<i>DeepPhysioRecon</i>: Tracing peripheral physiology in low frequency fMRI dynamics
Bibliographic record
Abstract
Abstract Many studies of the human brain using functional magnetic resonance imaging (fMRI) lack physiological measurements, which substantially impacts the interpretation and richness of fMRI studies. Natural fluctuations in autonomic physiology, such as breathing and heart rate, provide windows into critical functions, including cognition, emotion, and health, and can heavily influence fMRI signals. Here, we developed DeepPhysioRecon, a Long-Short-Term-Memory (LSTM)-based network that decodes continuous variations in respiration amplitude and heart rate directly from whole-brain fMRI dynamics. Through systematic evaluations, we investigate the generalizability of this approach across datasets and experimental conditions. We also demonstrate the importance of including these measures in fMRI analyses. This work highlights the importance of studying brain-body interactions, proposes a tool that may enhance the efficacy of fMRI as a biomarker, and provides widely applicable open-source software.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".