Minor Functional Deficits in Basic Response Patterns for Reinforcement after Frontal Traumatic Brain Injury in Rats
Bibliographic record
Abstract
Traumatic brain injury (TBI) is a major contributor to numerous psychiatric conditions and chronic behavioral dysfunction. Recent studies in experimental brain injury have begun to adopt operant methodologies to assess these deficits, all of which rely on the process of reinforcement. No studies have directly examined how reinforced behaviors are affected by TBI, however. The current study assessed performance under the four most common schedules of reinforcement (fixed ratio, variable ratio, fixed interval, variable interval) and one higher order schedule assessing motivation (progressive ratio) after bilateral, pre-frontal controlled cortical impact injury. TBI-induced differences on the basic schedules were minor, with the exception of the variable ratio, where increased efficacy (more reinforcers, higher response rates, lower interresponse times) at higher requirements was observed as a result of brain injury. Performance on the progressive ratio schedule showed some gross differences between the groups, in that sham rats became more efficient under this schedule while injured rats perseverated in lever pressing. Further, injured rats were specifically impaired at lower response requirements on the progressive ratio. Taken together, these findings indicate that simple reinforced behaviors are mostly unaffected after TBI, except in the case of variable ratio schedules, but the altered performance on the higher-order progressive ratio schedule suggests changes involving motivation or potentially perseveration. These findings validate operant measures of more complex behaviors for brain injury, all of which rely on reinforcement and can be taken into consideration when adapting and developing novel functional assessments.
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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 | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".