Distinct Neuromodulatory Effects of Endogenous Orexin and Dynorphin Corelease on Projection-Defined Ventral Tegmental Dopamine Neurons
Bibliographic record
Abstract
Dopamine (DA) neurons in the ventral tegmental area (VTA) respond to motivationally relevant cues, and circuit-specific signaling drives different aspects of motivated behavior. Orexin (ox; also known as hypocretin) and dynorphin (dyn) are coexpressed lateral hypothalamic (LH) neuropeptides that project to the VTA. These peptides have opposing effects on the firing activity of VTA DA neurons via orexin 1 (Ox1R) or kappa opioid (KOR) receptors. Given that Ox1R activation increases VTA DA firing, and KOR decreases firing, it is unclear how the coreleased peptides contribute to the net activity of DA neurons. We tested if optical stimulation of LH ox/dyn neuromodulates VTA DA neuronal activity via peptide release and if the effects of optically driven LH ox/dyn release segregate based on VTA DA projection targets including the basolateral amygdala (BLA) or the lateral or medial shell of the nucleus accumbens (lAcbSh, mAchSh). Using a combination of circuit tracing, optogenetics, and patch-clamp electrophysiology in male and female orexin cre mice, we showed a diverse response of LH ox/dyn optical stimulation on VTA DA neuronal firing, which is not mediated by fast transmitter release and is blocked by antagonists to KOR and Ox1R signaling. Additionally, where optical stimulation of LH ox/dyn inputs in the VTA inhibited firing of the majority of BLA-projecting VTA DA neurons, optical stimulation of LH ox/dyn inputs in the VTA bidirectionally affects firing of either lAcbSh- or mAchSh-projecting VTA DA neurons. These findings indicate that LH ox/dyn corelease may influence the output of the VTA by balancing ensembles of neurons within each population which contribute to different aspects of reward seeking.
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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".