Superior Parietal Lobule: A Role in Relative Localization of Multiple Different Elements
Bibliographic record
Abstract
Simultanagnosia is an impairment in processing multiple visual elements simultaneously consecutive to bilateral posterior parietal damage, and neuroimaging data have specifically implicated the superior parietal lobule (SPL) in multiple element processing. We previously reported that a patient with focal and bilateral lesions of the SPL performed slower than controls in visual search but only for stimuli consisting of separable lines. Here, we further explored this patient's visual processing of plain object (colored disk) versus object consisting of separable lines (letter), presented in isolation (single object) versus in triplets. Identification of objects was normal in isolation but dropped to chance level when surrounded by distracters, irrespective of eccentricity and spacing. We speculate that this poor performance reflects a deficit in processing objects' relative locations within the triplet (for colored disks), aggravated by a deficit in processing the relative location of each separable line (for letters). Confirming this, performance improved when the patient just had to detect the presence of a specific colored disk within the triplets (visual search instruction), while the inability to identify the middle letter was alleviated when the distracters were identical letters that could be grouped, thereby reducing the number of ways individual lines could be bound.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".