Atomoxetine has no effects on visual working memory but benefits motivation
Bibliographic record
Abstract
Atomoxetine (ATX) is a selective catecholamine reuptake inhibitor and is increasingly prescribed to individuals with attention deficit hyperactivity disorder (ADHD). To date, there is equivocal evidence that ATX improves cognitive abilities in nonhuman primates and humans, including people with ADHD. We examined the effects of ATX on visual working memory in three adult female rhesus macaques. The animals were tested with a range of ATX doses (0.03-3 mg/kg) that span beyond the therapeutic range (0.5-1.4 mg/kg); they were orally administered the drug. A visual sequential comparison (VSC) task was used to assess visual working memory. Each trial of the VSC task begins with the presentation of a memory array of 2 to 5 coloured stimuli. Following a one second retention interval, a test array is presented and the animals are required to make a saccade to the item that has changed colour to receive a liquid reward. We found that ATX did not significantly enhance the monkeys' response accuracy and response latency in the VSC task. However, ATX had significant effects on improving the animals' motivation (task engagement) in the VSC task. To more directly assess motivation following the administration of ATX, we developed a task with a progressive ratio (PR) schedule of reinforcement. In this PR task, the animal must fixate a gradually increasing number of visual stimuli to obtain the reinforcer (liquid) and the number of fixations made to obtain the last reinforcer (the breakpoint) estimates motivation. We found that the animals' breakpoint in the PR task varied as a function of ATX dose, with an optimal dose falling within 0.3 and 3 mg/kg. Overall, our results suggest that ATX does not directly enhance visual working memory and may be best described as boosting motivation. Meeting abstract presented at VSS 2018
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".