Long-term stability of physiological signals within fluctuations of brain state under urethane anesthesia
Bibliographic record
Abstract
Project Description: Urethane, an acute laboratory anesthetic, produces distinct neurophysiological and physiological effects creating an effective model of the dynamics of natural sleep. As a model of both sleep-like neurophysiological activity and the downstream peripheral function urethane is used to model a variety of physiological and pathophysiological processes. In this present study, we recorded respiration rate and heart rate concurrently with local field potentials from the neocortex and hippocampus to determine the stability of peripheral physiological functions within and between brain-states under urethane anesthesia. Our data shows electroencephalographic characteristics and breathing rate are remarkable stable over long-term recordings within minor reductions in heart rate on the same time scale. File Description: All files are .dat files extract via MatLab from the raw data recording EEG (electroencephalogram) and physiological signals. The spectral analysis was accomplished using a series of 6-second long, Hanning-windowed samples with a 2-second overlap using Welch’s periodogram method. The first vertical column shows frequency from 0-500 Hz with a resolution of 0.05 Hz. Each subsequent column (starting on column 2) shows the average power (mV^2) of the corresponding row frequency (based on column 1) during a 10 second interval (ie the second column shows average power of all frequencies for the first 10 seconds of the experiment, the third column shows average power during the next 10 seconds, ect.). Four signals were recorded, they are: cortical EEG (CTX), hippocampal EEG (HPC), breathing rate (BR) and heart rate (HR). EEG was recorded via bipolar recording electrodes, the HR was recorded via a pulse transducer, and a thermocouple wire was used to record BR (NOTE: not all experiments have all 4 signals recorded). The files are named in the following fashion: experiment number-recording signal. For example, 1-CTX is the first experiments cortical EEG. Experiments are numbered in the order they were analyzed in and have no significant meaning.
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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 | 0.001 |
| 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) | 0.007 | 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".