View cells in the hippocampus and prefrontal cortex of macaques during virtual navigation
Bibliographic record
Abstract
Cells selectively activated by a particular view of an environment have been found in the primate hippocampus (HPC). Whether view cells are present in other brain areas, and how view selectivity interacts with other variables such as object features and place remain unclear. Here, we explore these issues by recording the responses of neurons in the HPC and the lateral prefrontal cortex (LPFC) of rhesus macaques performing a task in which they learn new context-object associations while navigating a virtual environment using a joystick. We measured neuronal responses at different locations in a virtual maze where animals freely directed gaze to different regions of the visual scenes. We show that specific views containing task relevant objects selectively activated a proportion of HPC units, and an even higher proportion of LPFC units. Place selectivity was scarce and generally dependent on view. Many view cells were not affected by changing the object color or the context cue, two task relevant features. However, a small proportion of view cells showed selectivity for these two features. Our results show that during navigation in a virtual environment with complex and dynamic visual stimuli, view cells are found in both the HPC and the LPFC. View cells may have developed as a multiarea specialization in diurnal primates to encode the complexities and layouts of the environment through gaze exploration which ultimately enables building cognitive maps of space that guide navigation.
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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 | 0.000 | 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) | 0.000 | 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".