The Neuroanatomy of Speech Sequencing at the Syllable Level
Bibliographic record
Abstract
Correctly ordering a sequence of speech sounds is a crucial aspect of speech production. Although studies have yielded a rich body of data on the neural substrates of visuomotor sequencing and sequence learning, research on brain regions and their functions involving speech sequence production hasn’t attracted much attention until recently. Previous functional MRI studies manipulating the complexity of sequences at the phonemic, syllabic, and suprasyllabic levels have revealed a network of motor-related cortical and sub-cortical speech regions. In this study, we directly compared human brain activity measured with functional MRI during processing of a sequence of syllables compared with the same syllables processed individually. Among a network of regions independently identified as being part of the sensorimotor circuits for speech production, only the left posterior inferior frontal gyrus (pars opercularis, lIFG), the supplementary motor area (SMA), and the left inferior parietal lobe (lIPL) responded more during the production of syllable sequences compared to producing the same syllables articulated one at a time.
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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 | 0.000 |
| 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".