Are Wayfinding Abilities Correlated With Specific Brain Anatomy? An Investigation on Regular Car Drivers Using a Navigational Map in an Unknown Environment
Bibliographic record
Abstract
The ability to navigate spatially in the physical world is a fundamental cognitive skill. This study examines the anatomical correlates of map-assisted wayfinding in an unfamiliar virtual environment using structural magnetic resonance magining (MRI). Thirty-three participants were required to reach up to seven different locations represented on a navigational map in a simulated environment, while their gazing behavior was recorded, and, in close temporal proximity, the anatomical MRI of their brain was acquired. Significant predictors of wayfinding performance were the volumes of the right hippocampus, left retrosplenial cortex, and posterior cingulate cortex-left inferior frontal gyrus, right superior frontal gyrus, and right cerebellar lobule VIIB. Detailed analyses revealed a dissociation between two clusters of gray matter density in the right hippocampus. Compared with the poorest wayfinders, the best wayfinders exhibited more gray matter density in a cluster located in the right posterior hippocampus but less gray matter density in a cluster located in the anterior section of the hippocampus. In addition, top performers spent more time gazing at the map, highlighting the benefit of using external aids during navigation tasks. Altogether, these results underscore how structural adaptations are associated with spatial navigation performance.
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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 | 0.000 |
| 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 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".