Are Supramodality and Cross-Modal Plasticity the Yin and Yang of Brain Development? From Blindness to Rehabilitation
Bibliographic record
Abstract
Research in blind individuals has primarily focused for a long time on the brain plastic reorganization that occurs in early visual areas. Only more recently, scientists have developed innovative strategies to understand to what extent vision is truly a mandatory prerequisite for the brain’s fine morphological architecture to develop and function. As a whole, the studies conducted to date in sighted and congenitally blind individuals have provided ample evidence that several ‘visual’ cortical areas develop independently from visual experience and do process information content regardless of the sensory modality through which a particular stimulus is conveyed: a property named supramodality. At the same time, lack of vision leads to a structural and functional reorganization within 'visual' brain areas, a phenomenon known as cross-modal plasticity. Cross-modal recruitment of the occipital cortex in visually deprived individuals represents an adaptative compensatory mechanism that mediates processing of non-visual inputs. Supramodality and cross-modal plasticity appear to be the 'yin and yang' of brain development: supramodal is what takes place despite the lack of vision, whereas cross-modal is what happens because of lack of vision. Here we provide a critical overview of the research in this field and discuss the implications that these novel findings have for the development of educative/rehabilitation approaches and sensory substitution devices in sensory-impaired individuals.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".