Neurons in the ventral striatopallidal complex modulate lateral hypothalamic orexin/hypocretin neuron activity: Implications for reward-seeking
Bibliographic record
Abstract
Abstract Reward-seeking involves the engagement and computation of multiple physiological and motivational parameters. The lateral hypothalamus (LH) is a necessary node in the circuits that control food-seeking and motivation. One group of cells that plays an important yet incompletely understood role in these processes are the orexin/hypocretin (OX/HT) neurons. OX/HT cells are located exclusively within the LH and are implicated in feeding, arousal, and reward-seeking behavior. Importantly, the role of OX/HT neurons in consummatory versus reward-seeking actions is not fully defined, nor are the circuits that control the activity of these neurons under different behavioral states. Here we show that OX/HT neurons respond in real time to food presentation and that this response is modulated by differences in metabolic state. We observed increased OX/HT neuron activity on approach to food, but this activity trended towards pre-approach levels by the start of the consummatory phase. Next, we studied ventrostriatopallidal (VSP) inputs to the OX/HT neurons. Using optogenetics and cell type-specific electrophysiology, we found that ventral pallidum inputs onto OX/HT neurons exert strong inhibitory (and weak excitatory) effects whereas the lateral nucleus accumbens shell provides weaker direct inhibitory connections with OX/HT neurons. These findings reveal that the activity of OX/HT neurons is strongly modulated by metabolic and hedonic state. Further, OX/HT neurons is primarily associated with food approach and that the effect of VSP-terminal output is to suppress OX/HT activity.
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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".