A novel protocol for magnetoencephalographic mapping of speech motor control regions during speech production
Bibliographic record
Abstract
Abstract Neuroimaging protocols for mapping of expressive speech centres employ several standard speech tasks including object naming, rhyming, and covert word production (Agarwal et al., 2019). These tasks reliably elicit activation of distributed speech centres in prefrontal, precentral and cingulate motor cortices and are widely used for presurgical mapping and in research studies of language production. In the present study we used an alternative speech protocol employing reiterated productions of simple disyllabic nonwords (VCV; Anastasopoulou et al., 2022; van Lieshout et al., 2007). Here we show that this task elicits highly focal and highly lateralised activations of speech motor control areas centred on the precentral gyrus and adjacent portions of the middle frontal gyrus. 10 healthy adults, 19 typically developing children and 7 children with CAS participated in the study. MEG scans were carried out with a whole-head MEG system consisting of 160 first-order axial gradiometers with a 50 mm baseline (Model PQ1160R-N2, KIT, Kanazawa, Japan). MEG data were acquired with analog filter settings of 0.03 Hz high-pass, 1,000 Hz low-pass, 4,000 Hz sampling rate. Measurements were carried out with participants in supine position in a magnetically shielded room (Fujihara Co. Ltd., Tokyo, Japan). Time-aligned speech acoustics were recorded in an auxiliary channel of the MEG setup at the same sample rate as the MEG recordings. Brain activity was recorded while participants produced reiterated utterances of /ipa/ and /api/, at normal and speeded rates in addition to a button press task (right index finger) to elicit activity in the hand region of sensorimotor cortex (e.g. Johnson et al., 2020). MEG data were co-registered with individual structural MRI scans obtained in a separate scanning session. Source reconstruction was performed with synthetic aperture magnetometry (SAM) beamformer implemented in Matlab (Jobst et al., 2018) and group statistics performed with permutation tests (p < 0.05). Button press map shows clusters encompassing dorsal precentral and postcentral gyri (Brodmann areas 4 and 6), corresponding to hand sensorimotor cortices. Speech map shows clusters encompassing precentral gyrus immediately ventral to hand motor cortex (BA6), and an immediately adjacent portion of the posterior middle frontal gyrus. Both button press and speech result in a robust desynchronisation restricted within a frequency band of about 13-30 Hz (beta band). Our results show that the reiterated speech task results in robust beta-band desynchronisation in a highly focal region of the precentral gyrus, located immediately ventral to the hand motor region of the precentral gyrus. In adults, speech motor -related brain activity was predominantly observed in the left hemisphere. Typically developing children, on the other hand, exhibited bilateral activation and in the case of individuals with CAS exhibited only right-hemisphere activation. Taken together the present findings provide a non-invasive and highly selective window on a crucial node of the expressive speech network that has previously been accessed only with invasive electrophysiological means and lesion studies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".