Beyond the arcuate fasciculus: consensus and controversy in the connectional anatomy of language
Bibliographic record
Abstract
The growing consensus that language is distributed into large-scale cortical and subcortical networks has brought with it an increasing focus on the connectional anatomy of language, or how particular fibre pathways connect regions within the language network. Understanding connectivity of the language network could provide critical insights into function, but recent investigations using a variety of methodologies in both humans and non-human primates have provided conflicting accounts of pathways central to language. Some of the pathways classically considered language pathways, such as the arcuate fasciculus, are now argued to be domain-general rather than specialized, which represents a radical shift in perspective. Other pathways described in the non-human primate remain to be verified in humans. In this review, we examine the consensus and controversy in the study of fibre pathway connectivity for language. We focus on seven fibre pathways-the superior longitudinal fasciculus and arcuate fasciculus, the uncinate fasciculus, extreme capsule, middle longitudinal fasciculus, inferior longitudinal fasciculus and inferior fronto-occipital fasciculus-that have been proposed to support language in the human. We examine the methods in humans and non-human primate used to investigate the connectivity of these pathways, the historical context leading to the most current understanding of their anatomy, and the functional and clinical correlates of each pathway with reference to language. We conclude with a challenge for researchers and clinicians to establish a coherent framework within which fibre pathway connectivity can be systematically incorporated to the study of language.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.016 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".