A three-dimensional thalamocortical dataset for characterizing brain heterogeneity

Abstract

Neural microarchitecture is heterogeneous, varying both across and within brain regions. The consistent identification of regions of interest is one of the most critical aspects in examining neurocircuitry, as these structures serve as the vital landmarks with which to map brain pathways. Access to continuous, three-dimensional volumes that span multiple brain areas not only provides richer context for identifying such landmarks, but also enables a deeper probing of the microstructures within. Here, we describe a three-dimensional X-ray microtomography imaging dataset of a well-known and validated thalamocortical sample, encompassing a range of cortical and subcortical structures from the mouse brain . In doing so, we provide the field with access to a micron-scale anatomical imaging dataset ideal for studying heterogeneity of neural structure.

A multimodal imaging and analysis pipeline for creating a cellular census of the human cerebral cortex

“…To understand its properties and functionality, it is critical to produce a comprehensive characterization of the neuronal cell types that compose it and to visualize their distributions through the whole volume 1,2 . Although significant technological advances [3][4][5][6][7] have been made to obtain complete cell census in animal models such as mouse and marmoset monkey [8][9][10][11][12][13][14][15][16] , no current imaging technology can directly visualize the defining microscopic features of the human brain without significant distortion. Indeed, available cytoarchitectural parcellations of the human brain 17 are limited by unavoidable distortions introduced by slice-to-slice sectioning, clearing, staining and mounting steps involved in current histochemistry protocols.…”

Brain Microenvironment Heterogeneity: Potential Value for Brain Tumors

“…Imaging, genomic and proteomic analyses have been valuable tools for dissecting inter-and intraregional heterogeneity within the brain. Initially applied to uncover neuronal subtypes across brain regions (2)(3)(4)(5), single-cell RNA sequencing (scRNAseq), singlenucleus RNA sequencing (snRNAseq), mass cytometry (CyTOF) and spatial transcriptomics, have also proved to be a powerful tool beyond non-neuronal cells, revolutionizing the way we interrogate cancer-associated heterogeneity. Recently, the principles of scRNAseq have been expanded to elucidate in vivo networks based on cell-to-single cell interactions (6)(7)(8).…”