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Related Concept Videos

Brain Imaging01:14

Brain Imaging

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Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
529

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A three-dimensional thalamocortical dataset for characterizing brain heterogeneity.

Judy A Prasad1, Aishwarya H Balwani2, Erik C Johnson3

  • 1Department of Neurobiology, University of Chicago, Chicago, IL, USA.

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|October 21, 2020
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This study presents a 3D X-ray microtomography dataset of a mouse brain, offering a micron-scale view of neural structures. This resource aids in mapping brain pathways and understanding neural heterogeneity.

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Area of Science:

  • Neuroscience
  • Neuroanatomy
  • Imaging Science

Background:

  • Neural microarchitecture exhibits heterogeneity across and within brain regions.
  • Accurate identification of regions of interest is crucial for neurocircuitry examination and mapping brain pathways.
  • 3D volumetric data spanning multiple brain areas enhances landmark identification and microstructure analysis.

Purpose of the Study:

  • To introduce a 3D X-ray microtomography imaging dataset of a thalamocortical mouse brain sample.
  • To provide the scientific community with a micron-scale anatomical imaging dataset.
  • To facilitate the study of neural structure heterogeneity.

Main Methods:

  • Acquisition of a 3D X-ray microtomography dataset.
  • Imaging of a validated thalamocortical sample from a mouse brain.
  • Dataset encompasses a range of cortical and subcortical structures.

Main Results:

  • A comprehensive 3D imaging dataset of mouse brain anatomy at the micron scale.
  • The dataset captures both cortical and subcortical structures within a continuous volume.
  • Provides rich contextual information for neuroanatomical studies.

Conclusions:

  • The presented dataset is a valuable resource for neuroscience research.
  • Enables detailed investigation into the heterogeneity of neural structures.
  • Supports advanced studies in neurocircuitry and brain mapping.