Noradrenergic Control of Cortico-Striato-Thalamic and Mesolimbic Cross-Structural Synchrony
Bibliographic record
Abstract
Although normal dopaminergic tone has been shown to be essential for the induction of cortico-striatal and mesolimbic theta oscillatory activity, the influence of norepinephrine on these brain networks remains relatively unknown. To address this question, we simultaneously recorded local field potentials and single-neuron activity across 10 interconnected brain areas (ventral striatum, frontal association cortex, hippocampus, primary motor cortex, orbital frontal cortex, prelimbic cortex, dorsal lateral striatum, medial dorsal nucleus of thalamus, substantia nigra pars reticularis, and ventral tegmental area) in a combined genetically and pharmacologically induced mouse model of hyponoradrenergia. Our results show that norepinephrine (NE) depletion induces a novel state in male mice characterized by a profound disruption of coherence across multiple cortico-striatal circuits and an increase in mesolimbic cross-structural coherence. Moreover, this brain state is accompanied by a complex behavioral phenotype consisting of transient hyperactivity, stereotypic behaviors, and an acute 12-fold increase in grooming. Notably, treatment with a norepinephrine precursors (l-3,4-dihydroxyphenylalanine at 100 mg/kg or l-threo-dihydroxyphenylserine at 5 mg/kg) or a selective serotonin reuptake inhibitor (fluoxetine at 20 mg/kg) attenuates the abnormal behaviors and selectively reverses the circuit changes observed in NE-depleted mice. Together, our results demonstrate that norepinephrine modulates the dynamic tuning of coherence across cortico-striato-thalamic circuits, and they suggest that changes in coherence across these circuits mediate the abnormal generation of hyperactivity and repetitive behaviors.
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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".