Functional-Optical Coherence Tomography: A Non-invasive Approach to Assess the Sympathetic Nervous System and Intrinsic Vascular Regulation
Bibliographic record
Abstract
Sympathetic nervous system dysregulation and vascular impairment in neuronal tissue beds are hallmarks of prominent cardiorespiratory diseases. However, an accurate and convenient method of assessing SNA and local vascular regulation is lacking, hindering routine clinical and research assessments. To address this, we investigated whether spectral domain optical coherence tomography (OCT), that allows investigation of retina and choroid vascular responsiveness, reflects sympathetic activity in order to develop a quick, easy and non-invasive sympathetic index. Here, we compare choroid and retina vascular perfusion density (VPD) acquired with OCT and heart rate variability (HRV) to microneurography. We recruited 6 healthy males (26±3y) and 5 healthy females (23±1y) and instrumented them for respiratory parameters, ECG, blood pressure and muscle sympathetic nerve microneurography. Choroid VPD decreases with the cold pressor test, inhaled hypoxia and breath-hold, and increases with hyperoxia and hyperpnoea suggesting that sympathetic activity dominates choroid responses. In contrast, retina VPD was unaffected by the cold pressor test, increased with hypoxia and breath hold and decreases with hyperoxia and hyperpnoea, suggesting metabolic vascular regulation dominates the retina. With regards to integrated muscle sympathetic nerve activity, HRV had low predictive power whereas choroid VPD was strongly (inversely) correlated with integrated muscle sympathetic nerve activity (R= -0.76; p<0.0001). These data suggest that Functional-OCT may provide a novel approach to assess sympathetic activity and intrinsic vascular responsiveness (i.e. autoregulation). Given that sympathetic nervous system activity is the main determinant of autonomic function, sympathetic excitation is associated with severe cardiovascular/cardiorespiratory diseases and autoregulation is critical for brain health, we suggest that the use of our new Functional-OCT technique will be of broad interest to clinicians and researchers.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".