Bibliographic record
Abstract
Critical to episodic memory is pattern separation (PS), the storage of similar inputs as distinct and nonoverlapping. Spatial and temporal PS have been shown to be related to disparate subfields of the hippocampus (HC) in rodents. Extra-HC structures involved have not yet been elucidated. The current work provides an exploratory investigation into the neural correlates of spatial and temporal PS, employing functional magnetic resonance imaging and univariate and multivariate analysis techniques. In Experiment 1, behavioural spatial and temporal memory tasks were developed that assess varying PS demands. Objectives for the experiment were met, in that accuracy was lower and reaction time higher for conditions requiring more engagement of PS. In Experiment 2, whole-brain regions as well as the neural networks involved in spatial and temporal PS were examined, and functional connectivity of the HC was observed. Univariate data revealed unique areas of activation based on information type being encoded (i.e., spatial vs. temporal). The cuneus and HC were uniquely involved in the spatial task, while a wider area of regions including middle occipital and medial frontal areas were activated in the temporal task. Multivariate analyses were convergent with the spatial and temporal context memory literature. The HC, parahippocampal gyri, prefrontal cortices, and precuneus were part of a correlated network in the spatial task. Bilateral prefrontal cortices, including the orbitofrontal cortex were involved in the temporal task. Further, the multivariate analysis revealed qualitatively distinct networks based on memory processing stage (i.e., encoding vs. retrieval). Interestingly, the network included anterior HC in spatial encoding, and posterior HC in spatial and temporal retrieval, consistent with an influential theory positing a rostrocaudal gradient along the HC for encoding and retrieval. Functional connectivity analyses revealed connectivity of the posterior HC seed with temporal and superior parietal areas in the spatial task, and with frontal areas in the temporal task, suggesting the right posterior HC interacts with regions differently based on information type. Results confirm and extend findings from previous literature demonstrating HC involvement in PS, and also suggest HC and extra-HC involvement varies based on processing stage and information type.
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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 | 0.001 |
| 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 | 0.001 |
| 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".