Anterior hippocampal integration tracks the developmental emergence of flexible navigation through changing environments
Bibliographic record
Abstract
Abstract Flexible memory depends on cognitive maps that integrate spatial relationships and guide behavior as environments change. The anterior hippocampus is well positioned to support integration across broad spatiotemporal scales, but its late maturation may constrain development of flexible, map-based navigation. Here, we tested whether hippocampal temporal autocorrelation, an index of neural activity stability over time, tracks the development of spatial integration. In a large resting-state fMRI sample (N = 382; ages 5-34 years), temporal autocorrelation increased with age in anterior, but not posterior, hippocampus. This anterior-specific pattern was replicated in an independent task-based fMRI sample of children, adolescents, and adults (N = 85; aged 6-12 years and adults), wherein we linked hippocampal autocorrelation to dissociable components of spatial behavior. The navigation task separated memory for object locations from the ability to update and generalize knowledge across rotations of the distal reference frame and to new object sets. Although all age groups learned object locations, only older participants showed evidence that prior spatial structure supported performance as the environment changed across runs. Critically, hippocampal autocorrelation related to behavior only when spatial knowledge was used across runs, rather than improved through within-run feedback, with the clearest profile emerging in adults. In adults, anterior and posterior autocorrelation jointly predicted precise object-location memory, whereas anterior autocorrelation uniquely predicted efficient trajectories from novel starting positions. These findings identify anterior hippocampal temporal autocorrelation as a later-maturing computation that supports the transition from local spatial learning in childhood to flexible navigation through changing environments in adulthood. Significance Statement Finding our way through the world requires more than remembering where things are. We also need to use what we have learned to take new routes, adjust when familiar places change, and apply old knowledge to new situations. These abilities improve from childhood to adulthood, but the brain changes that support this transition remain unclear. We show that a signal in anterior hippocampus, a brain region important for linking experiences, becomes more stable over development. Using a navigation task that separated remembering object locations from flexibly using a map, we found that this signal was most strongly tied to adults’ ability to navigate efficiently through changing environments. These findings reveal a hippocampal mechanism that supports flexible navigation as children mature.
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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 | 0.001 |
| 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 | 0.001 | 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".