Disadvantageous decision-making on a rodent gambling task is associated with increased motor impulsivity in a population of male rats
Bibliographic record
Abstract
BACKGROUND: Impulsivity is understood as a range of behaviours, but the association between these behaviours is not well understood. Although high motor impulsivity is a key symptom of disorders like pathological gambling and addiction, in which decision-making on laboratory tasks is compromised, there have been no clear demonstrations that choice and motor impulsivity are associated in the general population. We examined this association in a large population of rodents. METHODS: We performed a meta-analysis on behavioural data from 211 manipulation-naive male animals that performed a rodent gambling task in our laboratory between 2008 and 2012. The task measures an aspect of both impulsive decision-making and impulsive action, making it possible to evaluate whether these 2 forms of maladaptive behaviour are related. RESULTS: Our meta-analysis revealed that motor impulsivity was positively correlated with poor decision-making under risk. Highly motor impulsive rats were slower to adopt an advantageous choice strategy and quicker to make a choice on individual trials. LIMITATIONS: The data analyzed were limited to that produced by our laboratory and did not include data of other researchers who have used the task. CONCLUSION: This work may represent the first demonstration of a clear association between choice and motor impulsivity in a nonclinical population. This lends support to the common practice of studying impulsivity in nonclinical populations to gain insight into impulse control disorders and suggests that differences in impulsive behaviours between clinical and nonclinical populations may be ones of magnitude rather than ones of quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".