Distinct Structural Connectivity Patterns Associated with Variations in Language Lateralisation
Bibliographic record
Abstract
Abstract Hemispheric asymmetries in white matter tracts are proposed key determinants of language lateralisation, yet evidence in healthy individuals remains inconsistent. This suggests that simple tractography techniques might not be sensitive enough to identify language dominance. Significant insights into the functional organization of the human brain may be achieved by considering networks and brain connectivity, providing more information about discrepancies in people with different hemispheric language dominance. In this study, we examined 285 healthy participants compare their structural connectomes at the whole-brain level and determine the networks responsible for the three different functional language lateralisation groups (typical, atypical and strongly atypical). Probabilistic tractography generated whole-brain tractograms, and white matter fibres were filtered according to anatomical Boolean guidelines. Connectivity matrices with nodes corresponding to supramodal sentence areas in the language atlas and edges weighted by fractional anisotropy (FA) were generated to compare the groups using graph theory and network-based statistic (NBS) approaches. We demonstrated that both atypical (bilateral) and strongly atypical (right-lateralised) lateralisation are characterised by heightened interhemispheric temporal connectivity. Post-hoc analyses showed that strongly atypical individuals exhibited increased temporo-frontal connectivity, while atypical individuals had enhanced temporal and frontal connectivity but lacked temporo-frontal connections. These connectivity patterns diverge from traditional models of hemispheric dominance, suggesting a reliance on integrated bilateral networks in atypically lateralised individuals. This reflects distinct neural mechanisms underlying atypical language organisation, departing from developmental trajectory of typical lateralisation and offering insights into cognitive flexibility and clinical applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".