Nonverbal Communication Processing in Deaf Adults: An Activation Likelihood Estimation Meta-Analysis
Bibliographic record
Abstract
Background/Objectives: Hearing loss affects spoken language processing and leads to cortical reorganization in sensory systems. While neuroimaging research has explored cross-modal plasticity in visual language processing, there is a need to identify brain activation patterns consistently activated across different nonverbal communication tasks in deaf individuals. We hypothesized that deaf adults would show convergent activation across studies in visual and auditory cortices during nonverbal communication processing compared to typical hearing adults. Methods: To test this, we conducted an Activation Likelihood Estimation analysis of 14 neuroimaging studies using different visual linguistic stimuli and tasks in adults with prelingual deafness and age-matched hearing controls. Results: Contrary to expectations, deaf individuals did not show intramodal activation in the visual cortex. Instead, they demonstrated convergence activation in the left superior temporal gyrus only, indicating cross-modal recruitment of auditory regions, which supports visual-spatial language processing. Conclusions: These findings highlight the need for future research to clarify how cortical reorganization impacts speech perception outcomes following auditory restoration using neuroprostheses like cochlear implants.
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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 | 0.015 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.030 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".