Novelty Discrimination of Configural Objects in the Perirhinal and Anterolateral Entorhinal Cortices Is Impacted by Aging
Bibliographic record
Abstract
The representational-hierarchical account of object processing characterizes the perirhinal cortex (PRC) as supporting conjunctive representations of object features, such that damage or age-related decline in the PRC impairs discrimination between complex object with overlapping features. In older adults, gray matter volume of the anterolateral entorhinal cortex (alERC), a PRC-adjacent region, correlated with object discrimination based on configural (spatial) arrangements of features. However, this relationship has not yet been examined with functional activation or systematically investigated in aging. Importantly, object novelty discrimination can rely on changes at the feature-level (where all features are novel) or configural-level (where familiar features are rearranged in novel configurations), and the PRC/alERC may differentially support these processes-differences that may become more pronounced with age-related neurodegeneration. However, distinguishing functional roles of the PRC/alERC is complicated by interindividual variability in their anatomical boundaries that may be exacerbated by aging. In the present fMRI study, we manually delineated the PRC/alERC in a group of 43 younger (32 females) and 47 older adults (33 females) performing a configural object processing task with concurrent eye-tracking. In younger adults, gaze behavior and PRC activity distinguished both feature and configural novelty, whereas alERC activity was sensitive to configural novelty. In contrast, age-related decline was most evident in the PRC's activation to configural novelty, and older adults showed no novelty-related differentiation in gaze behavior or alERC function. These findings suggest the critical role of the alERC in object processing and reveal age-related changes in the PRC/alERC during novelty discrimination of complex objects.
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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".