Abstract
The zebrafish is an ideal model organism for behavioral genetics and neuroscience. The high conservation of genes and neurotransmitter pathways between zebrafish and other vertebrates permits the translation of research between species. Zebrafish behavior can be studied at both larval and adult stages and recent research has begun to establish zebrafish models for human disease. Fast scan cyclic voltammetry (FSCV) is an electrochemical technique that permits the detection of neurotransmitter release and reuptake. In this study we have used in vitro FSCV to measure the release of analytes in the adult zebrafish telencephalon. We compare different stimulation methods and present a characterization of neurochemical changes in the wild-type zebrafish brain. This study represents the first FSCV recordings in zebrafish, thus paving the way for neurochemical analysis of the fish brain.
Highlights
A central goal of neuroscience is to understand how the brain processes stimuli in order to tailor an appropriate behavioral response
We explored the possibility that pH changes could be influencing the signals that we recorded in the telencephalon by altering the pH of dopamine, histamine and 5-HT mixtures in a flow cell
To confirm that our principal component analysis (PCA) was accurate in its representation of type- and concentration- of analytes, we examined a combination of 0.25 μM 5HT, 1 μM dopamine, 40 μM histamine and an acidic pH shift of +1.0 unit obtained in the flow cell
Summary
A central goal of neuroscience is to understand how the brain processes stimuli in order to tailor an appropriate behavioral response. Each behavior was thought to be driven by a dedicated neural circuit in the brain (Zupanc and Lamprecht, 2000). Recent research suggests that discrete behaviors can be produced by the interaction of diffuse neural networks with overlapping functions (Bargmann, 2012). Dramatically different behaviors can be driven by the same neurons acting in parallel circuits. Rather than being hard-wired entities, neural circuits exhibit plasticity due to short-term neuromodulatory activity and longer-term structural reorganization at the synaptic level (Zupanc and Lamprecht, 2000; Bargmann, 2012). A combination of approaches combining information from a range of scientific disciplines is needed to identify the network components that drive behavior
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