Circadian influences on dopamine circuits of the brain: regulation of striatal rhythms of clock gene expression and implications for psychopathology and disease
Bibliographic record
Abstract
Circadian clock proteins form an autoregulatory feedback loop that is central to the endogenous generation and transmission of daily rhythms in behavior and physiology. Increasingly, circadian rhythms in clock gene expression are being reported in diverse tissues and brain regions that lie outside of the suprachiasmatic nucleus (SCN), the master circadian clock in mammals. For many of these extra-SCN rhythms, however, the region-specific implications are still emerging. In order to gain important insights into the potential behavioral, physiological, and psychological relevance of these daily oscillations, researchers have begun to focus on describing the neurochemical, hormonal, metabolic, and epigenetic contributions to the regulation of these rhythms. This review will highlight important sites and sources of circadian control within dopaminergic and striatal circuitries of the brain and will discuss potential implications for psychopathology and disease . For example, rhythms in clock gene expression in the dorsal striatum are sensitive to changes in dopamine release, which has potential implications for Parkinson's disease and drug addiction. Rhythms in the ventral striatum and limbic forebrain are sensitive to psychological and physical stressors, which may have implications for major depressive disorder. Collectively, a rich circadian tapestry has emerged that forces us to expand traditional views and to reconsider the psychopathological, behavioral, and physiological importance of these region-specific rhythms in brain areas that are not immediately linked with the regulation of circadian rhythms.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".