Temporal association activates projections from the perirhinal cortex and ventral CA1 to the prelimbic cortex and from the prelimbic cortex to the basolateral amygdala
Bibliographic record
Abstract
Abstract In temporal associations, the prelimbic cortex (PL) has persistent activity during the interval between the conditioned stimulus (CS) and the unconditioned stimulus (US), which maintains a CS representation. Regions cooperating for this function or encoding the CS before the interval could neuroanatomically connect to the PL, supporting learning. The basolateral amygdala (BLA) has CS- and US-responsive neurons, convergently activated. The PL could directly project to the BLA to associate the transient CS memory with the US. We investigated the neural circuit supporting temporal associations using the CFC-5s task, in which a 5-second interval separates the contextual CS from the US. Injecting retrobeads, we quantified c-Fos in PL- or BLA-projecting neurons from 9 regions after CFC-5s or contextual fear conditioning (CFC), in which CS/US overlap. The CFC-5s activated ventral CA1 (vCA1) and perirhinal cortex (PER) neurons projecting to the PL, and PL neurons projecting to BLA. Both CFC-5s and CFC activated vCA1 and lateral entorhinal (LEC) neurons projecting to BLA, and BLA neurons projecting to PL. Both conditioning activated the PER, LEC, cingulate and infralimbic cortices, nucleus reuniens, and ventral subiculum. Results added new relevance to the PER→PL projection and showed that the PL/BLA are reciprocally functionally connected in CFC-5s.
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) | 0.002 | 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".