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Research On Neural Change Mechanism After Spinal Cord Injury Based On EEG

Posted on:2015-01-03Degree:MasterType:Thesis
Country:ChinaCandidate:Z Q YanFull Text:PDF
GTID:2284330452455686Subject:Pattern Recognition and Intelligent Systems
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With the development of social economy, the incidence of spinal cord injury (SCI)grows, attracting more attention on the prognosis of SCI. Because of non-injury and hightemporal resolution of electroencephalogram (EEG), the researches of the mechanism ofEEG changes and neural plasticity become hot issue in brain science.We go deep into the research of the mechanism of EEG changes after SCI in thispaper, analyze the alteration of scale EEG and cortical current densty reconstruction (CDR)in treadmill walking movement after SCI. In this paper, we expound the background,significance and development of EEG research after SCI. And then basic knowledge ofEEG and primary algorithms of EEG processing are described in details. We designexperimental paradigm and apply64channels Scan4.5acquisition system to record EEG.Event-related potential (ERP), event-related (de)synchronization (ERS/ERD) and powerspectrum estimation of EEG are analyzed based on the methods of EEG processing in timedomain, frequency domain, and time-frequency to discuss the mechanism of EEG changes.We find that the reduced sensory inputs due to spinal cord injury lead to the developmentof denervation hypersensitization, which enhance ERP and ERS in specific frequency band,Moreover, the enhancement pattern is significantly associated with SCI level. Thediscovery could help estimate spinal cord injury and provide potential intervention for theimprovement of functions. To solve the problem that we can not map scale EEG to corticalsignal directly, we apply source reconstruction for current density reconstruction (CDR),and then build complex brain network for further analysis of mechanism of cortical signalchange after SCI.
Keywords/Search Tags:spinal cord injury, electroencephalogram, event-related (de) synchronization, current density, brain network
PDF Full Text Request
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