Alteration Functional and Effective Connectivity Between Visual and Attention-Networks in Cognitively Impaired Patients With Temporal Lobe Epilepsy
Bibliographic record
Abstract
Abstract Purpose: This paper examines the changes in functional connectivity (FC) and effective connectivity (EC) of the visual (VIS)-network and attention network (AN) in patients with cognitive impairment caused by temporal lobe epilepsy (CI-TLE) through independent component analysis (ICA) and Granger causality analysis (GCA).Material and methods: Resting-state functional magnetic resonance imaging（rs-fMRI）data and Montreal cognitive assessment（CoMA） were collected from 32 patients with CI-TLE and 29 age-matched healthy controls.Results: In the VIS network of CI-TLE patients, FC decreased in the right inferior occipital gyrus (IOG) and the left lingual gyrus (LG) and in the right temporal-parietal junction (TPJ) in the Doral attention network (DAN). FC increased in the right middle frontal gyrus (MFG) and right precuneus gyrus (PG). In the DAN, FC decreased in the left superior parietal gyrus (SPG) and right inferior parietal gyrus (LG). GCA revealed the decreased EC from the left LG to the right IOG within the VIS network and from the right inferior parietal gyrus (IPG) of the DAN to the left LG of the VIS network. In contrast, CI-TLE patients demonstrated increased EC from the right SPG to the right IPG within DAN，and from the right IPG of the DAN to the right TPJ of the VAN, and from the right TPJ to the left PG within VAN. Compared with healthy controls , Voxel-wise GCA in CI-TLE patients showed positive EC from the left LG to the right SPG. In contrast, increased EC was exhibited from the right TPJ to the right caudate. Pearson analysis showed a negative correlation between the CoMA scores and GC values from the right IPG to the right TPJ.Conclusion: The results indicate intrinsic brain network connectivity dysfunction in CI-TLE patients and the causal connection abnormality in the resting-state VIS network and AN. Also, it was found that CI-TLE patients possibly have a compensatory mechanism in the above networks. These findings shed new insights on the neuroimaging marker of CI-TLE.
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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 | 0.001 | 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) | 0.001 | 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".