Connecting the dots of the cerebro‐cerebellar role in cognitive function: Neuronal pathways for cerebellar modulation of dopamine release in the prefrontal cortex
Bibliographic record
Abstract
Cerebellar involvement in autism, schizophrenia, and other cognitive disorders is typically associated with prefrontal cortical pathology. However, the underlying neuronal mechanisms are largely unknown. It has previously been shown in mice that stimulation of the dentate nucleus (DN) of the cerebellum evokes dopamine (DA) release in the medial prefrontal cortex (mPFC). Here, we investigated the neuronal circuitry by which the cerebellum modulates mPFC DA release. Fixed potential amperometry was used to determine the contribution of two candidate pathways by which the cerebellum may modulate mPFC DA release. In urethane anesthetized mice, DA release evoked by DN stimulation (50 Hz) was recorded in mPFC following local anesthetic lidocaine (0.02 μg) or ionotropic glutamate receptor antagonist kynurenate (0.5 μg) infusions into the mediodorsal or ventrolateral thalamic nucleus (ThN md; ThN vl), or the ventral tegmental area (VTA). Following intra-VTA lidocaine or kynurenate infusions, DA release was decreased by ∼50%. Following intra-ThN md and ThN vl infusions of either drug, DA release was decreased by ∼35% and 15%, respectively. Reductions in DA release following lidocaine or kynurenate infusions were not significantly different indicating that neuronal cells in the VTA and ThN were activated primarily if not entirely by glutamatergic inputs. The present study suggests that neuropathological changes in the cerebellum commonly observed in autism, schizophrenia, and other cognitive disorders could result in a loss of functionality of cerebellar-mPFC circuitry that is manifested as aberrant dopaminergic activity in the mPFC. Additionally, these results specifically implicate glutamate as a modulator of mPFC dopaminergic 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".