The reorganization of extrastriate cortex in patients with lobectomy
Bibliographic record
Abstract
The recovery of perceptual functions that occur following cortical damage can offer key insights into the nature and plasticity of brain organization. In this respect, studies of individuals post-lobectomy/hemispherectomy offer a unique window into the nature and extent of cortical plasticity. First, in contrast with more common lesions, the extent of the damage in such patients can be extreme (i.e. an entire hemisphere in some cases) yet, at the same time, very well controlled - both cortical and subcortical structures of the remaining hemisphere are typically intact. Second, the extent of the recovery is often disproportionate relative to the extent of the damage - many compromised functions are regained partly or even completely. Using fMRI, our present work characterizes the changes in topography in extrastriate cortex in children who have undergone surgical lobectomy or hemispherectomy of ventral cortex in either hemisphere (compared with control participants who have undergone resections to other areas such as dorsal cortex). We also map language areas in each individual as an anchor for hemispheric dominance. We uncover atypicalities in the selectivity maps to common visual categories (face, object, and word) in the ventral patients and show changes in their development/reorganization over time. Overall, the current results suggest that extensive removal of visual cortex lead to atypical/diminished selectivity for common visual categories despite the absence of major recognition difficulties and that, in some cases, reorganization may result in somewhat more typical selectivity maps. Meeting abstract presented at VSS 2015
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".