Bibliographic record
Abstract
The field of the neurobiology of language is experiencing a paradigm shift in which the predominant Broca-Wernicke-Geschwind language model is being revised in favor of models that acknowledge that language is processed within a distributed cortical and subcortical system. While it is important to identify the brain regions that are part of this system, it is equally important to establish the anatomical connectivity supporting their functional interactions. The most promising framework moving forward is one in which language is processed via two interacting "streams"--a dorsal and ventral stream--anchored by long association fiber pathways, namely the superior longitudinal fasciculus/arcuate fasciculus, uncinate fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, and two less well-established pathways, the middle longitudinal fasciculus and extreme capsule. In this article, we review the most up-to-date literature on the anatomical connectivity and function of these pathways. We also review and emphasize the importance of the often overlooked cortico-subcortical connectivity for speech via the "motor stream" and associated fiber systems, including a recently identified cortical association tract, the frontal aslant tract. These pathways anchor the distributed cortical and subcortical systems that implement speech and language in the human brain.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".