Zebrafish brain mapping—standardized spaces, length scales, and the power of N and n

Abstract

Mapping anatomical and functional parameters of the zebrafish brain is moving apace. Research communities undertaking such studies are becoming ever larger and more diverse. The unique features, tools, and technologies associated with zebrafish are propelling them as the 21st century model organism for brain mapping. Uniquely positioned as a vertebrate model system, the zebrafish enables imaging of anatomy and function at different length scales from intraneuronal compartments to sparsely distributed whole brain patterns. With a variety of diverse and established statistical modeling and analytic methods available from the wider brain mapping communities, the richness of zebrafish neuroimaging data is being realized. The statistical power of population observations (N) within and across many samples (n) projected onto a standardized space will provide vast databases for data-driven biological approaches. This article reviews key brain mapping initiatives at different levels of scale that highlight the potential of zebrafish brain mapping. By way of introduction to the next wave of brain mappers, an accessible introduction to the key concepts and caveats associated with neuroimaging are outlined and discussed.

Introduction to the special issue on from maps to circuits: Models and mechanisms for generating neural connections

“…The reviews by Kita et al and Hunter et al emphasize the importance of zebrafish as a model system for studying neural maps. Due to their ease of manipulation, and their accessibility and optical transparency during early development, they offer many opportunities for probing mechanisms of map formation.…”

“…(Kita et al, ) introduce in a zebrafish context some of the basic principles that are then developed in the other contributions, most importantly the role of both molecular and activity‐dependent cues in driving map formation. The main focus of (Hunter et al, ) is the potential of zebrafish for large‐scale brain mapping, including gene expression mapping, understanding the functional classes of retinal ganglion cells, and the retinal projectome, and understanding the relationships between neural activity, neural circuits and behavior. They also discuss some of the big data problems involved, and possible approaches to resolving those.…”