Lifespan Changes in the Countermanding Performance of Young and Middle Aged Adult Rats
Bibliographic record
Abstract
Inhibitory control can be investigated with the countermanding task, which requires subjects to make a response to a go signal and cancel that response when a stop signal is presented occasionally. Adult humans performing the countermanding task typically exhibit impaired response time (RT), stop signal response time (SSRT) and response accuracy as they get older, but little change in post-error slowing. Rodent models of the countermanding paradigm have been developed recently, yet none have directly examined age-related changes in performance throughout the lifespan. Male Wistar rats (N = 16) were trained to respond to a visual stimulus (go signal) by pressing a lever directly below an illuminated light for food reward, but to countermand the lever press subsequent to a tone (stop signal) that was presented occasionally (25% of trials) at a variable delay. Subjects were tested in 1 h sessions at approximately 7 and 12 months of age with intermittent training in between. Rats demonstrated longer go trial RT, a higher proportion of go trial errors and performed less total trials at 12, compared to 7 months of age. Consistent SSRT and post-error slowing were observed for rats at both ages. These results suggest that the countermanding performance of rats does vary throughout the lifespan, in a manner similar to humans, suggesting that rodents may provide a suitable model for behavioral impairment related to normal aging. These findings also highlight the importance of indicating the age at which rodents are tested in countermanding investigations.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".