Resting-state functional MRI of the visual system for characterization of optic neuropathy
Bibliographic record
Abstract
Optic neuropathy refers to disease of the optic nerve and can result in loss of visual acuity and/or visual field defects. Combining findings from multiple fMRI modalities can offer valuable information for characterizing and managing optic neuropathies. In this article, we review a subset of resting-state functional magnetic resonance imaging (RS-fMRI) studies of optic neuropathies. We consider glaucoma, acute optic neuritis (ON), discuss traumatic optic neuropathy (TON), and explore consistency between findings from RS and visually driven fMRI studies. Consistent with visually driven studies, glaucoma studies at rest also indicated reduced activation in the visual cortex and dorsal visual stream. RS-fMRI further reported varying levels of functional connectivity in the ventral stream depending on disease severity. ON patients show alterations within the visual cortex in both fMRI techniques. Particularly, higher-than-normal RS activity is observed in the acute phase and decreases as the disease progresses. A similar pattern is observed in the visual cortex of TON-like, open globe injury (OGI), patients. Additionally, visually driven and RS-fMRI studies of ON patients show recovery of brain activity in the visual cortex. RS-fMRI suggests recovery of signals in higher-tier visual areas MT and LOC as well. Finally, RS-fMRI has not yet been applied to TON, although reviewing OGI studies suggests that it is feasible. Future RS-fMRI studies of optic neuropathies could prioritize studying the fine scale RS activity of brain areas that visually driven studies have identified. We suggest that a more systematic longitudinal comparison of optic neuropathies with advanced fMRI would provide improved diagnostic and prognostic information.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".