Individual differences in motor development during early childhood: An MEG study
Bibliographic record
Abstract
In a previous study, we reported the first measurements of pre-movement and sensorimotor cortex activity in preschool age children (ages 3-5 years) using a customized pediatric magnetoencephalographic system. Movement-related activity in the sensorimotor cortex differed from that typically observed in adults, suggesting that maturation of cortical motor networks was still incomplete by late preschool age. Here we compare these earlier results to a group of school age children (ages 6-8 years) including seven children from the original study measured again two years later, and a group of adults (mean age 31.1 years) performing the same task. Differences in movement-related brain activity were observed both longitudinally within children in which repeated measurements were made, and cross-sectionally between preschool age children, school age children, and adults. Movement-related mu (8-12 Hz) and beta (15-30 Hz) oscillations demonstrated linear increases in amplitude and mean frequency 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. Notably, pre-movement activity ('readiness fields') observed in adults was absent in even the oldest children. These are the first direct observations of brain activity accompanying motor responses throughout early childhood, confirming that maturation of this activity is still incomplete by mid-childhood. In addition, individual children demonstrated markedly different developmental trajectories in movement-related brain activity, suggesting that individual differences need to be taken into account when studying motor development across age groups.
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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".