Median Raphe Stimulation Disrupts Hippocampal Theta Via Rapid Inhibition and State-Dependent Phase Reset of Theta-Related Neural Circuitry
Bibliographic record
Abstract
Evidence has accumulated suggesting that the median raphe (MR) mediates hippocampal theta desynchronization. However, few studies have evaluated theta-related neural circuitry during MR manipulation. In urethane-anesthetized rats, we investigated the effects of MR stimulation on hippocampal field and cell activity using high-frequency (100 Hz), theta burst (TBS), and slow-frequency electrical stimulation (0.5 Hz). We demonstrated that high-frequency stimulation of the MR did not elicit deactivated patterns in the forebrain, but rather elicited low-voltage activity in the neocortex and small-amplitude irregular activity (SIA) in the hippocampus. Both hippocampal phasic theta-on and -off cells were inhibited by high-frequency MR stimulation, although MR stimulation failed to affect cells that had neither state or phase relationships with theta field activity. TBS of the MR-induced theta field activity phase locked to the stimulation. Slow-frequency stimulation elicited a state-dependent reset of theta phase through a short-latency inhibition (5 ms) in phasic theta-on cells. Subpopulations of phasic theta-on cells responded in either oscillatory or nonoscillatory patterns to MR pulses, depending on their intraburst interval. off cells exhibited a state-dependent modulation of cell firing occurring preferentially during nontheta. The magnitude of MR-induced reset varied as a function of the phase of the theta oscillation when the pulse was administered. Therefore high-frequency stimulation of the MR appears to disrupt hippocampal theta through a state-dependent, short-latency inhibition of rhythmic cell populations in the hippocampus functioning to switch theta oscillations to an activated SIA field state.
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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 | 0.000 |
| 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".