Audiovisual integration in children with cochlear implants revealed through EEG and fNIRS
Classification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sensory deprivation can offset the balance of audio versus visual information in multimodal processing. Such a phenomenon could persist for children born deaf, even after they receive cochlear implants (CIs), and could potentially explain why one modality is given priority over the other. Here, we recorded cortical responses to a single speaker uttering two syllables, presented in audio-only (A), visual-only (V), and audio-visual (AV) modes. Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) were successively recorded in seventy-five school-aged children. Twenty-five were children with normal hearing (NH) and fifty wore CIs, among whom 26 had relatively high language abilities (HL) comparable to those of NH children, while 24 others had low language abilities (LL). In EEG data, visual-evoked potentials were captured in occipital regions, in response to V and AV stimuli, and they were accentuated in the HL group compared to the LL group (the NH group being intermediate). Close to the vertex, auditory-evoked potentials were captured in response to A and AV stimuli and reflected a differential treatment of the two syllables but only in the NH group. None of the EEG metrics revealed any interaction between group and modality. In fNIRS data, each modality induced a corresponding activity in visual or auditory regions, but no group difference was observed in A, V, or AV stimulation. The present study did not reveal any sign of abnormal AV integration in children with CI. An efficient multimodal integrative network (at least for rudimentary speech materials) is clearly not a sufficient condition to exhibit good language and literacy.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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 it