The human subcortex is comprised of more than 450 individual nuclei which lie deep in the brain. Due to their small size and close proximity, up until now only 7% have been depicted in standard MRI atlases. Thus, the human subcortex can largely be considered as terra incognita. Here we present a new open source parcellation algorithm to automatically map the subcortex. The new algorithm has been tested on 17 prominent subcortical structures based on a large quantitative MRI dataset at 7 Tesla. It has been carefully validated against expert human raters and previous methods, and can easily be extended to other subcortical structures and applied to any quantitative MRI dataset. In sum, we hope this novel parcellation algorithm will facilitate functional and structural neuroimaging research into small subcortical nuclei and help to chart terra incognita.
The tool presented in this article is available in open source on Github (https://github.com/nighres/nighres). The atlases necessary to run the algorithm have been deposited on the University of Amsterdam FigShare (https://doi.org/10.21942/uva.12074175.v1 and https://doi.org/10.21942/uva.12301106.v2). A single sample subject data set has been deposited on the University of Amsterdam FigShare (https://doi.org/10.21942/uva.12280316.v2). All the measurements used to generate the figures included in the article have been deposited on the University of Amsterdam FigShare (https://doi.org/10.21942/uva.12452444.v1).
The Amsterdam Ultra-high field adult lifespan database (AHEAD): A freely available multimodal 7 Tesla submillimeter magnetic resonance imaging databaseFigShare University of Amsterdam / Amsterdam University of Applied Sciences.
The WU-Minn Human Connectome ProjectWU-Minn HCP Retest Data.
- Birte U Forstmann
- Anneke Alkemade
- Birte U Forstmann
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Human subjects: Informed consent and consent to publish, including consent to publish anonymized imaging data, was obtained for all subjects. Ethical approval was obtained with the University of Amsterdam Faculty of Social and Behavioral Sciences LAB Ethics Review Board, with ERB number 2016-DP-6897.
- Timothy Verstynen, Carnegie Mellon University, United States
© 2020, Bazin et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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