Rapid monitoring of cerebral ischemia dynamics using laser-based optical imaging of blood oxygenation and flow
Bibliographic record
Abstract
Imaging blood flow or oxygenation changes using optical techniques is useful for monitoring cortical activity in healthy subjects as well as in diseased states such as stroke or epilepsy. However, in order to gain a better understanding of hemodynamics in conscious, freely moving animals, these techniques must be implemented in a small scale, portable design that is adaptable to a wearable format. We demonstrate a novel system which combines the two techniques of laser speckle contrast imaging and intrinsic optical signal imaging simultaneously, using compact laser sources, to monitor induced cortical ischemia in a full field format with high temporal acquisition rates. We further demonstrate the advantages of using combined measurements of speckle contrast and oxygenation to establish absolute flow velocities, as well as to statistically distinguish between veins and arteries. We accomplish this system using coherence reduction techniques applied to Vertical Cavity Surface Emitting Lasers (VCSELs) operating at 680, 795 and 850 nm. This system uses minimal optical components and can easily be adapted into a portable format for continuous monitoring of cortical hemodynamics.
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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 | 0.000 |
| 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) | 0.001 | 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".