A change detection approach to study visual working memory of the macaque monkey
Bibliographic record
Abstract
A core aspect of working memory is that only a limited amount of information can be held at one time, but the investigations of its underlying neural mechanisms in animal models have been dominated by paradigms requiring the retention of a single memorandum. In humans, the information processing limitations of visual working memory have been studied extensively using a sequential comparison procedure, in which subjects detect a change in a multiple-item array following a retention interval. Here, we adopted this approach to study the working memory ability of the macaque monkey. We trained two female rhesus monkeys (Macaca mulatta) to perform a change detection task, in which they were required to report with a saccadic eye movement which one of several items (two to five colored stimuli) in a array had changed color after a 1-s retention interval. Performance gradually declined as a function of set size but always exceeded chance probability. These results show that monkeys possess sufficient information processing capability to perform a visual working memory task requiring the simultaneous maintenance of mnemonic representations of multiple items and validate this animal model for investigation of the neural mechanisms underlying the temporary retention of more than one memorandum.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".