Intrinsic reward-like dopamine and acetylcholine dynamics in striatum
Bibliographic record
Abstract
External rewards like food and money are potent modifiers of behavior 1,2 . Pioneering studies established that these salient sensory stimuli briefly interrupt the tonic cell-autonomous discharge of neurons that produce the neuromodulators dopamine (DA) and acetylcholine (ACh): midbrain DA neurons (DANs) fire a burst of action potentials that broadly elevates DA levels in striatum 3-5 at the same time as striatal cholinergic interneurons (CINs) produce a characteristic pause in firing 6-8 . These phasic responses are thought to create unique, temporally-limited conditions that motivate action and promote learning 9-14 . However, the dynamics of DA and ACh outside explicitly-rewarded situations remain poorly understood. Here we show that extracellular levels of DA and ACh fluctuate spontaneously in the striatum of mice and maintain the same temporal relationship as that evoked by reward. We show that this neuromodulatory coordination does not arise from direct interactions between DA and ACh within striatum. Periodic fluctuations in ACh are instead controlled by glutamatergic afferents, which act to locally synchronize spiking of striatal cholinergic interneurons. Together, our findings reveal that striatal neuromodulatory dynamics are autonomously organized by distributed extra-striatal afferents across behavioral contexts. The dominance of intrinsic reward-like rhythms in DA and ACh offers novel insights for explaining how reward-associated neural dynamics emerge and how the brain motivates action and promotes learning from within.
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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) | 0.000 | 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".