The Role of Cannabinoid Transmission in Emotional Memory Formation: Implications for Addiction and Schizophrenia
Bibliographic record
Abstract
Emerging evidence from both basic and clinical research demonstrates an important role for endocannabinoid (ECB) signaling in the processing of emotionally salient information, learning, and memory. Cannabinoid transmission within neural circuits involved in emotional processing has been shown to modulate the acquisition, recall, and extinction of emotionally salient memories and importantly, can strongly modulate the emotional salience of incoming sensory information. Two neural regions in particular, the medial prefrontal cortex (PFC) and the basolateral nucleus of the amygdala (BLA), play important roles in emotional regulation and contain high levels of cannabinoid receptors. Furthermore, both regions show profound abnormalities in neuropsychiatric disorders such as addiction and schizophrenia. Considerable evidence has demonstrated that cannabinoid transmission functionally interacts with dopamine (DA), a neurotransmitter system that is of exceptional importance for both addictive behaviors and the neuropsychopathology of disorders like schizophrenia. Research in our laboratory has focused on how cannabinoid transmission both within and extrinsic to the mesolimbic DA system, including the BLA → mPFC circuitry, can modulate both rewarding and aversive emotional information. In this review, we will summarize clinical and basic neuroscience research demonstrating the importance of cannabinoid signaling within this neural circuitry. In particular, evidence will be reviewed emphasizing the importance of cannabinoid signaling within the BLA → mPFC circuitry in the context of emotional salience processing, memory formation and memory-related plasticity. We propose that aberrant states of hyper or hypoactive ECB signaling within the amygdala-prefrontal cortical circuit may lead to dysregulation of mesocorticolimbic DA transmission controlling the processing of emotionally salient information. These disturbances may in turn lead to emotional processing, learning, and memory abnormalities related to various neuropsychiatric disorders, including addiction and schizophrenia-related psychoses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.001 | 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".