Evidence for a virtual human analog of a rodent relational memory task: A study of aging and fMRI in young adults
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Bibliographic record
Abstract
A radial maze concurrent spatial discrimination learning paradigm consisting of two stages was previously designed to assess the flexibility property of relational memory in mice, as a model of human declarative memory. Aged mice and young adult mice with damage to the hippocampus, learned accurately Stage 1 of the task which required them to learn a constant reward location in a specific set of arms (i.e., learning phase). In contrast, they were impaired relative to healthy young adult mice in a second stage when faced with rearrangements of the same arms (i.e., flexibility probes). This mnemonic inflexibility in Stage 2 is thought to derive from insufficient relational processing by the hippocampus during initial learning (Stage 1) which favors stimulus-response learning, a form of procedural learning. This was proposed as a model of the selective declarative and relational memory decline classically described in elderly people. As a first step to examine the validity of this model, we adapted this protocol to humans using a virtual radial-maze. (1) We showed that performance in the flexibility probes in young and older adults positively correlated with performance in a wayfinding task, suggesting that our paradigm assesses relational memory. (2) We demonstrated that older healthy participants displayed a deficit in the performance of the flexibility probes (Stage 2), similar to the one previously seen in aged mice. This was associated with a decline in the wayfinding task. (3) Our fMRI data in young adults confirmed that hippocampal activation during early discrimination learning in Stage 1 correlated with memory flexibility in Stage 2, whereas caudate nucleus activation in Stage 1 negatively correlated with subsequent flexibility. By enabling relational memory assessment in mice and humans, our radial-maze paradigm provides a valuable tool for translational research.
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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 | 0.000 |
| 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) | 0.000 | 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 it