The psychophysical properties of working memory and mental rotation reveal different processes
Bibliographic record
Abstract
Despite the fact that the influential Working Memory (WM) model proposed by Baddeley and Hitch (1974) included the manipulation of information as a fundamental aspect of this cognitive ability, how individuals manipulate mental representations remains an underexplored area in vision science. Moreover, though the psychophysical properties of WM are well established for simple stimuli (eg. lines, colors), less is known about WM for more complex stimuli. In contrast, the mental imagery literature has commonly used 3D stimuli to investigate the manipulation of mental representations, however less is known about the psychophysical properties of mental imagery abilities. In this study, we compared the psychophysical properties of the storage and manipulation of lines and complex 3D Tetris shapes. In Experiment 1, participants were required to remember the orientation of both types of stimuli in a classic WM delayed-recall paradigm that varied memory load. Overall recall error was worse for complex 3D shapes than for lines, with increased WM load having a greater effect on precision for the complex shapes. Experiment 2 investigated the effect of manipulating the memory of a single stimulus through mental rotation. During the delay of a single item delayed-response task, participants were cued to either report the stimulus as it was presented (WM condition) or to mentally rotate the stimuli (60° or 120°). The results reveal that for both stimuli, recall error increased as a function of rotation magnitude, paralleling the effects of load in Experiment 1. Interestingly, in both experiments, WM precision as measured by raw error was uncorrelated between stimulus type, suggesting the ability to represent visual information in WM may be stimulus dependent. Moreover, the precision of WM showed no signs of correlation with mental rotation precision, suggesting that these two visual cognitive abilities may be independent, contrary to some theoretical models. Meeting abstract presented at VSS 2018
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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 | 0.000 | 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) | 0.000 | 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".