A Subpopulation of Neurons in the Medial Prefrontal Cortex Encodes Emotional Learning with Burst and Frequency Codes through a Dopamine D<sub>4</sub>Receptor-Dependent Basolateral Amygdala Input
Bibliographic record
Abstract
The basolateral nucleus of the amygdala (BLA) and medial prefrontal cortex (mPFC) are involved importantly in the processing and encoding of emotionally salient learned associations. Here, we examined the possible role of the mPFC in the acquisition and encoding of emotional associative learning at the behavioral and single-neuron level. A subpopulation of neurons in the mPFC that received monosynaptic and orthodromic inputs from the BLA demonstrated strong associative responding to odors paired previously with footshock by increasing spontaneous activity and bursting activity. This occurred specifically in response to postconditioning presentations of the footshock-paired odors but not to odors presented in the absence of footshock. In contrast, mPFC neurons that failed to respond to BLA stimulation showed no associative responding. Systemic or intra-mPFC blockade of dopamine (DA) D4 receptors prevented this emotional associative learning in neurons of the mPFC and blocked the expression of olfactory conditioned fear. These results demonstrate that individual neurons in the mPFC that receive a functional input from the BLA actively encode emotional learning and that this process depends on DA D4 receptor stimulation in the mPFC.
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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".