Different classes of input and output neurons reveal new features in microglomeruli of the adult <i>Drosophila</i> mushroom body calyx
Bibliographic record
Abstract
To investigate how sensory information is processed, transformed, and stored within an olfactory system, we examined the anatomy of the input region, the calyx, of the mushroom bodies of Drosophila melanogaster. These paired structures are important for various behaviors, including olfactory learning and memory. Cells in the input neuropil, the calyx, are organized into an array of microglomeruli each comprising the large synaptic bouton of a projection neuron (PN) from the antennal lobe surrounded by tiny postsynaptic neurites from intrinsic Kenyon cells. Extrinsic neurons of the mushroom body also contribute to the organization of microglomeruli. We employed a combination of genetic reporters to identify single cells in the Drosophila calyx by light microscopy and compared these with cell shapes, synapses, and circuits derived from serial-section electron microscopy. We identified three morphological types of PN boutons, unilobed, clustered, and elongated; defined three ultrastructural types, with clear- or dense-core vesicles and those with a dark cytoplasm having both; reconstructed diverse dendritic specializations of Kenyon cells; and identified Kenyon cell presynaptic sites upon extrinsic neurons. We also report new features of calyx synaptic organization, in particular extensive serial synapses that link calycal extrinsic neurons into a local network, and the numerical proportions of synaptic contacts between calycal neurons. All PN bouton types had more ribbon than nonribbon synapses, dark boutons particularly so, and ribbon synapses were larger and with more postsynaptic elements (2-14) than nonribbon (1-10). The numbers of elements were in direct proportion to presynaptic membrane area. Extrinsic neurons exclusively had ribbon synapses.
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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".