Optogenetic frequency scrambling of hippocampal theta oscillations dissociates working memory retrieval from hippocampal spatiotemporal codes
Bibliographic record
Abstract
Abstract The precise temporal coordination of activity in the brain is thought to be fundamental for memory encoding and retrieval. Pacemaker GABAergic neurons in the medial septum (MS) provide the largest source of innervation to the hippocampus and play a major role in controlling hippocampal theta (~8 Hz) oscillations. While pharmacological inhibition of the MS is known to disrupt memory, the exact role of MS inhibitory neurons and theta frequency rhythms in hippocampal representations and memory is not fully understood. Here, we dissociate the role of theta rhythms in spatiotemporal coding and memory using an all-optical interrogation and recording approach in freely behaving mice. We propose a novel paradigm to dissociate encoding of space, time and distance in freely moving mice and apply complementary optogenetic stimulation paradigms of MS GABAergic neurons to either pace or abolish theta altogether while recording large hippocampal cell assemblies using calcium imaging conjointly. We first show that optogenetic frequency scrambling of MS GABAergic neuron activity abolished theta rhythms and modulated the activity of a subpopulation of CA1 neurons. Such stimulation led to decreased memory retrieval in both a delayed non-match to sample task, a novel place object recognition task, as well as spontaneous cue-guided linear alternation. Strikingly, scrambled stimulations were not associated with disrupted encoding of place, time, distance, or multiplexed information. Our study suggests that theta rhythms play a specific and essential role in supporting working memory retrieval and maintenance while not being necessary for hippocampal spatiotemporal codes.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".