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A parcellation-based connectomic model of hemispatial neglect.

Authors :
Ahsan SA
Dadario NB
Dhaliwal J
Briggs RG
Osipowicz K
Ahsan SM
Chendeb K
Conner AK
O'Neal CM
Glenn CA
Sughrue ME
Source :
Journal of neuroimaging : official journal of the American Society of Neuroimaging [J Neuroimaging] 2024 Mar-Apr; Vol. 34 (2), pp. 267-279. Date of Electronic Publication: 2023 Dec 19.
Publication Year :
2024

Abstract

Background and Purpose: Hemispatial neglect is characterized by a reduced awareness to stimuli on the contralateral side. Current literature suggesting that damage to the right parietal lobe and attention networks may cause hemispatial neglect is conflicting and can be improved by investigating a connectomic model of the "neglect system" and the anatomical specificity of regions involved in it.<br />Methods: A meta-analysis of voxel-based morphometry magnetic resonance imaging (MRI) studies of hemispatial neglect was used to identify regions associated with neglect. We applied parcellation schemes to these regions and performed diffusion spectrum imaging (DSI) tractography to determine their connectivity. By overlaying neglect areas and maps of the attention networks, we studied the relationship between them.<br />Results: The meta-analysis generated a list of 13 right hemisphere parcellations. These 13 neglect-related parcellations were predominantly linked by the superior longitudinal fasciculus (SLF) throughout a fronto-parietal-temporal network. We found that the dorsal and ventral attention networks showed partial overlap with the neglect system and included various other higher-order networks.<br />Conclusions: We provide an anatomically specific connectomic model of the neurobehavioral substrates underlying hemispatial neglect. Our model suggests a fronto-parietal-temporal network linked via the SLF supports the functions impaired in neglect and implicates various higher-order networks which are not limited to the attention networks.<br /> (© 2023 American Society of Neuroimaging.)

Details

Language :
English
ISSN :
1552-6569
Volume :
34
Issue :
2
Database :
MEDLINE
Journal :
Journal of neuroimaging : official journal of the American Society of Neuroimaging
Publication Type :
Academic Journal
Accession number :
38115162
Full Text :
https://doi.org/10.1111/jon.13176