A novel candidate neuromarker of central motor dysfunction in childhood apraxia of speech
Bibliographic record
Abstract
Abstract Childhood apraxia of speech (CAS) is conceived as an impairment of the central motor system’s ability to program multiple speech movements, resulting in inaccurate transitions between and relative timing across speech sounds. However, the extant neuroimaging evidence base is scant and inconclusive and the neurophysiological origins of these motor planning problems remain highly underspecified. In the first magnetoencephalography study of this disorder, we measured brain activity from typically developing children (N = 19) and children with CAS (N=7) during performance of a speech task designed to interrogate function of the speech areas of primary sensorimotor cortex. Relative to their typically developing peers, our sample of CAS children showed abnormal speech-related responses within the mu-band motor rhythm, and beamformer source reconstruction analyses specify a brain origin of this speech rhythm in the left cerebral hemisphere, within or near pre-Rolandic motor areas crucial for the planning and control of speech and oromotor movements. These results provide a new and specific candidate mechanism for the core praxic features of CAS; point to a novel and robust neurophysiological marker of typical and atypical expressive speech development; and support an emerging neuroscientific consensus which assigns a central role for programming and coordination of speech movements to the motor cortices of the precentral gyrus.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".