Brain Resting-State Functional Connectivity Is Preserved Under Sevoflurane Anesthesia in Patients with Pervasive Developmental Disorders: A Pilot Study
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Bibliographic record
Abstract
Functional connectivity studies play a huge role in understanding the relationship between the network connections and the behavioral phenotype of patients with pervasive developmental disorders (PDD). Some patients with PDD may not be able to tolerate the imaging procedure while they are awake, and, hence, they often need general anesthesia. General anesthesia is a confounding factor in functional imaging studies due to its effect on the functional connectivity. The objective of this study is to look at the resting-state functional connectivity (RS-FC) under sevoflurane anesthesia in patients with PDDs. Thirteen adults with PDD scheduled for magnetic resonance imaging (MRI) of the brain under general anesthesia were recruited for the study. Resting-state functional MRI (fMRI) scans were acquired at 1 minimum alveolar concentration (MAC) of sevoflurane. Spontaneous blood oxygenation level-dependent fluctuations were measured, and a seed-voxel analysis was done to identify the resting-state networks. Subjects' data were compared with data from 16 nonanesthetized healthy controls. Six networks (default mode network [DMN], executive control network [ECN], salience network [SN], auditory, visual, and sensorimotor) were investigated. At 1 MAC sevoflurane anesthesia, RS-FC was preserved in all the networks. Secondary analysis of connectivity showed a decrease in connectivity within the thalamus and an increase in DMN-ECN and DMN-SN cross-network connectivity in the anesthetized patient group compared to healthy controls. Previous reports suggested that even mild levels of anesthesia could reduce overall fluctuation levels in the major brain. However, our results provide strong evidence that most networks can sustain detectable levels of activity in patients with PDDs even under deep levels of anesthesia.
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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 | 0.002 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it