Modeling Spontaneous Activity in the Developing Spinal Cord Using Activity-Dependent Variations of Intracellular Chloride
Bibliographic record
Abstract
We investigated how spontaneous activity is generated in developing, hyperexcitable networks. We focused our study on the embryonic chick spinal cord, a preparation that exhibits rhythmic discharge on multiple timescales: slow episodes (lasting minutes) and faster intraepisode cycling (approximately 1 Hz frequency). For this purpose, we developed a mean field model of a recurrent network with slow chloride dynamics and a fast depression variable. We showed that the model, in addition to providing a biophysical mechanism for the slow dynamics, was able to account for the experimentally observed activity. The model made predictions on how interval and duration of episodes are affected when changing chloride-mediated synaptic transmission or chloride flux across cell membrane. These predictions guided experiments, and the model results were compared with experimental data obtained with electrophysiological recordings. We found agreement when transmission was affected through changes in synaptic conductance and good qualitative agreement when chloride flux was varied through changes in external chloride concentration or in the rate of the Na+-K+-2Cl- cotransporter. Furthermore, the model made predictions about the time course of intracellular chloride concentration and chloride reversal potential and how these are affected by changes in synaptic conductance. Based on the comparison between modeling and experimental results, we propose that chloride dynamics could be an important mechanism in rhythm generation in the developing chick spinal cord.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".