TY - JOUR
T1 - Brain anomaly networks uncover heterogeneous functional reorganization patterns after stroke
AU - Zou, Yong
AU - Zhao, Zhiyong
AU - Yin, Dazhi
AU - Fan, Mingxia
AU - Small, Michael
AU - Liu, Zonghua
AU - Hilgetag, Claus C.
AU - Kurths, Jürgen
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Stroke has a large physical, psychological, and financial burden on patients, their families, and society. Based on functional networks (FNs) constructed from resting state fMRI data, network connectivity after stroke is commonly conjectured to be more randomly reconfigured. We find that this hypothesis depends on the severity of stroke. Head movement-corrected, resting-state fMRI data were acquired from 32 patients after stroke, and 37 healthy volunteers. We constructed anomaly FNs, which combine time series information of a patient with the healthy control group. We propose data-driven techniques to automatically identify regions of interest that are stroke relevant. Graph analysis based on anomaly FNs suggests consistently that strong connections in healthy controls are broken down specifically and characteristically for brain areas that are related to sensorimotor functions and frontoparietal control systems, but new links in stroke patients are rebuilt randomly from all possible areas. Entropic measures of complexity are proposed for characterizing the functional connectivity reorganization patterns, which are correlated with hand and wrist function assessments of stroke patients and show high potential for clinical use.
AB - Stroke has a large physical, psychological, and financial burden on patients, their families, and society. Based on functional networks (FNs) constructed from resting state fMRI data, network connectivity after stroke is commonly conjectured to be more randomly reconfigured. We find that this hypothesis depends on the severity of stroke. Head movement-corrected, resting-state fMRI data were acquired from 32 patients after stroke, and 37 healthy volunteers. We constructed anomaly FNs, which combine time series information of a patient with the healthy control group. We propose data-driven techniques to automatically identify regions of interest that are stroke relevant. Graph analysis based on anomaly FNs suggests consistently that strong connections in healthy controls are broken down specifically and characteristically for brain areas that are related to sensorimotor functions and frontoparietal control systems, but new links in stroke patients are rebuilt randomly from all possible areas. Entropic measures of complexity are proposed for characterizing the functional connectivity reorganization patterns, which are correlated with hand and wrist function assessments of stroke patients and show high potential for clinical use.
KW - Brain networks
KW - Connectivity complexity
KW - Random reorganization hypothesis
KW - Stroke
UR - http://www.scopus.com/inward/record.url?scp=85052105538&partnerID=8YFLogxK
U2 - 10.1016/j.nicl.2018.08.008
DO - 10.1016/j.nicl.2018.08.008
M3 - Article
C2 - 30167372
AN - SCOPUS:85052105538
VL - 20
SP - 523
EP - 530
JO - NeuroImage: Clinical
JF - NeuroImage: Clinical
SN - 2213-1582
ER -