Inferior Longitudinal Fasciculus’ Role in Visual Processing and Language Comprehension: A Combined MEG-DTI Study
Bibliographic record
Abstract
The inferior longitudinal fasciculus (ILF) is a white matter tract that connects the occipital and the temporal lobes. ILF abnormalities have been associated with deficits in visual processing and language comprehension in dementia patients, thus suggesting that its integrity is important for semantic processing. However, it remains elusive whether ILF microstructural organization per se impacts the visual semantic processing efficiency in the healthy brain. The present study aims to investigate whether there is an association between ILF’s microstructural organization and visual semantic processing at the individual level. We hypothesized that the efficiency of visual semantic processing positively correlates with the degree of anisotropy of the ILF. We studied 10 healthy right-handed subjects. We determined fractional anisotropy (FA) of the ILF using diffusion tensor imaging (DTI). We extracted N400m latency and amplitude from magnetoencephalography (MEG) signals during a visual semantic decision task. N400m and mean FA of the ILF were left lateralized with the higher FA value in the left hemisphere. Inter-individual analysis showed that FA of the ILF negatively correlated with the N400m latency and amplitude, which suggests that high ILF anisotropy is associated with more efficient semantic processing. In summary, our findings provide supporting evidence for a role of the ILF in language comprehension.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".