Development of sensorimotor responses in larval zebrafish: a comparison between wild-type and GCaMP6s transgenic line
Bibliographic record
Abstract
Abstract During early development, zebrafish larvae exhibit stereotypical behaviors, which rapidly become more complex. Thus, the generation of mutant transgenic lines that maintain transparency throughout their larval stage and that can be used to record brain activity has offered strategic opportunities to investigate the underlying neural correlates of behavior establishment. However, few studies have documented the behavioral profile of these lines during larval development. Here, we set up a behavioral characterization using diverse stimuli (light and vibration) throughout larval development to compare the responses of a transgenic strain expressing a pan-neuronal calcium indicator (GCaMP6s) with that of a wild-type strain. Interestingly, we report a drastic switch in behavioral responses to light transitions at 11 days post-fertilization (dpf) and to vibration stimuli at 14 dpf in both lines. These data highlight a specific time window of behavioral complexification. Meanwhile, we found no major difference in the maturation of sensorimotor responses between GCaMP6s and wild-type strains. Thus, these results support using GCaMP6s strain in investigating the neural mechanisms underlying the developmental maturation of sensorimotor responses. We observed nevertheless some minor differences that suggest careful attention should be taken when using mutant/transgenic lines for behavioral studies. Highlights - Longitudinal investigation of sensorimotor responses by zebrafish during their larval development - During the second week of development, larval zebrafish switch their motor response to light transition - Pan-neuronal nuclear expression of GCaMP6s has little impact on larval fish response to various stimuli
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".