Sparsity of Population Activity in the Hippocampus Is Task‐Invariant Across the Trisynaptic Circuit and Dorsoventral Axis
Bibliographic record
Abstract
Evidence from neurophysiological and genetic studies demonstrates that activity sparsity-the proportion of neurons that are active at a given time in a population-systematically varies across the canonical trisynaptic circuit of the hippocampus. Recent work has also shown that sparsity varies across the hippocampal dorsoventral (long) axis, wherein activity is sparser in ventral than dorsal regions. While the hippocampus has a critical role in long-term memory (LTM), whether sparsity across the trisynaptic circuit and hippocampal long axis is task-dependent or invariant remains unknown. Importantly, representational sparsity has significant implications for neural computation and theoretical models of learning and memory within and beyond the hippocampus. Here we used functional molecular imaging to quantify sparsity in the rat hippocampus during performance of the Morris water task (MWT) and contextual fear discrimination (CFD) - two popular and distinct assays of LTM. We found that activity sparsity is highly reliable across memory tasks, wherein activity increases sequentially across the trisynaptic circuit (DG < CA3 < CA1) and decreases across the long axis (ventral<dorsal). These results have important implications for models of hippocampal function and suggest that activity sparsity is a preserved property in the hippocampal system across cognitive settings.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".