A slice of π : An exploratory neuroimaging study of digit encoding and retrieval in a superior memorist
Bibliographic record
Abstract
Subject PI demonstrated superior memory using a variant of a Method of Loci (MOL) technique to recite the first digits of the mathematical constant pi to more than 2(16) decimal places. We report preliminary behavioral, functional magnetic resonance imaging (fMRI), and brain volumetric data from PI. fMRI data collected while PI recited the first 540 digits of pi (i.e., during retrieval) revealed increased activity in medial frontal gyrus and dorsolateral prefrontal cortex. Encoding of a novel string of 100 random digits activated motor association areas, midline frontal regions, and visual association areas. Volumetric analyses indicated an increased volume of the right subgenual cingulate, a brain region implicated in emotion, mentalizing, and autonomic arousal. Wechsler Abbreviated Scale of Intelligence (WASI) testing indicated that PI is of average intelligence, and performance on mirror tracing, rotor pursuit, and the Silverman and Eals Location Memory Task revealed normal procedural and implicit memory. PI's performance on the Wechsler Memory Scale (WMS-III) revealed average general memory abilities (50th percentile), but superior working memory abilities (99th percentile). Surprisingly, PI's visual memory (WMS-III) for neutral faces and common events was remarkably poor (3rd percentile). PI's self-report indicates that imagining affective situations and high emotional content is critical for successful recall. We speculate that PI's reduced memory for neutral/non-emotional faces and common events, and the observed increase in volume of the right subgenual cingulate, may be related to extensive practice with memorizing highly emotional material.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".