Functional segregation of cortical hand and speech areas by frequency detuning of an intrinsic motor rhythm
Bibliographic record
Abstract
ABSTRACT Many decades after Penfield’s (1937) classic depiction of the motor homunculus, it remains unclear how spatially contiguous and interconnected representations within human sensorimotor cortex might separate their activities to achieve the directed and precise control of distinct body regions evident in activities as different as typing and speaking. One long-standing but relatively neglected explanation draws from models of simple physical systems (like swinging pendulums) to posit that small differences in the oscillatory properties of neuronal populations (termed “frequency detuning”) can result in highly effective segregation of their activities and outputs. We tested this hypothesis by comparing the peak frequencies of beta-band (13-30 Hz) motor rhythms measured in a magnetoencephalographic neuroimaging study of finger and speech movements in a group of healthy adults and a group of typically developing children. Our results confirm a peak frequency task difference of about 1.5 Hz in the beta motor rhythms of both left and right hemispheres in adults. A comparable task difference was obtained in children for the left but not for the right hemisphere. These results provide novel support for the role of frequency detuning in the functional organisation of the brain and suggest that this mechanism should play a more prominent role in current models of bodily representations and their development within the sensorimotor cortex. NEW & NOTEWORTHY This work is the first evidence for frequency detuning of an intrinsic motor rhythm in spatially contiguous regions of primary motor cortex associated with hand and speech movements, supporting a mechanism of functional segregation that has been largely overlooked by current models of motor cortex organization. Our results from children further provide the first evidence for frequency detuning in the developing brain, indicating an early-developing mechanism with later refinements of hemispheric control.
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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 | 0.000 | 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) | 0.002 | 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".