The ratio of posterior–anterior medial temporal lobe volumes predicts source memory performance in healthy young adults
Bibliographic record
Abstract
A functional gradient has been proposed across the medial temporal lobes (MTL) such that the anterior MTL is thought to support processing of individual items (e.g., item memory and complex object perception), whereas the posterior MTL is thought to support item-context retrieval (e.g., source memory). Whereas functional imaging studies have provided evidence supporting this anatomical organization, results from structural analyses remain inconclusive. The current study examined the relationship between volume of MTL regions of interest (ROIs), and performance on a source memory task and a fine-grain complex object perception task, in healthy young adults (mean age = 21.5, range = 18-29). Using a semiautomated procedure, we segmented the parahippocampal and perirhinal cortices (PHC, PRC), posteromedial and anterolateral entorhinal cortices (pmERC, alERC), and posterior and anterior hippocampus (postHC, antHC) on high-resolution T2-weighted MRIs. Regional volumes were computed as proportions of intracranial volume, and as posterior-anterior volumetric ratios (PHC:PRC, pmERC:alERC, postHC:antHC). Partial-least squares regressions were applied to predict source and item memory, and perceptual discrimination accuracy, based on ROI and ratio volumes. In our ROI regressions, we found that postHC volume was positively correlated with a latent factor predicting source memory, and PRC and antHC volumes were negatively correlated to this latent factor. In our ratio regressions, we observed an effect relating the posterior-anterior distribution of gray matter across the MTL with source memory. Our results demonstrate differential associations between anterior and posterior MTL and source memory performance. Findings from this study highlight the importance of considering patterns of structure-behavior associations in the neurobiology of episodic memory.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".