Coordinated electrical and chemical signaling between two neurons orchestrates switching of motor states
Bibliographic record
Abstract
Summary To survive in a complex environment, animals must respond to external cues, e.g., to escape threats or to navigate towards favorable locations. Navigating requires transition between motor states, e.g. switching from forward to backward movement. Here, we investigated how two classes of interneurons, RIS and RIM, fine-tune this transition in the nematode C. elegans . By Ca 2+ imaging in freely moving animals, we found that RIS gets active slightly before RIM and likely biases decision-making towards a reversal. In animals lacking RIS, we observed lowered Ca 2+ -levels in RIM prior to a reversal. Combined photo-stimulation and voltage imaging revealed that FLP-11, a neuropeptide released by RIS, has an excitatory effect on RIM, while tyramine, released from RIM, inhibits RIS. Voltage imaging of intrinsic activity provided evidence for tight electrical coupling between RIS and RIM via gap junctions harboring UNC-7 innexins. Asymmetric junctional current flow was observed from RIS to RIM, and vice versa. We propose that the interplay of RIS and RIM is based on concerted electrical and chemical signaling, with a fast junctional current exchange early during the transition from forward to backward movement, followed by chemical signaling, likely during reversal execution.
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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".