Wayfinding in familiar and unfamiliar environments in a case of progressive topographical agnosia
Bibliographic record
Abstract
A 71-year-old right-handed man (F.G.) presents with prosopagnosia and with an inability to recognize famous and familiar buildings. Despite his deficit, F.G. obtained normal scores on neuropsychological tests of executive functions, language, praxis and primary visuoperceptual skills. Brain MRI showed atrophy predominantly in the right temporal lobe, particularly in the fusiform gyrus and the parahippocampal cortex. The present study investigated F.G.'s ability to orient himself in familiar and new environments. His wayfinding abilities in a familiar environment (i.e., his hometown) were preserved despite an inability to recognize familiar and famous buildings, monuments and landmarks in this environment. Wayfinding was achieved through a heavy reliance on written indications (e.g., names of restaurants and streets), preservation of a pre-existing cognitive map of this familiar environment, and normal executive functions necessary to plan the execution of a given trajectory. In an unfamiliar environment, F.G.'s topographical agnosia resulted in severe wayfinding difficulties and in the inability to build an adequate cognitive spatial representation. F.G.'s topographical agnosia results from a high-level visuoperceptual deficit, characterized by an inability to access a global configuration of complex visual stimuli such as familiar and famous monuments, and an over-reliance on the processing of local features.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".