Editorial: Zebrafish Cognition and Behavior
Bibliographic record
Abstract
Abstract Introduction Understanding animal cognition has evolved from using simple visual and acoustic stimuli to complex objects and videos, revealing sophisticated mental processes across various species. While the cognitive abilities of fish were historically debated and often dismissed as simple stimulus-response reflexes due to their smaller brains , recent neurobiological research demonstrates that fish possess genetic, neuronal, and physiological mechanisms similar to mammals. This includes homologous brain regions for emotional regulation and memory, as well as complex behaviors such as tool use, spatial learning, counting, and long-term memory. The Zebrafish as a Model Organism Among fish, the zebrafish (Danio rerio) has emerged as a premier vertebrate model for biomedical and translational neuroscience research. Since George Streisinger successfully cloned the first homozygous diploid zebrafish in the 1970s, the species has offered distinct advantages: * Embryos develop rapidly, hatching just 3 days post-fertilization. * Transparent embryos allow for the direct visualization of anatomical changes during development. * A partially sequenced genome reveals high genetic similarities to other vertebrates, including humans. Today, an estimated 8 million zebrafish are used annually in over 600 laboratories worldwide. Overview of the Research Topic The Research Topic "Zebrafish Cognition and Behavior" featured in Frontiers in Behavioral Neuroscience compiles a diverse body of work investigating cognitive functions from molecular mechanisms to behavior, and from health to pathology. The sampled studies explore: * Environmental and embryonic alcohol impacts on dynamic shoaling behaviors. * Behavioral, anxiety-like, and oxidative consequences of social and restraint stress. * Memory impairment and altered cortisol levels caused by environmental toxicants like pyriproxyfen. * Quantity estimation and decision-making in fish. * Correlations between personality and cognitive traits. * Theories surrounding elemental versus configural learning and memory. Ultimately, this collection highlights how the zebrafish combines the complexity of a vertebrate brain with the practical advantages of an invertebrate, making it a powerful model for decoding the mechanisms of learning, memory, and cognitive decay.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.030 | 0.013 |
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".