Integrated Behavioral, Genetic and Brain Circuit Visualization Methods to Unravel Functional Anatomy of Zebrafish Amygdala

Diving into the zebrafish brain: exploring neuroscience frontiers with genetic tools, imaging techniques, and behavioral insights

The zebrafish (Danio rerio) is increasingly used in neuroscience research. Zebrafish are relatively easy to maintain, and their high fecundity makes them suitable for high-throughput experiments. Their small, transparent embryos and larvae allow for easy microscopic imaging of the developing brain. Zebrafish also share a high degree of genetic similarity with humans, and are amenable to genetic manipulation techniques, such as gene knockdown, knockout, or knock-in, which allows researchers to study the role of specific genes relevant to human brain development, function, and disease. Zebrafish can also serve as a model for behavioral studies, including locomotion, learning, and social interactions. In this review, we present state-of-the-art methods to study the brain function in zebrafish, including genetic tools for labeling single neurons and neuronal circuits, live imaging of neural activity, synaptic dynamics and protein interactions in the zebrafish brain, optogenetic manipulation, and the use of virtual reality technology for behavioral testing. We highlight the potential of zebrafish for neuroscience research, especially regarding brain development, neuronal circuits, and genetic-based disorders and discuss its certain limitations as a model.

Molecular organization of neuronal cell types and neuromodulatory systems in the zebrafish telencephalon

The function of neuronal networks is determined not only by synaptic connectivity but also by neuromodulatory systems that broadcast information via distributed connections and volume transmission. To understand the molecular constraints that organize neuromodulatory signaling in the telencephalon of adult zebrafish, we used transcriptomics and additional approaches to delineate cell types, to determine their phylogenetic conservation, and to map the expression of marker genes at high granularity. The combinatorial expression of GPCRs and cell-type markers indicates that all neuronal cell types are subject to modulation by multiple monoaminergic systems and distinct combinations of neuropeptides. Individual cell types were associated with multiple (typically >30) neuromodulatory signaling networks but expressed only a few diagnostic GPCRs at high levels, suggesting that different neuromodulatory systems act in combination, albeit with unequal weights. These results provide a detailed map of cell types and brain areas in the zebrafish telencephalon, identify core components of neuromodulatory networks, highlight the cell-type specificity of neuropeptides and GPCRs, and begin to decipher the logic of combinatorial neuromodulation.

Genetic Identification of Neural Circuits Essential for Active Avoidance Fear Conditioning in Adult Zebrafish

Inhibition or ablation of neuronal activity combined with behavioral assessment is crucial in identifying neural circuits or populations essential for specific behaviors and to understand brain function. In the model vertebrate zebrafish, the development of genetic methods has allowed not only visualization but also targeted manipulation of neuronal activity, and quantitative behavioral assays allow precise measurement of animal behavior. Here, we describe a method to inhibit a specific neuronal population in adult zebrafish brain and assess their role in a learning behavior. We employed the Gal4-UAS system, gene trap and enhancer trap methods, and isolated transgenic zebrafish lines expressing Gal4FF transactivator in specific populations of neurons in the adult zebrafish brain. In these lines, a genetically engineered neurotoxin, botulinum toxin B light chain, was expressed and the fish were assessed in the active avoidance fear conditioning paradigm. The transgenic lines that showed impaired avoidance response were isolated and, in these fish, the Gal4-expressing neurons were analyzed to identify the neuronal circuits involved in avoidance learning.