Reflections on blindsight: Neuroimaging and behavioural explorations clarify a case of reversed localisation in the blind field of a patient with hemianopia.
Bibliographic record
Abstract
Blindsight refers to residual visual abilities of patients with primary visual cortex lesions. Most of this research uses single case studies, most famously patient GY. We examined a patient (DC) after surgical resection of V1 who demonstrated robust but reversed blind field target localisation, mislocalising midline blind field targets to the periphery and vice versa. This pattern was reliable across multiple sessions and was not because of extraocular light scatter. We then used functional magnetic resonance imaging to examine neural responses to blind field motion stimuli with no evidence of motion-selective activation in DC's extrastriate cortex in the damaged hemisphere, in stark contrast to GY who showed robust bilateral activation in response to blind field stimuli. This suggests that DC's blind field performance may not represent true blindsight. Follow-up testing with the target--background contrast reversed (i.e., black targets/white background), eliminated DC's reversed localisation, strongly suggesting that she was employing an unusual decision criterion based on intraocular light scatter. DC's failure to demonstrate true blindsight may be related to the age at which she acquired her lesion--much later in life than GY.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".