Brainwide Projections of Mouse Dopaminergic Zona Incerta Neurons
Bibliographic record
Abstract
The zona incerta (ZI) supports diverse behaviors including binge feeding, sleep-wake cycles, nociception, and hunting. Diverse ZI functions can be attributed to its heterogeneous neurochemical characterization, cytoarchitecture, and efferent connections. The ZI is predominantly GABAergic, but we recently identified a subset of medial ZI GABA cells that are marked by the enzyme tyrosine hydroxylase (TH) and produce dopamine (DA). While the role of GABA within the ZI is well studied, less is known about the functions of ZI DA cells. To identify potential roles of ZI DA cells, we further phenotyped them and mapped their efferent fiber projections. We showed that wild-type TH-immunoreactive (-ir) ZI cells did not express somatostatin or calretinin immunoreactivity. We next validated a Th-cre;L10-Egfp mouse line and found that medial Egfp ZI cells were more likely to be TH-ir. We therefore delivered a Cre-dependent virus into the medial ZI of Th-cre or Th-cre;L10-Egfp mice and selected two injection cases for full brain mapping, namely, cases with the lowest and highest colocalization between TH-ir and virally transduced, DsRed-labeled cells, to identify common target sites. Overall, DsRed-labeled fibers were distributed brainwide and were most prominent within the motor-related midbrain (MBmot), notably the periaqueductal gray area and superior colliculus. We also observed numerous DsRed-labeled fibers within the polymodal association cortex-related thalamus (DORpm), like paraventricular thalamic nucleus and nucleus of reunions, that processes external and internal sensory input. Overall, ZI DA cells displayed a similar fiber profile to ZI GABA cells and may integrate sensory input to coordinate motor output at their target sites.
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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 | 0.001 | 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 | 0.001 |
| 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".