Decision letter: Neuronal populations in the occipital cortex of the blind synchronize to the temporal dynamics of speech
Bibliographic record
Abstract
Scientists once thought that certain parts of the brain were hard-wired to process information from specific senses or to perform specific tasks. For example, some had concluded that language processing is built into certain parts of the brain, because the way the brain responds to language is remarkably similar in different people even from very early on in life. Yet other studies with individuals who were born blind emphasize that experience also shapes the way the brain works. In people who are born blind, parts of the brain that typically interpret visual information in sighted people are often put to other uses. Now, van Ackeren et al. show that people who became blind early in life are able to repurpose parts of the brain that are more typically used for vision to understand spoken language instead. A technique called magnetoencephalography was used to map how different parts of the brain respond when both people with sight and those who are blind listen to recordings of someone talking. In some of the experiments, the speech was distorted, making it unintelligible. In both groups, areas of the brain known to process sound information showed patterns of activity that match the rhythms present in the speech. The group with blindness also showed similar activity in parts of the brain usually used to process visual information, and even more so when they were exposed to intelligible speech. The experiments show that brain efficiently reshapes to adapt to a world with no visual input. It may do this by making use of connections that already exist between the auditory and visual brain centers. For instance, very young children use these connections to link what they hear to the lip movements of adults. Future studies are needed to determine if individuals whose ability to see is restored would be able to process the visual information or if the adaptation of the visual processing parts of the brain to help understand speech would interfere with their sight.
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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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.010 | 0.005 |
| Insufficient payload (model declined to judge) | 0.144 | 0.053 |
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".