Viral labeling of neurons synaptically connected to nucleus accumbens somatostatin interneurons
Bibliographic record
Abstract
The nucleus accumbens, a key brain reward region, receives synaptic inputs from a range of forebrain and brainstem regions. Many of these projections have been established using electrophysiology or fluorescent tract tracing. However, more recently developed viral tracing techniques have allowed for fluorescent labeling of synaptic afferents in a cell type-specific manner. Since the NAc is comprised of multiple cell types, these methods have enabled the delineation of the cell type-specific connectivity of principal medium spiny neurons in the region. The synaptic connectivity of somatostatin interneurons, which account for <5% of the neurons in the region, has been inferred from electrophysiological and immunohistochemical data, but has not yet been visualized using modern viral tracing techniques. Here, we use the pseudorabies virus (PRV)-Introvert-GFP virus, an alphaherpes virus previously shown to label synaptic afferents in a cell type-specific manner, to label first order afferents to NAc somatostatin interneurons. While we find GFP(+) labeling in several well established projections to the NAc, we also observe that several known projections to NAc did not contain GFP(+) cells, suggesting they do not innervate somatostatin interneurons in the region. A subset of the GFP(+) afferents are c-FOS(+) following acute administration of cocaine, showing that NAc somatostatin interneurons are innervated by some cells that respond to rewarding stimuli. These results provide a foundation for future studies aimed toward elucidating the cell type-specific connectivity of the NAc, and identify specific circuits that warrant future functional characterization.
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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 | 0.001 |
| 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".