Structure, Activity and Function of a Singing CPG Interneuron Controlling Cricket Species-Specific Acoustic Signaling
Bibliographic record
Abstract
The evolution of species-specific song patterns is a driving force in the speciation of acoustic communicating insects. It must be closely linked to adaptations of the neuronal network controlling the underlying singing motor activity. What are the cellular and network properties that allow generating different songs? In five cricket species, we analyzed the structure and activity of the identified abdominal ascending opener interneuron, a homologous key component of the singing central pattern generator. The structure of the interneuron, based on the position of the cell body, ascending axon, dendritic arborization pattern, and dye coupling, is highly similar across species. The neuron's spike activity shows a tight coupling to the singing motor activity. In all species, current injection into the interneuron drives artificial song patterns, highlighting the key functional role of this neuron. However, the pattern of the membrane depolarization during singing, the fine dendritic and axonal ramifications, and the number of dye-coupled neurons indicate species-specific adaptations of the neuronal network that might be closely linked to the evolution of species-specific singing. SIGNIFICANCE STATEMENTA fundamental question in evolutionary neuroscience is how species-specific behaviors arise in closely related species. We demonstrate behavioral, neurophysiological, and morphological evidence for homology of one key identified interneuron of the singing central pattern generator in five cricket species. Across-species differences of this interneuron are also observed, which might be important to the generation of the species-specific song patterns. This work offers a comprehensive and detailed comparative analysis addressing the neuronal basis of species-specific behavior.
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".