Second-order threat conditioning in the amygdala-posterior piriform cortex network
Bibliographic record
Abstract
Fear, while crucial for survival, is a component of a myriad of psychiatric illnesses in its extreme. Persistent fear memories can form through processes such as second-order conditioning (SOC), during which a second-order conditioned stimulus (CS2) acquires significance by associating with a first-order conditioned stimulus (CS1). The neural circuitry underlying SOC, particularly the roles of sensory cortices, remains poorly understood. Here we explore the mechanisms of olfactory SOC in rats, focusing on the basolateral amygdala (BLA) and posterior piriform cortex (pPC). Our results demonstrate that NMDAR-dependent plasticity in both regions is essential for SOC. The BLA mediates the CS2-CS1 association, while the pPC, receiving inputs from the locus coeruleus and BLA, is critical for memory acquisition and retrieval. Single-nucleus multiomics analysis of Fos+ ensembles in both regions reveals distinct yet overlapping gene activation profiles in excitatory neurons, accompanied by global chromatin remodeling. These findings highlight the specific yet coordinated roles of these structures in supporting learning and memory. Olfactory second-order conditioning is supported by the posterior piriform cortex–basolateral amygdala circuit, characterized by overlapping gene regulation profiles and distinct chromatin remodeling in pyramidal neurons.
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 | 0.000 | 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".