Changes in White Matter Integrity following Intensive Voice Treatment (LSVT LOUD®) in Children with Cerebral Palsy and Motor Speech Disorders
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
Preliminary evidence suggests that intensive voice and speech treatment based on activity-dependent neuroplasticity principles holds promise for affecting positive change in children with cerebral palsy (CP) and motor speech disorders. Diffusion tensor imaging (DTI) allows researchers to make inferences about the integrity of white matter tracks and provides a sensitive measure of neuroplasticity. Previous treatment studies looking at the effects of training on white matter integrity have shown positive results, but these studies have been limited to gross motor function. Eight children with motor speech disorders and CP (3 females; age 8-16 years) and an age- and sex-matched group of typically developing (TD) children participated. Each child with CP completed a full dose of LSVT LOUD® and a 12-week maintenance program. Participants attended 3 recording sessions: before and after treatment, and after the maintenance period. TD children were tested at the same 3 time points. Recording sessions for both groups of children included measures of white matter integrity using DTI and acoustic measures of voice and speech. Fractional anisotropy (FA) was measured for 2 motor tracts and 5 association tracts. In children with CP, we observed an increase in FA in several motor and association tracts immediately following treatment and 12 weeks after treatment. Acoustic data on untrained tasks were correlated with changes in FA detected immediately following treatment and after the 12-week maintenance program. These findings suggest that long-term practice of skills attained during the treatment phase enhances white matter tract integrity in speech production networks.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it