Developmental Changes in Movement Related Brain Activity in Early Childhood
Bibliographic record
Abstract
In a previous MEG study of movement-related brain activity in preschool age children, we reported that pre-movement fields and sensorimotor cortex oscillations differed from those typically observed in adults, suggesting that maturation of cortical motor networks is still incomplete by late preschool age (Cheyne et al., 2014). Here we describe the same measurements in an older group of school-aged children (6 to 8 years old) and an adult control group, in addition to repeated recordings in seven children from the original study approximately two years later. Differences were observed both longitudinally within children and between age groups. Pre-movement (readiness) fields were still not present in the oldest children, however both frequency and magnitude of movement-related mu (8-12Hz) and beta (15-30Hz) oscillations demonstrated linear increases with age. In contrast, movement-evoked gamma synchronization demonstrated a step-like transition from low (30-50 Hz) to high (70-90 Hz) narrow-band oscillations, and this occurred at different ages in different children. These data provide novel evidence of linear and non-linear changes in motor cortex oscillations and delayed development of the readiness field throughout early childhood. Individual children showed large differences in maturation of movement-related brain activity, possibly reflecting differing rates of motor development.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".