A descending pathway facilitates undulatory wave propagation in <i>Caenorhabditis elegans</i> through gap junctions
Bibliographic record
Abstract
Descending signals from the brain play critical roles in controlling and modulating locomotion kinematics. In the Caenorhabditis elegans nervous system, descending AVB premotor interneurons exclusively form gap junctions with B-type motor neurons that drive forward locomotion. We combined genetic analysis, optogenetic manipulation, and computational modeling to elucidate the function of AVB-B gap junctions during forward locomotion. First, we found that some B-type motor neurons generated intrinsic rhythmic activity, constituting distributed central pattern generators. Second, AVB premotor interneurons drove bifurcation of B-type motor neuron dynamics, triggering their transition from stationary to oscillatory activity. Third, proprioceptive couplings between neighboring B-type motor neurons entrained the frequency of body oscillators, forcing coherent propagation of bending waves. Despite substantial anatomical differences between the worm motor circuit and those in higher model organisms, we uncovered converging principles that govern coordinated locomotion. Significance Statement A deep understanding of the neural basis of motor behavior must integrate neuromuscular dynamics, mechanosensory feedback, as well as global command signals, to predict behavioral dynamics. Here, we report on an integrative approach to defining the circuit logic underlying coordinated locomotion in C. elegans. Our combined experimental and computational analysis revealed that (1) motor neurons in C. elegans could function as intrinsic oscillators; (2) Descending inputs and proprioceptive couplings work synergistically to facilitate the sequential activation of motor neuron activities, allowing bending waves to propagate efficiently along the body. Our work thus represents a key step towards an integrative view of animal locomotion.
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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".