A rare case of bilateral damage to cortical motion processing areas 40 years after patient L.M.
Bibliographic record
Abstract
In 1983, Zihl and colleagues reported the case of patient L.M., who had suffered bilateral damage to the lateral temporal-occipital cortex and showed a “disturbance of movement vision in a rather pure form” [Zihl, von Cramon, & Mai, Brain 1983; p.313], manifesting in selective deficits in motion perception, smooth pursuit and manual tracking of moving targets, particularly at higher speeds. These findings suggest that a human homologue of the middle temporal area (MT, or area V5) was located in this region. Here we present 19-year-old female patient C.C., who suffered encephalitis at age 3, with recent MRI showing bilateral damage to lateral occipitotemporal and medial occipitoparietal cortex. Similar to L.M., patient C.C. reports feeling overwhelmed in crowded areas, struggling with ball sports, and inaccuracy with fine motor tasks that involve moving objects. We tested C.C.’s smooth pursuit eye movements to visible and occluded targets and her ability to track and rapidly intercept objects that moved unpredictably. Compared to healthy young adults, C.C.’s smooth pursuit had a reduced velocity gain (.75) and was frequently interrupted by catch-up saccades, even in response to slow (10°/s) targets. When the target was temporarily occluded (ramp-occlusion-ramp for 800 ms each), pursuit dropped to zero velocity during occlusion and did not predictively accelerate before target reappearance. These motion prediction deficits extended to the patient’s performance in naturalistic interception tasks. Whereas pointing accuracy was high (interception error 0.8°) for objects moving along simple, horizontal trajectories, performance degraded significantly for complex flyball (M = 2.4°) and occluded trajectories (M = 3.6°) with almost no ability to discriminate different trajectory types. These findings provide neuropsychological evidence for a role of C.C.’s damaged areas in the control of predictive eye and hand movements to moving objects and show that there is little compensation for these deficits.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".