A study of brain white matter plasticity in early blinds using tract-based spatial statistics and tract statistical analysis
Bibliographic record
Abstract
Early blind individuals are known to exhibit structural brain reorganization. Particularly, early-onset blindness may trigger profound brain alterations that affect not only the visual system but also the remaining sensory systems. Diffusion tensor imaging (DTI) allows in-vivo visualization of brain white matter connectivity, and has been extensively used to study brain white matter structure. Among statistical approaches based on DTI, tract-based spatial statistics (TBSS) is widely used because of its ability to automatically perform whole brain white matter studies. Tract specific analysis (TSA) is a more recent method that localizes changes in specific white matter bundles. In the present study, we compare TBSS and TSA results of DTI scans from 12 early blind individuals and 13 age-matched sighted controls, with two aims: (a) to investigate white matter alterations associated with early visual deprivation; (b) to examine the relative sensitivity of TSA when compared with TBSS, for both deficit and hypertrophy of white matter microstructures. Both methods give consistent results for broad white matter regions of deficits. However, TBSS does not detect hypertrophy of white matter, whereas TSA shows a higher sensitivity in detecting subtle differences in white matter colocalized to the posterior parietal lobe.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".