Systematic Review: Anesthetic Protocols and Management as Confounders in Rodent Blood Oxygen Level Dependent Functional Magnetic Resonance Imaging (BOLD fMRI)—Part B: Effects of Anesthetic Agents, Doses and Timing
Bibliographic record
Abstract
In rodent models the use of functional magnetic resonance imaging (fMRI) under anesthesia is common. The anesthetic protocol might influence fMRI readouts either directly or via changes in physiological parameters. As long as those factors cannot be objectively quantified, the scientific validity of fMRI in rodents is impaired. In the present systematic review, literature analyzing in rats and mice the influence of anesthesia regimes and concurrent physiological functions on blood oxygen level dependent (BOLD) fMRI results was investigated. Studies from four databases that were searched were selected following pre-defined criteria. Two separate articles publish the results; the herewith presented article includes the analyses of 83 studies. Most studies found differences in BOLD fMRI readouts with different anesthesia drugs and dose rates, time points of imaging or when awake status was compared to anesthetized animals. To obtain scientifically valid, reproducible results from rodent fMRI studies, stable levels of anesthesia with agents suitable for the model under investigation as well as known and objectively quantifiable effects on readouts are, thus, mandatory. Further studies should establish dose ranges for standardized anesthetic protocols and determine time windows for imaging during which influence of anesthesia on readout is objectively quantifiable.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".