A single system account of enhanced recognition memory in synaesthesia
Bibliographic record
Abstract
Researchers often adjudicate between models of memory according to the models' ability to explain impaired patterns of performance (e.g., in amnesia). In contrast, evidence from special groups with enhanced memory is very rarely considered. Here, we explored how people with unusual perceptual experiences (synaesthesia) perform on various measures of memory and test how computational models of memory may account for their enhanced performance. We contrasted direct and indirect measures of memory (i.e., recognition memory, repetition priming, and fluency) in grapheme-colour synaesthetes and controls using a continuous identification with recognition (CID-R) paradigm. Synaesthetes outperformed controls on recognition memory and showed a different reaction-time pattern for identification. The data were most parsimoniously accounted for by a single-system computational model of the relationship between recognition and identification. Overall, the findings speak in favour of enhanced processing as an explanation for the memory advantage in synaesthesia. In general, our results show how synaesthesia can be used as an effective tool to study how individual differences in perception affect cognitive functions.
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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) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".