Synaesthesia lost and found: two cases of person‐ and music‐colour synaesthesia
Bibliographic record
Abstract
Synaesthesia is a developmental condition involving cross-communication between sensory modalities or substreams whereby an inducer (e.g. a sound) automatically evokes a concurrent percept in another modality (e.g. a colour). Whether this condition arises due to atypical structural connectivity (e.g., between normally unconnected cortical areas) or altered neurochemistry remains a central question. We report the exceptional cases of two synaesthetes - subjects AB and CD - both of whom experience coloured auras around individuals, as well as coloured perceptions in response to music. Both subjects have, in recent years, suffered a complete loss or reduction of their synaesthetic experiences, one (AB) through successive head traumas, including a lightning strike, followed by a number of medications, and the other (CD) while taking anxiolytic medications. Using semi-structured interviews and data from the Synaesthesia Battery and a colourpicker task, we characterize the phenomenological characteristics of their pre-loss synaesthesia, as well as the subsequent restoration of each subject's synaesthetic experiences (in the months post-trauma for AB, and after cessation of medication for CD). Even after years of suppression, the patterns of associations were highly consistent with those experienced pre-injury. The phenomenological experience of synaesthesia can, thus, like most conscious experiences, be modulated by pharmacologically diverse medications or head injury. However, the underlying neural substrates mediating specific synaesthetic pairings appear remarkably 'hard-wired' and can persist over very long periods even under conditions that alter or completely suppress the conscious synaesthetic experience itself.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".