Literature DB >> 31077843

Multimodal characterization of the human nucleus accumbens.

Samuel Cd Cartmell1, Qiyuan Tian2, Brandon J Thio3, Christoph Leuze4, Li Ye5, Nolan R Williams6, Grant Yang2, Gabriel Ben-Dor6, Karl Deisseroth7, Warren M Grill3, Jennifer A McNab4, Casey H Halpern8.   

Abstract

Dysregulation of the nucleus accumbens (NAc) is implicated in numerous neuropsychiatric disorders. Treatments targeting this area directly (e.g. deep brain stimulation) demonstrate variable efficacy, perhaps owing to non-specific targeting of a functionally heterogeneous nucleus. Here we provide support for this notion, first observing disparate behavioral effects in response to direct simulation of different locations within the NAc in a human patient. These observations motivate a segmentation of the NAc into subregions, which we produce from a diffusion-tractography based analysis of 245 young, unrelated healthy subjects. We further explore the mechanism of these stimulation-induced behavioral responses by identifying the most probable subset of axons activated using a patient-specific computational model. We validate our diffusion-based segmentation using evidence from several modalities, including MRI-based measures of function and microstructure, human post-mortem immunohistochemical staining, and cross-species comparison of cortical-NAc projections that are known to be conserved. Finally, we visualize the passage of individual axon bundles through one NAc subregion in a post-mortem human sample using CLARITY 3D histology corroborated by 7T tractography. Collectively, these findings extensively characterize human NAc subregions and provide insight into their structural and functional distinctions with implications for stereotactic treatments targeting this region.
Copyright © 2019. Published by Elsevier Inc.

Entities:  

Keywords:  Accumbens; CLARITY; Computational modeling; Core; DBS; Shell; Tractography

Mesh:

Year:  2019        PMID: 31077843      PMCID: PMC7341972          DOI: 10.1016/j.neuroimage.2019.05.019

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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