Distinct electrophysiological properties of glutamatergic, cholinergic and GABAergic rat septohippocampal neurons: novel implications for hippocampal rhythmicity
Bibliographic record
Abstract
The medial septum-diagonal band complex (MSDB) contains cholinergic and non-cholinergic neurons known to play key roles in learning and memory processing, and in the generation of hippocampal theta rhythm. Electrophysiologically, several classes of neurons have been described in the MSDB, but their chemical identity remains to be fully established. By combining electrophysiology with single-cell RT-PCR, we have identified four classes of neurons in the MSDB in vitro. The first class displayed slow-firing and little or no Ih, and expressed choline acetyl-transferase mRNA (ChAT). The second class was fast-firing, had a substantial Ih and expressed glutamic acid decarboxylase 67 mRNA (GAD67), sometimes co-localized with ChAT mRNAs. A third class exhibited fast- and burst-firing, had an important Ih and expressed GAD67 mRNA also occasionally co-localized with ChAT mRNAs. The ionic mechanism underlying the bursts involved a low-threshold spike and a prominent Ih current, conductances often associated with pacemaker activity. Interestingly, we identified a fourth class that expressed transcripts solely for one or two of the vesicular glutamate transporters (VGLUT1 and VGLUT2), but not ChAT or GAD. Some putative glutamatergic neurons displayed electrophysiological properties similar to ChAT-positive slow-firing neurons such as the occurrence of a very small Ih, but nearly half of glutamatergic neurons exhibited cluster firing with intrinsically generated voltage-dependent subthreshold membrane oscillations. Neurons belonging to each of the four described classes were found among septohippocampal neurons by retrograde labelling. We provide results suggesting that slow-firing cholinergic, fast-firing and burst-firing GABAergic, and cluster-firing glutamatergic neurons, may each uniquely contribute to hippocampal rhythmicity in vivo.
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 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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".