A three-dimensional thalamocortical dataset for characterizing brain heterogeneity

Judy A. Prasad, Aishwarya H. Balwani, Erik C. Johnson, Joseph D. Miano, Vandana Sampathkumar, Vincent De Andrade, Kamel Fezzaa, Ming Du, Rafael Vescovi, Chris Jacobsen, Konrad P. Kording, Doga Gürsoy, William Gray Roncal, Narayanan Kasthuri, Eva L. Dyer*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

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.

Original languageEnglish (US)
Article number358
JournalScientific Data
Volume7
Issue number1
DOIs
StatePublished - Dec 1 2020

ASJC Scopus subject areas

  • Statistics and Probability
  • Information Systems
  • Education
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences

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