Browse the brains in the cell type atlas

Computational Toolbox for STP Tomography based Cell Density Mapping

The main functionality is to stitch STP data set together and to analyze them as described in the paper by Kim et al., Cell 2017. These codes are specifically designed handle STP dataset.
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Cell type atlas

Cell types are the elementary building blocks of the mammalian brain, as they determine the properties of local circuits that can be built to serve area-specific brain functions. While there is a growing knowledge of cell type-specific cell anatomy (dendritic morphology and axonal arborization) and physiology (biophysical and synaptic properties and transcriptome profiles), there are virtually no data on quantitative brainwide cell-type distribution. Yet, without this knowledge, it will not be possible to understand how cell type-specific circuit assemblies give rise to motor, sensory-perceptual, emotional, and cognitive functions, or how cell type-specific gender differences may contribute to male or female-specific behavioral variations.

Here we begin to address this knowledge gap by building a cell type-based atlas of the male and female mouse brain. We start by focusing on a population of GABAergic inhibitory neurons, which comprises an extraordinary diversity of cell types proposed to partake in a broad range brain functions, from orchestrating cortical activity during sensory and cognitive processing, to controlling fear, aggression, and sexual behaviors. In the first data release, we focus on three broad inhibitory cell types identified by the expression of somatostatin (SST), parvalbumin (PV), and vasoactive intestinal peptide (VIP), and four intersectional sub-cell types co-expressing SST and calretinin (SST:CR), SST and neuronal nitric oxide synthase (SST:nNOS), VIP and CR (VIP:CR), and VIP and cholecystokinin (VIP:CCK). The imaging and computational methods used to map the cell type distribution are described in Kim et al., 2017 article[^] “Brain-wide Maps Reveal Stereotyped Cell-Type-Based Cortical Architecture and Subcortical Sexual Dimorphism”.