Coreleased Orexin and Glutamate Evoke Nonredundant Spike Outputs and Computations in Histamine Neurons
Bibliographic record
Abstract
Stable wakefulness requires orexin/hypocretin neurons (OHNs) and OHR2 receptors. OHNs sense diverse environmental cues and control arousal accordingly. For unknown reasons, OHNs contain multiple excitatory transmitters, including OH peptides and glutamate. To analyze their cotransmission within computational frameworks for control, we optogenetically stimulated OHNs and examined resulting outputs (spike patterns) in a downstream arousal regulator, the histamine neurons (HANs). OHR2s were essential for sustained HAN outputs. OHR2-dependent HAN output increased linearly during constant OHN input, suggesting that the OHN→HAN(OHR2) module may function as an integral controller. OHN stimulation evoked OHR2-dependent slow postsynaptic currents, similar to midnanomolar OH concentrations. Conversely, glutamate-dependent output transiently communicated OHN input onset, peaking rapidly then decaying alongside OHN→HAN glutamate currents. Blocking glutamate-driven spiking did not affect OH-driven spiking and vice versa, suggesting isolation (low cross-modulation) of outputs. Therefore, in arousal regulators, cotransmitters may translate distinct features of OHN activity into parallel, nonredundant control signals for downstream effectors.
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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) | 0.001 | 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".