTN were compared with sham controls on two tasks that differed in difficulty and could be solved using directional heading. Rats were first trained on a direction problem in a water T maze where they learned to travel either east or west from two locations in the experimental room. DTN-lesioned rats were impaired relative to sham controls, both early in training, on the first block of eight trials, and on the total trials taken to reach criterion. In the food-foraging task, rats were trained to leave a home cage at the periphery of a circular table, find food in the center of the table and return to the home cage. Again, DTN-lesioned rats were impaired relative to sham rats, making more errors on the return component of the foraging trip. These data extend previous cell-recording studies and behavioral tests in which rats with electrolytic DTN lesions were used, and they demonstrate the importance of the direction system to spatial learning.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".