Peripheral nerve injury-induced alterations in VTA neuron firing properties
Bibliographic record
Abstract
The ventral tegmental area (VTA) is one of the main brain regions harboring dopaminergic (DA) neurons, and plays important roles in reinforcement and motivation. Recent studies have indicated that DA neurons not only respond to rewarding stimuli, but also to noxious stimuli. Furthermore, VTA DA neurons undergo plasticity during chronic pain. Lateral and medial VTA neurons project to different brain areas, and have been characterized via their distinct electrophysiological properties. In this study, we characterized electrophysiological properties of lateral and medial VTA DA neurons using DAT-cre reporter mice, and examined their plasticity during neuropathic pain states. We observed various DA subpopulations in both the lateral and medial VTA, as defined by action potential firing patterns, independently of synaptic inputs. Our results demonstrated that lateral and medial VTA DA neurons undergo differential plasticity after peripheral nerve injury that leads to neuropathic pain. However, these changes only reside in specific DA subpopulations. This study suggests that lateral and medial VTA DA neurons are differentially affected during neuropathic pain conditions, and emphasizes the importance of subpopulation specificity when targeting VTA DA neurons for treatment of neuropathic pain.
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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) | 0.002 | 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".