Delta‐9‐tetrahydrocannabinol potentiates fear memory salience through functional modulation of mesolimbic dopaminergic activity states
Bibliographic record
Abstract
Chronic or acute exposure to delta-9-tetrahydrocannabinol (THC), the main psychoactive compound in cannabis, has been associated with numerous neuropsychiatric side-effects, including dysregulation of emotional processing and associative memory formation. Clinical and preclinical evidence suggests that the effects of THC are due to the ability to modulate mesolimbic dopamine (DA) activity states in the nucleus accumbens (NAc) and ventral tegmental area (VTA). Nevertheless, the mechanisms by which THC modulates mesolimbic DA function and emotional processing are not well understood. Using an olfactory associative fear memory procedure combined with in vivo neuronal electrophysiology, we examined the effects of direct THC microinfusions targeting the shell region of the NAc (NASh) and examined how THC may modulate the processing of fear-related emotional memory and concomitant activity states of the mesolimbic DA system. We report that intra-NASh THC dose-dependently potentiates the emotional salience of normally subthreshold fear conditioning cues. These effects were dependent upon intra-VTA transmission through GABAergic receptor mechanisms and intra-NASh DAergic transmission. Furthermore, doses of intra-NASh THC that potentiated fear memory salience were found to modulate intra-VTA neuronal network activity by increasing the spontaneous firing and bursting frequency of DAergic neurones whilst decreasing the activity levels of a subpopulation of putative GABAergic VTA neurones. These findings demonstrate that THC can act directly in the NASh to modulate mesolimbic activity states and induce disturbances in emotional salience and memory formation through modulation of VTA DAergic transmission.
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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) | 0.001 | 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".