Author response: Neural circuitry coordinating male copulation
Bibliographic record
Abstract
Idioms and love songs often euphemistically refer to “the birds and the bees”. Yet for neurobiologists interested in uncovering basic facts about sex and reproduction, the fruit fly has proven much more informative. Male fruit flies court females with a series of “hard-wired” or genetically programmed behaviors. One gene called doublesex generates differences in the anatomy and behavior of males and females in many animal species. In male fruit flies, the doublesex gene is active in roughly 650 neurons, with specific groups of cells controlling distinct steps of the courtship ritual. However, it was not understood how the different steps involved in copulation were coordinated to ensure a successful mating. Pavlou et al. have now identified a circuit of doublesex-expressing neurons that controls copulation itself. The circuit, which is in the fruit fly’s equivalent of the spinal cord, is made up of three types of neurons: motor neurons, inhibitory interneurons and mechanosensory neurons. The motor neurons coordinate the joining of the male’s genitals with those of the female. The inhibitory interneurons promote the release of the male’s genitals by opposing the motor neurons, while the mechanosensory neurons possibly coordinate the activity of the other neurons to generate the correct sequence of events needed for copulation. Pavlou et al. also showed that the mechanism that controls how the male attaches to and detaches from the female is independent of ejaculation, indicating that the mechanics of copulation are separate from those of reproduction. A future challenge will be to understand how command centres in the brain combine these signals with sensory feedback to enable males to execute and modify their copulation-related behaviors. Identifying neural circuits that drive behaviors in fruit flies provide insights into the universal principles by which a nervous system can coordinate complex motor behaviors such as walking and flying.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.370 | 0.146 |
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".