Dopaminergic signaling to ventral striatum neurons initiates sniffing behavior
Bibliographic record
Abstract
Sniffing is a motivated behavior displayed by nearly all terrestrial vertebrates. While sniffing is associated with acquiring and processing odors, sniffing is also intertwined with affective and motivated states. The systems which influence the display of sniffing are unclear. Here, we report that dopamine release into the ventral striatum in mice is coupled with bouts of sniffing and that stimulation of dopaminergic terminals in these regions drives increases in respiratory rate to initiate sniffing whereas inhibition of these terminals reduces respiratory rate. Both the firing of individual neurons and the activity of post-synaptic D1 and D2 dopamine receptor-expressing neurons are coupled with sniffing and local antagonism of D1 and D2 receptors squelches sniffing. Together, these results support a model whereby sniffing can be initiated by dopamine’s actions upon ventral striatum neurons. The nature of sniffing being integral to both olfaction and motivated behaviors implicates this circuit in a wide array of functions. Neural circuitry mechanism which invigorates an animal to go from basal breathing which serves the purpose of gas exchange, to engage in the voluntary act of sniffing is not fully understood. These results from Johnson and colleagues support a model whereby sniffing can be initiated by dopamine’s actions upon ventral striatum neurons.
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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 | 0.001 |
| 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".