Propagation of Neocortical Inputs in the Perirhinal Cortex
Bibliographic record
Abstract
The perirhinal area is a rostrocaudally oriented strip of cortex in which lesions produce memory and perceptual impairments. It receives topographically organized transverse projections from associative neocortical areas and is endowed with intrinsic longitudinal connections that could distribute neocortical inputs in the rostrocaudal axis. In search of distinguishing network properties that might support perirhinal involvement in memory, we have performed whole-cell recordings in horizontal perirhinal slices with preserved transverse neocortical links and intrinsic longitudinal connections. Neocortical stimulation sites in rostrocaudal register with regular spiking perirhinal neurons elicited a sequence of excitatory and inhibitory synaptic potentials. In contrast, apparently pure excitatory responses were observed when the stimulating and recording sites were separated by >/=1 mm in the rostrocaudal axis. This suggested that adjacent and distant neocortical stimuli influence regular spiking perirhinal neurons by pathways that respectively form and do not form synapses with inhibitory interneurons. In keeping with this, presumed interneurons did not respond to distant neocortical stimuli. These results suggest that neocortical inputs recruit perirhinal inhibitory interneurons located at the same transverse level, limiting the depolarization of principal perirhinal cells. In contrast, distant neocortical inputs only evoke excitation because longitudinal perirhinal pathways do not engage inhibitory interneurons. This leads us to suggest that the perirhinal network is biased to favor Hebbian-like associative interactions between coincident and spatially distributed inputs.
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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".