“I have often walked down this street before”: fMRI Studies on the hippocampus and other structures during mental navigation of an old environment
Bibliographic record
Abstract
The role of the hippocampus in recent spatial memory has been well documented in patients with damage to this structure, but there is now evidence that the hippocampus may not be needed for the storage and recovery of a spatial layout that was experienced long before injury. Such preservation may rely, instead, on a network of dissociable, extra-hippocampal regions implicated in topographical orientation. Using functional magnetic resonance imaging (fMRI), we investigated this hypothesis in healthy individuals with extensive experience navigating in a large-scale urban environment (downtown Toronto). Participants were scanned as they performed mental navigation tasks that emphasized different types of spatial representations. Tasks included proximity judgments, distance judgments, landmark sequencing, and blocked-route problem-solving. The following regions were engaged to varying degrees depending on the processing demands of each task: retrosplenial cortex, believed to be involved in assigning directional significance to locales within a relatively allocentric framework; medial and posterior parietal cortex, concerned with processing space within egocentric coordinates during imagined movement; and regions of prefrontal cortex, present in tasks heavily dependent on working memory. In a second, event-related experiment, a distinct area of inferotemporal cortex was revealed during identification of familiar landmarks relative to unknown buildings in addition to activation of many of those regions identified in the navigation tasks. This result suggests that familiar landmarks are strongly integrated with the spatial context in which they were experienced. Importantly, right medial temporal lobe activity was observed, its magnitude equivalent across all tasks, though the core of the activated region was in the parahippocampal gyrus, barely touching the hippocampus proper.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".