Miniature device for chronic, label-free multi-modal optical imaging of cortical hemodynamics in rats
Bibliographic record
Abstract
We report on a novel miniature head-mounted imaging system for simultaneous optical recording of brain blood flow and changes in brain blood oxygenation in a rat. Measurements of blood flow speeds are accomplished using Laser Speckle Contrast Imaging (LSCI) technique, while changes in blood oxygenation are measured via Intrinsic Optical Signal Imaging (IOSI) technique. A single multi-wavelength (wavelength = 680, 795, 850 nm) package of vertical cavity surface emitting lasers (VCSELs) is used as the sole brain illumination source. VCSELs enable rapid toggling between wavelengths, and between high-coherence and low-coherence modes, necessary for LSCI and IOSI, respectively. The combination of a miniature light source and a small 10-bit CCD camera sensor lead to a sub-20 g device mass. The miniature imaging system, including the lens, camera, and illumination lasers, is packaged as a module, and is mounted on a chronic implanted observation window that is surgically placed in the skull, allowing for repeated measurements and removal of the imaging system from the rats head after the imaging session. The imaging system allows for a 2mm-diameter field of view and a resolution of 7.4 µm. It will allow neurophysiologists to correlate standard behavioural assays to neurovascular response in animal models, and thus enrich their understanding of neurovascular coupling dynamics of brain disorders and diseases such as stroke and epilepsy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".