A multimodal neuroimaging study of cerebrovascular regulation: protocols and insights of combining electroencephalography, functional near-infrared spectroscopy, transcranial Doppler ultrasound, and physiological parameters
Bibliographic record
Abstract
Abstract Objective. The current paper describes the creation of a simultaneous trimodal neuroimaging protocol. The authors detail their methodological design for a subsequent large-scale study, demonstrate the ability to obtain the expected physiologically induced responses across cerebrovascular domains, and describe the pitfalls experienced when developing this approach. Approach. Electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), and transcranial Doppler ultrasound (TCD) were combined to provide an assessment of neuronal activity, microvascular oxygenation, and upstream artery velocity, respectively. Real-time blood pressure, capnography, and heart rate were quantified to control for the known confounding influence of cardiorespiratory variables. The EEG-fNIRS-TCD protocol was attached to a 21 year-old male who completed neurovascular coupling/functional hyperemia (finger tapping and ‘Where’s Waldo/Wally?’), dynamic cerebral autoregulation (squat-stand maneuvers), and cerebrovascular reactivity tasks (end-tidal clamping during hypocapnia/hypercapnia). Main results. In a pilot participant, the Waldo task produced robust hemodynamic responses within the occipital microvasculature and the posterior cerebral artery. A ∼90% decrease in alpha band power was seen in the occipital cortical region compared between the eyes closed and eyes opened protocol, compared to the frontal, central, and parietal regions (∼80% reduction). A modest increase in motor oxygenated hemoglobin was seen during the finger tapping task, with a harmonious alpha decrease of ∼15% across all cortical regions. No change in the middle or posterior cerebral arteries were noted during finger tapping. During cerebral autoregulatory challenges, sinusoidal oscillations were produced in hemodynamics at 0.05 and 0.10 Hz, while a decrease and increase in TCD and fNIRS metrics were elicited during hypocapnia and hypercapnia protocols, respectively. Significance. All neuroimaging modalities have their inherent limitations; however, these can be minimized by employing multimodal neuroimaging approaches. This EEG-fNIRS-TCD protocol enables a comprehensive assessment of cerebrovascular regulation across the association between electrical activity and cerebral hemodynamics during tasks with a mild degree of body and/or head movement.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".