Measuring interconnection of the residual cortical functional islands in persistent vegetative state and minimal conscious state with EEG nonlinear analysis - Wu, Dong-yu; Cai, Gui; Zorowitz, Richard D.; Yuan, Ying; Wang, Jie; Song, Wei-qun (Clinical neurophysiology, 2011)
► Cross-approximate entropy can measure the interconnection of residual cortical functional islands in unconscious patients. ► Interconnection of local and distant cortical networks in the minimal conscious state is greater than that in the persistent vegetative state. ► Improving interconnection of residual cortical functional islands might contribute to recovery from unconscious states. The aim of the study is to investigate the cortical response to painful and auditory stimuli for subjects in persistent vegetative state (PVS) and minimal conscious state (MCS), and measure the interconnection of the residual cortical functional islands with electroencephalographic (EEG) nonlinear dynamic analysis (NDA). Thirty PVS subjects, 20 MCS subjects and 30 subjects in normal conscious state (NCS) were involved in the study. EEG was recorded under three conditions: eyes closed, auditory stimuli and painful stimuli. EEG nonlinear index of cross-approximate entropy (C-ApEn) was calculated for all subjects. Interconnection of local and distant cortical networks of patients in PVS was generally suppressed, and painful or auditory stimulation could hardly cause any activation of associative cortices. Instead, interconnection of local cortical networks of patients in MCS improved significantly. The only significant difference with the NCS existed in the unaffected distant cortical networks. Interconnection of local and distant cortical networks in MCS is superior to that of PVS. NDA could measure interconnection of the residual cortical functional islands with associative cortices in the unconscious patients. NDA can characterise the interconnection of cortical networks for the unconscious state and provide some information of unconsciousness at the awareness level.