Enhanced Plasticity of Human Evoked Potentials by Visual Noise During the Intervention of Steady-State Stimulation Based Brain-Computer Interface
文献类型:期刊论文
作者 | Han, Chengcheng2; Han, Xingliang2; Xie J(谢俊)1,2,3; Xu GH(徐光华)2,3; Zhao XG(赵新刚)1![]() |
刊名 | FRONTIERS IN NEUROROBOTICS
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出版日期 | 2018 |
卷号 | 12页码:1-10 |
关键词 | Brain-computer Interface (Bci) Motion-reversal Stimulation Plasticity Visual Evoked Potential (Vep) Visual Noise |
ISSN号 | 1662-5218 |
产权排序 | 1 |
英文摘要 | Neuroplasticity, also known as brain plasticity, is an inclusive term that covers the permanent changes in the brain during the course of an individual's life, and neuroplasticity can be broadly defined as the changes in function or structure of the brain in response to the external and/or internal influences. Long-term potentiation (LTP), a well-characterized form of functional synaptic plasticity, could be influenced by rapid-frequency stimulation (or "tetanus") within in vivo human sensory pathways. Also, stochastic resonance (SR) has brought new insight into the field of visual processing for the study of neuroplasticity. In the present study, a brain-computer interface (BCI) intervention based on rapid and repetitive motion-reversal visual stimulation (i.e., a "tetanizing" stimulation) associated with spatiotemporal visual noise was implemented. The goal was to explore the possibility that the induction of LTP-like plasticity in the visual cortex may be enhanced by the SR formalism via changes in the amplitude of visual evoked potentials (VEPs) measured non-invasively from the scalp of healthy subjects. Changes in the absolute amplitude of P1 and N1 components of the transient VEPs during the initial presentation of the steady-state stimulation were used to evaluate the LIP-like plasticity between the non-noise and noise-tagged BCI interventions. We have shown that after adding a moderate visual noise to the rapid-frequency visual stimulation, the degree of the N1 negativity was potentiated following an similar to 40-min noise-tagged visual tetani. This finding demonstrated that the SR mechanism could enhance the plasticity-like changes in the human visual cortex. |
WOS关键词 | LONG-TERM POTENTIATION ; SYNAPTIC PLASTICITY ; FREQUENCY ; RECOVERY ; CORTEX ; LTP ; IMPAIRMENT ; INDUCTION ; PATHWAY ; MEMORY |
资助项目 | National Natural Science Foundation of China[61503298] ; National Natural Science Foundation of China[51505363] ; Natural Science Foundation of Shaanxi Province of China[2016JQ6002] ; Fundamental Research Funds for the Central Universities[xjj2016006] ; State Key Laboratory of Robotics[2016-O11] |
WOS研究方向 | Computer Science ; Robotics ; Neurosciences & Neurology |
语种 | 英语 |
WOS记录号 | WOS:000451716500001 |
资助机构 | National Natural Science Foundation of China ; Natural Science Foundation of Shaanxi Province of China ; Fundamental Research Funds for the Central Universities ; State Key Laboratory of Robotics |
源URL | [http://ir.sia.cn/handle/173321/23674] ![]() |
专题 | 沈阳自动化研究所_机器人学研究室 |
通讯作者 | Xie J(谢俊); Xu GH(徐光华) |
作者单位 | 1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 2.School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China 3.State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, ChinaEngn, Xian, Shaanxi, Peoples R China |
推荐引用方式 GB/T 7714 | Han, Chengcheng,Han, Xingliang,Xie J,et al. Enhanced Plasticity of Human Evoked Potentials by Visual Noise During the Intervention of Steady-State Stimulation Based Brain-Computer Interface[J]. FRONTIERS IN NEUROROBOTICS,2018,12:1-10. |
APA | Han, Chengcheng.,Han, Xingliang.,Xie J.,Xu GH.,Zhao XG.,...&Wang J.(2018).Enhanced Plasticity of Human Evoked Potentials by Visual Noise During the Intervention of Steady-State Stimulation Based Brain-Computer Interface.FRONTIERS IN NEUROROBOTICS,12,1-10. |
MLA | Han, Chengcheng,et al."Enhanced Plasticity of Human Evoked Potentials by Visual Noise During the Intervention of Steady-State Stimulation Based Brain-Computer Interface".FRONTIERS IN NEUROROBOTICS 12(2018):1-10. |
入库方式: OAI收割
来源:沈阳自动化研究所
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