Glutamatergic Neurons of the Mouse Medial Septum and Diagonal Band of Broca Synaptically Drive Hippocampal Pyramidal Cells: Relevance for Hippocampal Theta Rhythm
Bibliographic record
Abstract
Neurons of the medial septum and diagonal band of Broca (MS-DBB) provide an important input to the hippocampus and are critically involved in learning and memory. Although cholinergic and GABAergic MS-DBB neurons are known to modulate hippocampal activity, the role of recently described glutamatergic MS-DBB neurons is unknown. Here, we examined the electrophysiological properties of glutamatergic MS-DBB neurons and tested whether they provide a functional synaptic input to the hippocampus. To visualize the glutamatergic neurons, we used MS-DBB slices from transgenic mice in which the green fluorescent protein is expressed specifically by vesicular glutamate transporter 2-positive neurons and characterized their properties using whole-cell patch-clamp technique. For assessing the function of the glutamatergic projection, we used an in vitro septohippocampal preparation, electrically stimulated the fornix or chemically activated the MS-DBB using NMDA microinfusions and recorded postsynaptic responses in CA3 pyramidal cells. We found that glutamatergic MS-DBB neurons as a population display a highly heterogeneous set of firing patterns including fast-, cluster-, burst-, and slow-firing. Remarkably, a significant proportion exhibited fast-firing properties, prominent I(h), and rhythmic spontaneous firing at theta frequencies similar to those found in GABAergic MS-DBB neurons. Activation of the MS-DBB led to fast, AMPA receptor-mediated glutamatergic responses in CA3 pyramidal cells. These results describe for the first time the electrophysiological signatures of glutamatergic MS-DBB neurons, their rhythmic firing properties, and their capacity to drive hippocampal principal neurons. Our findings suggest that the glutamatergic septohippocampal pathway may play an important role in hippocampal theta oscillations and relevant cognitive functions.
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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 | 0.001 | 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".