Comparing Coordinated Networks Across the Brainstem and Spinal Cord in the Resting State and Altered Cognitive State
Bibliographic record
Abstract
Resting-state (RS) functional magnetic resonance imaging (fMRI) has been used to investigate networks of activity within the brain, as well as the brainstem (BS) and spinal cord (SC). While previous research has shown coordinated resting state networks (RSNs) in the BS/SC, their function is still unclear. The aim of this study was to investigate the function of RSNs across these regions, by examining how these networks change when participants are experiencing different cognitive states (RS, listening to an audio presentation, or watching a video). RS blood oxygenation-level dependent fMRI data were obtained from the human cervical SC and BS in 20 healthy participants (14 women, 6 men), at 3 tesla, with T2-weighted single-shot fast spin-echo imaging. Functional connectivity was investigated within the entire three-dimensional region by means of temporal correlations between anatomical regions and by structural equation modeling (SEM). Both correlational analyses and SEM showed extensive connectivity within and across BS and SC regions, and 37% to 40% of significant connections were consistent across study conditions. However, significant differences in connectivity between specific regions of the BS and SC were also identified which depended on the study conditions. The results indicate that connectivity across the RS SC/BS is influenced by a person's cognitive/emotional state. The known anatomical functions of the regions involved support the conclusion that this RS network may play a role in the integration of homeostatic autonomic functions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".