Bibliographic record
Abstract
The study of the neural consequences of sensory loss provides a unique window into the brain's functional and organizational principles. Although the blind visual cortex has been implicated in the cross-modal processing of nonvisual inputs for quite some time, recent research has shown that certain cortical organizational principles are preserved even in the case of complete sensory loss. Furthermore, a growing body of work has shown that markers of neuroplasticity extend to neuroanatomical metrics that include cortical thickness and myelinization. Although our understanding of the mechanisms that underlie sensory deprivation-driven cross-modal plasticity is improving, several critical questions remain unanswered. The specific pathways that underlie the rerouting of nonvisual information, for instance, have not been fully elucidated. The fact that important cross-modal recruitment occurs following transient deprivation in sighted individuals suggests that significant rewiring following blindness may not be required. Furthermore, there are marked individual differences regarding the magnitude and functional relevance of the cross-modal reorganization. It is also not clear to what extent precise environmental factors may play a role in establishing the degree of reorganization across individuals, as opposed to factors that might specifically relate to the cause or the nature of the visual loss. In sum, although many unresolved questions remain, sensory deprivation continues to be an excellent model for studying the plastic nature of the brain. This article is categorized under: Psychology > Brain Function and Dysfunction Psychology > Perception and Psychophysics Neuroscience > Plasticity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".