Open AccessCognitive profiles and associated structural brain networks in a multimorbid sample of marginalized adults
Author(s) -
Kristina M. Gicas,
Andrea A. Jones,
William J. Panenka,
Chantelle J. Giesbrecht,
Donna J. Lang,
Fidel VilaRodriguez,
Olga Leonova,
Alasdair M. Barr,
Ric M. Procyshyn,
Wayne Su,
Alexander Rauscher,
Alexandra T. Vertinsky,
Tari Buchanan,
G. William MacEwan,
Allen E. Thornton,
William G. Honer
Publication year - 2019
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0218201
Subject(s) - cognition , psychology , gyrification , effects of sleep deprivation on cognitive performance , cognitive skill , clinical psychology , neuroscience , cerebral cortex
Cognition is impaired in homeless and vulnerably housed persons. Within this heterogeneous and multimorbid group, distinct profiles of cognitive dysfunction are evident. However, little is known about the underlying neurobiological substrates. Imaging structural covariance networks provides a novel investigative strategy to characterizing relationships between brain structure and function within these different cognitive subgroups. Method Participants were 208 homeless and vulnerably housed persons. Cluster analysis was used to group individuals on the basis of similarities in cognitive functioning in the areas of attention, memory, and executive functioning. The principles of graph theory were applied to construct two brain networks for each cognitive group, using measures of cortical thickness and gyrification. Global and regional network properties were compared across networks for each of the three cognitive clusters. Results Three cognitive groups were defined by: higher cognitive functioning across domains (Cluster 1); lower cognitive functioning with a decision-making strength (Cluster 3); and an intermediate group with a relative executive functioning weakness (Cluster 2). Between-group differences were observed for cortical thickness, but not gyrification networks. The lower functioning cognitive group exhibited higher segregation and reduced integration, higher centrality in select nodes, and less spatially compact modules compared with the two other groups. Conclusions The cortical thickness network differences of Cluster 3 suggest that major disruptions in structural connectivity underlie cognitive dysfunction in a subgroup of people who have a high multimorbid illness burden and who are vulnerably housed or homeless. The origins, and possible plasticity of these structure-function relationships identified with network analysis warrant further study.