System for simultaneous measurement of fluorescence and hemodynamics (SSMFH) from deep brain regions of freely moving rodents
Bibliographic record
Abstract
Our understanding of hemodynamic signals, blood perfusion and oxygen saturation (sO2), recorded through fiber-based instruments is limited. To address this, a potential method can be to simultaneously acquire hemodynamic signals with widely used fluorescence fiber photometry signals. We report a novel System for the Simultaneous Measurement of Fluorescence and Hemodynamics (SSMFH) from deep brain regions of freely moving rodents. SSMFH has been developed by modifying our previous white light reflectance single fiber system (SFS) that enabled measurement of blood perfusion and oxygen saturation from freely moving rodents. SSMFH has been designed to be easily integrated with a commercial fluorescence fiber photometry system for time-locked measurement of both hemodynamics and fluorescence signals. SSMFH can be additionally synchronized to behavioral monitoring cameras and other behavioral equipment during experiments. In contrast to previous work in the literature, SSMFH enables hemodynamic recordings from deep brain regions using a wide spectral range (∼ 545nm to 700nm) without the need for injection of an activity-independent fluorescent reporter. The details of the design will be presented along with data to illustrate proof-of-concept through an animal experiment. GCaMP-based fiber photometry and its relation to neuronal activity is well understood. Hemodynamic measurement with simultaneous and co-localized GCaMP based neuronal activity recording can help in understanding variations in in-vivo hemodynamic signals. SSMFH can be used to correct fluorescence measurements which are affected by blood absorption changes.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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".