Cell-type specific sensory and motor activity in the cuneiform nucleus and pedunculopontine nucleus in mice
Bibliographic record
Abstract
The activity of neurotransmitter-based cell types in the cuneiform and pedunculopontine nuclei during locomotion, non-locomotor behaviors, and following sensory stimulation is not fully understood. Using fiber photometry in mice, we found cell-type specific responses to sensory stimuli. Glutamatergic and GABAergic cells responded to sound, visual looming, and air puffs, except for pedunculopontine GABAergic cells, which did not respond to visual looming. Cholinergic cells responded to air puffs. Air puffs triggered high-speed locomotion, whereas visual looming and sound stimuli evoked low-speed locomotion. During air puff-evoked locomotion, cuneiform glutamatergic neuron activity was higher than in trials without locomotion. In contrast, during locomotion evoked by visual looming or sound, activity in pedunculopontine glutamatergic neurons was higher than when no locomotion occurred. In the open-field arena, mice exhibited spontaneous low-speed locomotion during which activity increased in pedunculopontine glutamatergic cells. Activity also increased in a cell type-specific manner during grooming or rearing. Our study shows cell type-specific activity in the cuneiform or pedunculopontine nuclei during locomotion, non-locomotor behaviors, and following sensory stimulation. Sensory responsiveness likely has relevance in Parkinson's disease, where sensory circuits are increasingly targeted to improve walking.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".