A systematic review of altered resting‐state networks in early deafness and implications for cochlear implantation outcomes
Bibliographic record
Abstract
Auditory deprivation following congenital/pre-lingual deafness (C/PD) can drastically affect brain development and its functional organisation. This systematic review intends to extend current knowledge of the impact of C/PD and deafness duration on brain resting-state networks (RSNs), review changes in RSNs and spoken language outcomes post-cochlear implant (CI) and draw conclusions for future research. The systematic literature search followed the PRISMA guideline. Two independent reviewers searched four electronic databases using combined keywords: 'auditory deprivation', 'congenital/prelingual deafness', 'resting-state functional connectivity' (RSFC), 'resting-state fMRI' and 'cochlear implant'. Seventeen studies (16 cross-sectional and one longitudinal) met the inclusion criteria. Using the Crowe Critical Appraisal Tool, the publications' quality was rated between 65.0% and 92.5% (mean: 84.10%), ≥80% in 13 out of 17 studies. A few studies were deficient in sampling and/or ethical considerations. According to the findings, early auditory deprivation results in enhanced RSFC between the auditory network and brain networks involved in non-verbal communication, and high levels of spontaneous neural activity in the auditory cortex before CI are evidence of occupied auditory cortical areas with other sensory modalities (cross-modal plasticity) and sub-optimal CI outcomes. Overall, current evidence supports the idea that moreover intramodal and cross-modal plasticity, the entire brain adaptation following auditory deprivation contributes to spoken language development and compensatory behaviours.
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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 | 0.008 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".