Zebrafish Larva’s Response and Habituation to Electric Signal: Effects of Voltage, Current and Pulsation Studied in a Microfluidic Device
Bibliographic record
Abstract
We previously showed that electric current can cause zebrafish larvae to move towards the anode pole along a microchannel. For a semi-mobile larva, we observed that zebrafish response to electricity depended on the current magnitude. The effects of electric signal direction, voltage magnitude and habituation to repeated exposures to electric pulses were not characterized. Here, this knowledge gap was addressed by exploiting these parameters in a microfluidic device with a head-trap to immobilize a zebrafish larva and a downstream chamber for tail movement and phenotypic characterization of response duration (RD) and tail beat frequency (TBF). We first assessed larvae’s response to electric current direction (at 3µA) and voltage magnitude. Changing the current direction significantly altered the RD and TBF with long and low-frequency responses seen when the anode was positioned at larvae’s tail. The electric voltage drop across the fish body had a significant effect on larvae’s locomotion with long RD and low TBF observed at 5.6V in the range of 1.3-9V. We also demonstrated that the zebrafish locomotor response to repeated 3µA current pulses diminished with dependency on the interstimulus interval. However, the diminished response was fully recovered after a 5-min resting period or introduction of a novel light stimulus (i.e. habituation-dishabituation strategy). Therefore, electric response suppression in zebrafish was attributed to the habituation as a form of non-associative learning. Our microfluidic platform has broad application potential in behavioral neuroscience to study cognitive phenotypes, fundamental studies on the biological roots of electric response, and pharmacological screening.
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".