The perirhinal cortex modulates V2 activity in response to the agreement between part familiarity and configuration familiarity
Bibliographic record
Abstract
Research has demonstrated that the perirhinal cortex (PRC) represents complex object-level feature configurations, and participates in familiarity versus novelty discrimination. Barense et al. [(in press) Cerebral Cortex, 22:11, doi:10.1093/cercor/bhr347] postulated that, in addition, the PRC modulates part familiarity responses in lower-level visual areas. We used fMRI to measure activation in the PRC and V2 in response to silhouettes presented peripherally while participants maintained central fixation and performed an object recognition task. There were three types of silhouettes: Familiar Configurations portrayed real-world objects; Part-Rearranged Novel Configurations created by spatially rearranging the parts of the familiar configurations; and Control Novel Configurations in which both the configuration and the ensemble of parts comprising it were novel. For right visual field (RVF) presentation, BOLD responses revealed a significant linear trend in bilateral BA 35 of the PRC (highest activation for Familiar Configurations, lowest for Part-Rearranged Novel Configurations, with Control Novel Configurations in between). For left visual field (LVF) presentation, a significant linear trend was found in a different area (bilateral BA 38, temporal pole) in the opposite direction (Part-Rearranged Novel Configurations highest, Familiar Configurations lowest). These data confirm that the PRC is sensitive to the agreement in familiarity between the configuration level and the part level. As predicted, V2 activation mimicked that of the PRC: for RVF presentation, activity in V2 was significantly higher in the left hemisphere for Familiar Configurations than for Part-Rearranged Novel Configurations, and for LVF presentation, the opposite effect was found in right hemisphere V2. We attribute these patterns in V2 to feedback from the PRC because receptive fields in V2 encompass parts but not configurations. These results reveal two new aspects of PRC function: (1) it is sensitive to the congruency between the familiarity of object configurations and the parts comprising those configurations and (2) it likely modulates familiarity responses in visual area V2.
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 | 0.001 |
| 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".