Conjunctive and complementary CA1 hippocampal cell populations relate sensory events to immobility and locomotion
Bibliographic record
Abstract
Abstract This study investigated the dynamics of recruitment of cells in the CA1 region of the hippocampus in response to sensory stimuli presented during immobility, movement, and their transitions. Two-photon calcium imaging of somal activity in CA1 neuron populations was done in head fixed mice. Sensory stimuli, either a light flash or an air stream, were delivered to the mice when at rest, when moving spontaneously, and while they were induced to run a fixed distance on the conveyor belt. Overall, 99% of 2083 identified cells (from 5 mice) were active across one or more of 20 sensorimotor events. A larger proportion of cells were active during locomotion. Nevertheless, for any given sensorimotor event, only about 17% of cells were active. When considering pairs of sensorimotor event types, the active cell population consisted of conjunctive (C ∈ A and B) cells, active across both events, and complementary (C ∈ A not B or C ∈ B not A) cells that were active only during individual events. Whereas conjunctive cells characterised stable representations of repeated sensorimotor events, complementary cells characterised recruitment of new cells for encoding novel sensorimotor events. The moment-to-moment recruitment of conjunctive and complementary cells across changing sensorimotor events signifies the involvement of the hippocampus in functional networks integrating sensory information with ongoing movement. This role of the hippocampus is well suited for movement guidance that secondarily might include spatial behavior, episodic learning and memory, context representation, and scene construction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".