Functional role and connectivity of perirhinal cortex in face processing
Bibliographic record
Abstract
The prevailing view of medial temporal lobe (MTL) functioning holds that its structures are dedicated to declarative long-term memory. Recent evidence challenges this view, suggesting that perirhinal cortex (PrC), which interfaces the MTL with the ventral visual pathway, supports highly integrated object representations that are critical for perceptual as well as for memory-based discriminations. Here, we review research conducted with fMRI in healthy individuals that addresses the role of PrC, and its functional connectivity, in the context of face processing. Our research shows that (i) PrC exhibits a performance-related involvement in recognition-memory as well as in perceptual oddball judgments for faces; (ii) PrC involvement in perceptual tasks is related to demands for face individuation; (ii) PrC exhibits resting-state connectivity with the FFA and the amygdala that has behavioural relevance for the face-inversion effect; (iii) task demands that distinguish recognition-memory from perceptual-discrimination tasks are reflected in distinct patterns of functional connectivity between PrC and other cortical regions, rather than in differential PrC activity. Together, our findings challenge the view that mnemonic demands are the sole determinant of PrC involvement in face processing, and that its response to such demands uniquely distinguishes its role from that of more posterior ventral visual pathway regions. Instead, our findings point to the importance of considering the nature of representations and functional connectivity in efforts to elucidate the contributions of PrC and other cortical structures to face processing. Meeting abstract presented at VSS 2014
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 | 0.001 | 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".