Spinning in the scanner: Neural correlates of virtual reorientation.
Bibliographic record
Abstract
Recent studies have used spatial reorientation task paradigms to identify underlying cognitive mechanisms of navigation in children, adults, and a range of animal species. Despite broad interest in this task across disciplines, little is known about the brain bases of reorientation. We used functional magnetic resonance imaging to examine neural activity in adults during a virtual reality version of the reorientation task. Three environments that varied in the cues provided were studied: a rectangular room with 4 identical gray walls (Geometry), a square room with 3 gray walls and 1 red wall (Feature), and a rectangular room with 3 gray walls and 1 red wall (Feature + Geometry). Multiple areas within the medial temporal lobe (MTL) showed increased activation when a feature was present compared with when reorientation was based only on geometric cues. In contrast, reliance on geometric cues significantly activated a number of non-MTL structures, including the prefrontal cortex and inferior temporal gyrus. These results provide neural evidence for processing differences between the 2 types of cue as well as insight into developmental and comparative aspects of reorientation.
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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 | 0.002 |
| 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) | 0.002 | 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".