Whole-brain imaging using genetically encoded activity sensors in vertebrates

Andreas M. Kist, Laura D. Knogler, Daniil A. Markov, Tugce Yildizoglu, Ruben Portugues

Publikation: Beitrag in Buch/Bericht/KonferenzbandKapitelBegutachtung

2 Zitate (Scopus)

Abstract

In the mid-twentieth century, the development of electrophysiology revolutionized the way that the brain could be studied, allowing scientists to advance beyond anatomy and neuroethology and address questions involving brain function. These recordings offered a temporally and spatially high-resolution readout of the activity of single cells and enabled a detailed understanding of the input-output function of individual neurons. Nevertheless, understanding the brain one neuron at a time seems like a daunting task. Over the last two decades, a considerable amount of research has focused on understanding the brain at the mesoscale of brain circuits and networks, trying to bridge the gap from single neurons to the function of the whole brain in generating behavior. This is a large, open and exciting field that encompasses theory, computational models, behavioral studies, genetic manipulations and many more approaches. Importantly, the current interest in brain circuits is fueled by the development of new techniques that allow us to acquire data relevant to addressing network function and the activity of large populations of neurons. In this chapter, we present an introduction to whole-brain, single-cell resolution imaging in a behaving vertebrate model organism, the larval zebrafish. We describe the fundamental concepts developed during the last five years that are important for understanding large-scale imaging techniques in vertebrates from experimental design to data acquisition and analysis.

OriginalspracheEnglisch
TitelDecoding Neural Circuit Structure and Function
UntertitelCellular Dissection Using Genetic Model Organisms
Herausgeber (Verlag)Springer International Publishing
Seiten321-341
Seitenumfang21
ISBN (elektronisch)9783319573632
ISBN (Print)9783319573625
DOIs
PublikationsstatusVeröffentlicht - 24 Juli 2017
Extern publiziertJa

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