Disrupted Strength and Stability of Regional Brain Activity in Disorder of Consciousness Patients: A Resting-State Functional Magnetic Resonance Imaging Study. (10th August 2021)

• Record Type: Journal Article
• Authors: Yu, Yamei; Chen, Sicong; Zhang, Li; Liu, Xiaoyan; Tan, Xufei; Luo, Benyan
• Is Part Of: Neuroscience. Volume 469(2021)
• Page Start: 59
• Page End: 67
• Publication Date: 2021-08-10
• Subjects: ACC accuracy -- AG angular cortex -- ALFF amplitude of the low-frequency fluctuation -- AUC area under curve -- CRS-R Coma Recovery Scale-Revised -- CV coefficient of variation -- dfALFF dynamic fractional amplitude of the low-frequency fluctuation -- dFC dynamic functional connectivity -- DMN default mode network -- DOC disorder of consciousness -- EMCS emerge from minimally conscious state -- fALFF fractional amplitude of the low-frequency fluctuation -- FD framewise displacement -- fMRI functional magnetic resonance imaging -- IFG inferior frontal gyrus -- MCC middle cingulate cortex -- MCS minimally conscious state -- MFG middle frontal gyrus -- MNI Montreal Neurological Institute -- MOG middle occipital gyrus -- mPFC medial prefrontal cortex -- ROC receiver operating characteristic -- ROIs regions of interest -- SD standard deviation -- SMG supramarginal gyrus -- SVM support vector machine -- TR repetition times -- VS/UWS vegetative state/unresponsive wakefulness syndrome -- WM white matter; disorders of consciousness -- fMRI -- fALFF -- temporal dynamics -- machine learning; Neurochemistry -- Periodicals; Neurophysiology -- Periodicals; Neurology -- Periodicals; Neurochimie -- Périodiques; Neurophysiologie -- Périodiques; Neurochemistry; Neurophysiology; Electronic journals; Periodicals; Electronic journals; 612.8
• DOI: 10.1016/j.neuroscience.2021.06.031
• Languages: English
• ISSNs: 0306-4522

Abstract

Highlights: Both static and dynamic analyses of local neural activity were investigated in patients of disorder of consciousness (DOC). The dynamic analysis could unravel more pathological regions than the static analysis. Sub-frequency analysis of fALFF indicated a potential frequency dependent alteration of the default mode network in DOC patients. The DOC classifier established on fALFF achieved the highest classification accuracy. Abstract: Although the resting-state networks of patients with disorders of consciousness (DOC) have been widely investigated, the underlying neural mechanisms remain unclear. Here we aimed to explore the static and dynamic alterations in the regional brain activity in patients with DOC and detect the diagnostic ability of each index. Nineteen patients in the vegetative state, 19 in the minimally conscious state (MCS), and 41 healthy controls were recruited for this study. The fractional amplitudes of the low-frequency fluctuation (fALFF) and dynamic fALFF (dfALFF) values were computed, and intergroup differences were detected by analysis of variance. Sub-frequency analysis (slow-4 band and slow-5 band) of fALFF was also performed. Machine learning classifiers were established based on these measures to explore the classification accuracies between patients and controls. The fALFF and dfALFF analyses showed significant intergroup differences in the medial prefrontal gyrus, precuneus, left angular gyrus, and right middle cingulate cortex (MCC), whereas only the dfALFF analysis revealed aberrations in the right inferior frontal gyrus (IFG), right angular gyrus, left supramarginal gyrus (SMG), and left middle occipital gyrus (MOG). Sub-frequency analysis suggested a potential frequency dependent alteration in the default mode network (DMN). The fALFF model exhibited a higher classification accuracy (ACC) (90.50%) than the dfALFF model (86.29%). The combination of fALFF and dfALFF did not improve classification performance. The strength and stability of regional brain activities were disrupted in patients with DOC. Our findings demonstrate that dynamic analysis may reveal more pathological regions and provide a better understanding of the pathophysiologic mechanisms of DOC.