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Kunst, M.

Publications and source records attributed to Kunst, M..

2 recordsLinked to original sources

A single-cell resolution gene expression atlas of the larval zebrafish brain

The advent of multimodal brain atlases promises to accelerate discoveries in neuroscience by offering in silico queries of cell types, connectivity and gene expression in regions of interest. We employed multiplexed fluorescent in situ RNA hybridization chain reaction (HCR) to generate expression maps for an initial set of 200 marker genes across the larval zebrafish brain. The data were registered to the Max Planck Zebrafish Brain (mapzebrain) atlas, thus allowing co-visualization of gene expression patterns, single-neuron tracings, transgenic lines and anatomical segmentations. Additionally, brain activity maps of freely swimming larvae were generated at single-cell resolution using HCR labeling of the immediate-early gene cfos and integrated into the atlas. As a proof of concept, we identified a novel class of cerebellar eurydendroid cells that express calb2a, project to the hypothalamus and are activated in animals that have recently ingested food. Thus, a cellular-resolution gene expression atlas will not only help with rapid identification of marker genes for neuronal populations of interest, but also bridge the molecular and circuit levels by anchoring genetic information to functional activity maps and synaptic connectivity.

neuroscience↗

Compositional Restricted Boltzmann Machines Unveil the Brain-Wide Organization of Neural Assemblies

Patterns of endogenous activity in the brain reflect a stochastic exploration of the neuronal state space that is constrained by the underlying assembly organization of neurons. Yet it remains to be shown that this interplay between neurons and their assembly dynamics indeed suffices to generate whole-brain data statistics. Here we recorded the activity from ~ 40,000 neurons simultaneously in zebrafish larvae, and show that a data-driven generative model of neuron-assembly interactions can accurately reproduce the mean activity and pairwise correlation statistics of their spontaneous activity. This model, the compositional Restricted Boltzmann Machine (cRBM), unveils ~ 200 neural assemblies, which compose neurophysiological circuits and whose various com-binations form successive brain states. We then performed in silico perturbation experiments to determine the interregional functional connectivity, which is conserved across individual animals and correlates well with structural connectivity. Our results showcase how cRBMs can capture the coarse-grained organization of the zebrafish brain. Notably, this generative model can readily be deployed to parse neural data obtained by other large-scale recording techniques.

neuroscience↗