Forebrain organization representing baroreceptor gating of somatosensory afferents within the cortical autonomic network
Bibliographic record
Abstract
Somatosensory afferents are represented within the cortical autonomic network (CAN). However, the representation of somatosensory afferents, and the consequent cardiovascular effects, may be modified by levels of baroreceptor input. Thus, we examined the cortical regions involved with processing somatosensory inputs during baroreceptor unloading. Neuroimaging sessions (functional magnetic resonance imaging [fMRI]) recorded brain activity during 30 mmHg lower-body negative pressure (LBNP) alone and combined with somatosensory stimulation (LBNP+SS) of the forearm (n = 14). Somatosensory processing was also assessed during increased sympathetic outflow via end-expiratory apnea. Heart rate (HR), blood pressure (BP), cardiac output (Q), and muscle sympathetic nerve activity (MSNA) were recorded during the same protocols in a separate laboratory session. SS alone had no effect on any cardiovascular or MSNA variable at rest. Measures of HR, BP, and Q during LBNP were not different compared with LBNP+SS. The rise in MSNA burst frequency was attenuated during LBNP+SS versus LBNP alone (8 vs. 12 bursts/min, respectively, P < 0.05). SS did not affect the change in MSNA during apnea. Activations within the insula and dorsal anterior cingulate cortex (ACC) observed during LBNP were not seen during LBNP+SS. Anterior insula and ACC activations occurring during apnea were not modified by SS. Thus, the absence of insular and dorsal ACC activity during LBNP+SS along with an attenuation of MSNA burst frequency suggest sympathoinhibitory effects of sensory stimulation during decreased baroreceptor input by a mechanism that includes conjoint insula-dorsal ACC regulation. These findings reveal that the level of baroreceptor input influences the forebrain organization of somatosensory afferents.
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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 | 0.000 |
| 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) | 0.003 | 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".