The same type of visual working memory limitations in humans and monkeys
Bibliographic record
Abstract
Rhesus monkeys are widely used as an animal model for human memory, including visual working memory (VWM). It is, however, unknown whether the same principles govern VWM in humans and rhesus monkeys. Here, we tested both species in nearly identical change-localization paradigms and formally compared the same set of models of VWM limitations. These models include the classic item-limit model and recent noise-based (resource) models, as well as hybrid models that combine a noise-based representation with an item limit. By varying the magnitude of the change in addition to the typical set size manipulation, we were able to show large differences in goodness of fit among the five models tested. In spite of quantitative performance differences between the species, we find that the variable-precision model--a noise-based model--best describes the behavior of both species. Adding an item limit to this model does not help to account for the data. Our results suggest evolutionary continuity of VWM across primates and help establish the rhesus monkey as a model system for studying the neural substrates of multiple-item VWM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| 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".