Lateral entorhinal cortex afferents reconfigure the activity in piriform cortex circuits
Bibliographic record
Abstract
Odors are key signals for guiding spatial behaviors such as foraging and navigation in rodents. Recent findings reveal that odor representations in the piriform cortex (PCx) also encode spatial context information. However, the brain origins of this information and its integration into PCx microcircuitry remain unclear. This study investigates the lateral entorhinal cortex (LEC) as a potential source of spatial contextual information affecting the PCx microcircuit and its olfactory responses. Using mice brain slices, we performed patch-clamp recordings on superficial (SP) and deep (DP) pyramidal neurons, as well as parvalbumin (PV) and somatostatin (SOM) inhibitory interneurons. Concurrently, we optogenetically stimulated excitatory LEC projections to observe their impact on PCx activity. Results show that LEC inputs are heterogeneously distributed in the PCx microcircuit, evoking larger excitatory currents in SP and PV neurons due to higher monosynaptic connectivity. LEC inputs also differentially affect inhibitory circuits, activating PV while suppressing SOM interneurons. Studying the interaction between LEC inputs and sensory signals from the lateral olfactory tract (LOT) revealed that simultaneous LEC and LOT activation increases spiking in SP and DP neurons, with DP neurons showing a sharpened response due to LEC-induced inhibition that suppresses delayed LOT-evoked spikes. This suggests a regulatory mechanism where LEC inputs inhibit recurrent activity by activating PV interneurons. Our findings demonstrate that LEC afferents reconfigure PCx activity, aiding the understanding of how odor objects form within the PCx by integrating olfactory and nonolfactory information.
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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".