Dopamine Modulation of Emotional Processing in Cortical and Subcortical Neural Circuits: Evidence for a Final Common Pathway in Schizophrenia?
Bibliographic record
Abstract
The neural regulation of emotional perception, learning, and memory is essential for normal behavioral and cognitive functioning. Many of the symptoms displayed by individuals with schizophrenia may arise from fundamental disturbances in the ability to accurately process emotionally salient sensory information. The neurotransmitter dopamine (DA) and its ability to modulate neural regions involved in emotional learning, perception, and memory formation has received considerable research attention as a potential final common pathway to account for the aberrant emotional regulation and psychosis present in the schizophrenic syndrome. Evidence from both human neuroimaging studies and animal-based research using neurodevelopmental, behavioral, and electrophysiological techniques have implicated the mesocorticolimbic DA circuit as a crucial system for the encoding and expression of emotionally salient learning and memory formation. While many theories have examined the cortical-subcortical interactions between prefrontal cortical regions and subcortical DA substrates, many questions remain as to how DA may control emotional perception and learning and how disturbances linked to DA abnormalities may underlie the disturbed emotional processing in schizophrenia. Beyond the mesolimbic DA system, increasing evidence points to the amygdala-prefrontal cortical circuit as an important processor of emotionally salient information and how neurodevelopmental perturbances within this circuitry may lead to dysregulation of DAergic modulation of emotional processing and learning along this cortical-subcortical emotional processing circuit.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".