Analysis of Monosynaptic Inputs to Thalamic Paraventricular Nucleus Neurons Innervating the Shell of the Nucleus Accumbens and Central Extended Amygdala
Bibliographic record
Abstract
The paraventricular nucleus of the thalamus (PVT) sends dense projections to the shell of the nucleus accumbens (NAcSh), dorsolateral region of the bed nucleus of the stria terminalis (BSTDL) and the lateral region of central nucleus of the amygdala (CeL). Projection specific modulation of these pathways has been shown to regulate appetitive and aversive behavioral responses. The present investigation applied an intersectional monosynaptic rabies tracing approach to quantify the brain-wide sources of afferent input to PVT neurons that primarily project to the NAcSh, BSTDL and CeL. The results demonstrate that these projection neurons receive monosynaptic input from similar brain regions. The prefrontal cortex and the ventral subiculum of the hippocampus were major sources of input to the PVT projection neurons. In addition, the lateral septal nucleus, thalamic reticular nucleus and the hypothalamic medial preoptic area, dorsomedial, ventromedial, and arcuate nuclei were sources of input. The subfornical organ, parasubthalamic nucleus, periaqueductal gray matter, lateral parabrachial nucleus, and nucleus of the solitary tract were consistent but lesser sources of input. This input-output relationship is consistent with recent observations that PVT neurons have axons that bifurcate extensively to divergently innervate the NAcSh, BSTDL and CeL.
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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) | 0.003 | 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".