In order to study the function of the brain it is necessary to manipulate
the activity with high spatial precision. Transgenic lines offer the possibility to express proteins
in specific cell types that can be used to alter their activity (e.g. channelrhodopsin). We imaged
hundreds of different lines and created shape-based averages for each of them. To compare the
individual expression patterns with each other we are registered them to a high-resolution,
age-matched standard brain, with support from a local supercomputing center. In the future we hope
that this dataset will help researcher in finding lines that express in the cell-type of their
How many discrete cell types exist in the vertebrate brain and how do
they connect the different brain regions of the larval zebrafish brain? In order to tackle this
problem, we are automatically classifying neurons in a high-throughput fashion. We are using a
genetic tool that stochastically labels individual neurons with membrane-targeted fluorophores.
Labeled neurons are imaged by confocal microscopy at high resolution and reconstructed for
quantitative morphological analysis. In order to compare neurons between individual fish, we are
registering them to a high-resolution, age-matched standard brain, with support from a local
supercomputing center. From this data we could generate a preliminary mesoscale connectome that
describes the organization of the larval zebrafish brain.
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