Functional neuroimaging and behavioural classification of a case of prosopagnosia with classic bilateral occipitotemporal lesions
Bibliographic record
Abstract
Background: The classic cases of prosopagnosia described by Meadows (1974) and Damasio et al (1982) had bilateral medial occipitotemporal lesions. While cases with right-sided lesions have been described since, the impact of such classic lesions on the face network and various aspects of face processing are unknown. Objective: We studied a patient with bilateral occipitotemporal infarcts including both middle fusiform gyri, to determine the impact of the lesions upon the face processing network on functional MRI, correlate this with results on a behavioural battery, and compare these to prior subjects with unilateral lesions affecting the right fusiform face area (FFA) and/or occipital face area (OFA). Methods: We used the dynamic face localizer in functional MRI to characterize the core face processing network. In a perceptual battery, we evaluated face recognition, face perception, face imagery, and semantic knowledge about famous people. The subject had an event-related potential study of the face-selective N170. Results: There was no activation of either right or left FFA, or left OFA, but sparing of both pSTS (posterior superior temporal sulci). He was severely impaired in discrimination of facial configuration and features, and impaired in car and handwriting recognition. He performed normally on face imagery and semantic knowledge of famous people. There was no face-selectivity in the right N170 response, and in fact showed a larger left N170 response to objects than faces. Compared to R-IOT4, who had a lesion of the right FFA, he had more difficulty with same-view matching of faces, and other within-class object recognition. Conclusions: The bilateral medial occipitotemporal variant of prosopagnosia, with loss of both FFA and the left OFA, is associated with severe deficits in processing facial structure, associated recognition impairments for other object classes, as well as loss of the N170 response in the right hemisphere. Meeting abstract presented at VSS 2013
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".