Rapid recovery from cortical visual impairment in a pediatric patient following vision training: A case study
Bibliographic record
Abstract
Background. Cortical visual impairment (CVI) is a severe loss of visual function caused by damage to the visual cortex or its afferents, usually as a consequence of stroke or hypoxic insult. It is one of the leading causes of vision loss in children. Objective. Several studies have demonstrated limited vision restoration in adult CVI patients who trained on well-controlled psychophysical tasks involving complex motion stimuli. Given the greater potential for plasticity in the young brain, we hypothesized that similar vision training would be more effective in young patients. Methods. To test this hypothesis, we conducted a proof-of-principle study in one young CVI patient (age 18), to test the training speed, efficacy and generalizability of vision rehabilitation using complex motion stimuli. The patient trained at home and in the laboratory, on a psychophysical task that required discrimination of motion stimuli presented in the blind field. Visual function was assessed before and after training, using perimetric measures, as well as a battery of psychophysical tests. Results. The patient showed rapid improvements on the training task, with performance going from chance to 80% correct over the span of 11 sessions. With further training, improved vision was found for untrained stimuli and for perimetric measures of visual sensitivity. Some, but not all, of these performance gains were retained upon retesting after one year. Conclusion. These results suggest that existing vision rehabilitation programs can be highly effective in pediatric patients. Validation with a large sample size is critical, and future work should also focus on improving the usability and accessibility of these programs for young patients.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| 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".