Combining patient-lesion and big data approaches to reveal hippocampal contributions to spatial memory and navigation
Bibliographic record
Abstract
Classic findings of impaired allocentric spatial learning and memory following hippocampal lesions indicate that the hippocampus supports cognitive maps of one's environment. Many studies assess navigation in vista space virtual reality environments and compare hippocampal-lesioned individuals' performance to that of small control samples, potentially stifling detection of preserved and impaired performance. Using the mobile app Sea Hero Quest, we examined navigation in diverse complex environments in two individuals with hippocampal lesions relative to demographically matched controls ( N = 17,734). We found surprisingly accurate navigation in several environments, particularly those containing a constrained set of sub-goals, paths, and/or turns. Areas of impaired performance may reflect a role for the hippocampus in anterograde memory and more flexible and/or precise spatial representations, even when the need for allocentric processing is minimal. The results emphasize the value of combining single cases with big data and illustrate navigation performance profiles in individuals with hippocampal compromise.
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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 | 0.000 | 0.001 |
| 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".