Beta synchrony for expressive language lateralizes to right hemisphere in development
Bibliographic record
Abstract
A left perisylvian network is known to support language in healthy adults. Low-beta (13-23 Hz) event-related desynchrony (ERD) has been observed during verb generation, at approximately 700-1200 ms post-stimulus presentation in past studies; the signal is known to reflect increased neuronal firing and metabolic demand during language production. In contrast, concurrent beta event-related synchrony (ERS) is thought to reflect neuronal inhibition but has not been well studied in the context of language. Further, while low-beta ERD for expressive language has been found to gradually shift from bilateral in childhood to left hemispheric by early adulthood, developmental lateralization of ERS has not been established. We used magnetoencephalography to study low beta ERS lateralization in a group of children and adolescents (n = 78), aged 4 to less than 19 years, who performed covert verb generation. We found that the youngest children had bilateral ERD and ERS. By adolescence, low-beta ERD was predominantly left lateralized in perisylvian cortex (i.e., Broca's and Wernicke's regions), while beta ERS was predominantly right lateralized. Increasing lateralization was significantly correlated to age for both ERD (Spearman's r = 0.45, p < 0.01) and ERS (Spearman's r = - 0.44, p < 0.01). Interestingly, while ERD lateralized in a linear manner, ERS lateralization followed a nonlinear trajectory, suggesting distinct developmental trajectories. Implications to early-age neuroplasticity and neuronal inhibition are discussed.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".