Author response: The CNS connectome of a tadpole larva of Ciona intestinalis (L.) highlights sidedness in the brain of a chordate sibling
Bibliographic record
Abstract
Brains are made up of a network of nerve cells (neurons) that are connected to each other by junctions called synapses. The neurons on the left and right sides of the brain form different patterns of connections, but this asymmetry can be difficult to spot because the brain is large and complex. Understanding how the whole network operates is key to understanding how the brain works. However, a full map of all the connections between neurons – known as a connectome – has only been described for one species so far, a nematode worm called C. elegans. The tadpole larva of the common sea squirt has a fairly simple brain distantly related to our own but made up of only about 330 cells. Ryan et al. used a technique called electron microscopy to study thin sections from the brains of sea squirt larvae to reveal this animal’s connectome and investigate left-right asymmetry in the brain. The analysis revealed 177 neurons in this larval brain, just over half of its brain cells. These can be split into at least 25 types and each neuron has a simple, mostly unbranched shape with, on average, 49 synapses with other cells. This means that, even though it has such a small number of neurons, the neuron network is still relatively complex. The shortest sensory pathway to any muscle connects via three synapses, although most pathways involve more. The left and right sides of the brain differ in the types of neurons they contain and the connections these form, even though both sides have the same number of cells. The findings of Ryan et al. reveal the second animal connectome and lay the groundwork for future studies on how each neuron in the network influences the behaviour of the sea squirt’s larva. Further work is also required to find out how the patterns of synapses in the brain change as the larva ages, and whether the connectome differs between siblings.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.246 | 0.045 |
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".