Functional Identification of Distinct Subpopulations of PreBötzinger Complex Neurons Regulating Separate Respiratory Motor Outputs
Bibliographic record
Abstract
Rationale Breathing is an autonomic behaviour generated by a complex respiratory network in the brainstem. At its core is the preBötzinger Complex (preBötC), a population of neurons producing rhythmic breathing by activating respiratory muscles. The preBötC contains interneurons generating rhythmic respiratory activity, but also preBötC neurons that project to the hypoglossal premotor area, and then to the motor pool to activate the genioglossus muscle, an important upper airway respiratory muscle. The preBötC therefore regulates two distinct components of respiratory activity: rhythmic breathing and upper airway muscle activity. The anatomical organization of preBötC neurons is complex. The inhibitory peptide somatostatin (SST) is found in small fusiform interneurons expressing neurokinin‐1 receptors (small NK‐1R/SST neurons). SST is also co‐expressed with NK‐1Rs in medium‐size neurons that project to the hypoglossal premotor neurons (medium NK‐1R/SST neurons). A subpopulation of large multipolar preBötC neurons express NK‐1R, but not SST (NK‐1R neurons). The functional roles of these three subpopulations in mediating rhythmic breathing and upper airway muscle activity are unknown. Furthermore, NK‐1R and SST receptors can excite or inhibit neuronal activity through G‐protein‐gated inwardly rectifying potassium (GIRK) channels, but the contribution of these channels to SST and NK‐1R modulation of rhythmic breathing and upper airway muscle activity is not known. Objectives Here, we propose that GIRK channels play distinct functional roles in these three subpopulations of preBötC neurons. To test this claim, we probed the contributions of SST, NK‐1Rs and GIRK channels to rhythmic breathing and genioglossus muscle activity. Methods We microperfused selected agents into the preBötC of adult anesthetized rats and mice (wild‐type and GIRK2 subunit knockout; GIRK2 −/− ) while recording diaphragm and genioglossus muscle activity. Results SST (200 μM) decreased rhythmic breathing and genioglossus muscle activity. SST inhibition of rhythmic breathing, but not genioglossus muscle activity, was blocked by the SST 2A receptor antagonist CYN‐154806 (20 μM). The NK‐1R agonist GR73632 (50 μM) increased rhythmic breathing and genioglossus muscle activity. GIRK channel activation by flupirtine (100 μM) decreased rhythmic activity and genioglossus muscle activity in adult rats and wild‐type mice, but not in GIRK2 − / − mice, suggesting that GIRK channels contribute to NK‐1R excitation. On the other hand, SST inhibition of rhythmic breathing was not blocked by the GIRK channel blocker Tertiapin Q (1 μM) and SST inhibition was observed both in wild‐type and GIRK2 −/− mice. Discussion NK1‐Rs regulate rhythmic breathing by acting through GIRK channels likely in small NK‐1R/SST neurons, and increase genioglossus muscle activity through GIRK channels possibly in large NK‐1R neurons. SST inhibits medium‐size NK‐1R/SST neurons and therefore reduce rhythmic breathing and genioglossus muscle activity through an unknown GIRK‐independent mechanism. Here, the functional roles of specific subpopulations of preBötC neurons were dissected by identifying the contribution of GIRK channels to two distinct respiratory behaviors. Support or Funding Information G.M. was supported by a Parker B. Francis Fellowship. R.L.H was supported by a Tier 1 Canada Research Chair. This research was supported by the Canadian Institutes for Health Research (R.L.H.), the National Sanitarium Association Innovative Research Program (R.L.H.), and Canadian Institutes of Health Research (R.L.H.).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".