Synergy between Electrical Coupling and Membrane Properties Promotes Strong Synchronization of Neurons of the Mesencephalic Trigeminal Nucleus
Bibliographic record
Abstract
Electrical synapses are known to form networks of extensively coupled neurons in various regions of the mammalian brain. The mesencephalic trigeminal (MesV) nucleus, formed by the somata of primary afferents originating in jaw-closing muscles, constitutes one of the first examples supporting the presence of electrical synapses in the mammalian CNS; however, the properties, functional organization, and developmental emergence of electrical coupling within this structure remain unknown. By combining electrophysiological, tracer coupling, and immunochemical analysis in brain slices of rat and mouse, we found that coupling is mostly restricted to pairs or small clusters of MesV neurons. Electrical transmission is supported by connexin36 (Cx36)-containing gap junctions at somato-somatic contacts where only a small proportion of channels appear to be open (∼0.1%). In marked contrast with most brain structures, coupling among MesV neurons increases with age, such that it is absent during early development and appears at postnatal day 8. Interestingly, the development of coupling parallels the development of intrinsic membrane properties responsible for repetitive firing in these neurons. We found that, acting together, sodium and potassium conductances enhance the transfer of signals with high-frequency content via electrical synapses, leading to strong spiking synchronization of the coupled neurons. Together, our data indicate that coupling in the MesV nucleus is restricted to mostly pairs of somata between which electrical transmission is supported by a surprisingly small fraction of the channels estimated to be present, and that coupling synergically interacts with specific membrane conductances to promote synchronization of these neurons.
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 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".