Anatomical and functional organization of the human substantia nigra and its connections
Abstract
We investigated the anatomical and functional organization of the human substantia nigra (SN) using diffusion and functional MRI data from the Human Connectome Project. We identified a tripartite connectivity-based parcellation of SN with a limbic, cognitive, motor arrangement. The medial SN connects with limbic striatal and cortical regions and encodes value (greater response to monetary wins than losses during fMRI), while the ventral SN connects with associative regions of cortex and striatum and encodes salience (equal response to wins and losses). The lateral SN connects with somatomotor regions of striatum and cortex and also encodes salience. Behavioral measures from delay discounting and flanker tasks supported a role for the value-coding medial SN network in decisional impulsivity, while the salience-coding ventral SN network was associated with motor impulsivity. In sum, there is anatomical and functional heterogeneity of human SN, which underpins value versus salience coding, and impulsive choice versus impulsive action.
Data availability
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Human Connectome ProjectPublicly available at http://www.humanconnectome.org.
Article and author information
Author details
Funding
Canadian Institutes of Health Research (Foundation Scheme)
- Alain Dagher
Natural Sciences and Engineering Research Council of Canada (Discovery Grant)
- Alain Dagher
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: The authors agreed to the Open Access Data Use Terms of the Human Connectome Project (Van Essen et al 2013). Informed consent from participating individuals was obtained by the Human Connectome Project investigators. The Montreal Neurological Institute Research Ethics Board approved the use of Human Connectome Project data in the present project.
Copyright
© 2017, Zhang 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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