Volume of Left Heschl's Gyrus and Linguistic Pitch Learning
Bibliographic record
Abstract
Research on the contributions of the human nervous system to language processing and learning has generally been focused on the association regions of the brain without considering the possible contribution of primary and adjacent sensory areas. We report a study examining the relationship between the anatomy of Heschl's Gyrus (HG), which includes predominately primary auditory areas and is often found to be associated with nonlinguistic pitch processing and language learning. Unlike English, most languages of the world use pitch patterns to signal word meaning. In the present study, native English-speaking adult subjects learned to incorporate foreign pitch patterns in word identification. Subjects who were less successful in learning showed a smaller HG volume on the left (especially gray matter volume), but not on the right, relative to learners who were successful. These results suggest that HG, typically shown to be associated with the processing of acoustic cues in nonspeech processing, is also involved in speech learning. These results also suggest that primary auditory regions may be important for encoding basic acoustic cues during the course of spoken language learning.
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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".