采用近似熵研究睡眠剥夺(sleep deprivation,SD)对脑认知功能的影响,评价SD引起的大脑功能区状态的非线性变化.12名受试者在正常睡眠和一夜SD之后分别接受视觉注意力测试,记录自发脑电和诱发脑电,采用二维插值构建19导脑电近似熵脑信息...采用近似熵研究睡眠剥夺(sleep deprivation,SD)对脑认知功能的影响,评价SD引起的大脑功能区状态的非线性变化.12名受试者在正常睡眠和一夜SD之后分别接受视觉注意力测试,记录自发脑电和诱发脑电,采用二维插值构建19导脑电近似熵脑信息图(brain information map,BIM).结果表明,在SD状态下,自发脑电的近似熵在全脑范围内有不同程度的下降,额叶处大脑偏侧性发生变化,复杂度的中心从左脑转移到右脑;前额叶处诱发脑电近似熵值降低,而顶叶和颞叶处则升高.脑电近似熵可以作为指标来评价SD对脑认知功能的负向影响。BIM的变化趋势与从生理学及影像学角度的分析相吻合,与线性方法的研究结论一致,在一定程度上可以反映大脑功能状态,提供一条评价脑功能区状态变化趋势的思路.展开更多
In this paper, we review the current state- of-the-art techniques used for understanding the inner workings of the brain at a systems level. The neural activity that governs our everyday lives involves an intricate co...In this paper, we review the current state- of-the-art techniques used for understanding the inner workings of the brain at a systems level. The neural activity that governs our everyday lives involves an intricate coordination of many processes that can be attributed to a variety of brain regions. On the surface, many of these functions can appear to be controlled by specific anatomical structures; however, in reality, numerous dynamic networks within the brain contribute to its function through an interconnected web of neuronal and synaptic pathways. The brain, in its healthy or pathological state, can therefore be best understood by taking a systems-level approach. While numerous neuroengineering technologies exist, we focus here on three major thrusts in the field of systems neuroengineering： neuroimaging, neural interfacing, and neuromodulation. Neuroimaging enables us to delineate the structural and functional organization of the brain, which is key in understanding how the neural system functions in both normal and disease states. Based on such knowledge, devices can be used either to communicate with the neural system, as in neural interface systems, or to modulate brain activity, as in neuromodulation systems. The consideration of these three fields is key to the development and application of neuro-devices. Feedback-based neuro-devices require the ability to sense neural activity （via a neuroimaging modality） through a neural interface （invasive or noninvasive） and ultimately to select a set of stimulation parameters in order to alter neural function via a neuromodulation modality. Systems neuroengineering refers to the use of engineering tools and technologies to image, decode, and modulate the brain in order to comprehend its functions and to repair its dysfunction. Interactions between these fields will help to shape the future of systems neuroengineering--to develop neurotechniques for enhancing the understanding of whole- brain function and dysfunction, and the management of neurological and mental disorders.展开更多
文摘采用近似熵研究睡眠剥夺(sleep deprivation,SD)对脑认知功能的影响,评价SD引起的大脑功能区状态的非线性变化.12名受试者在正常睡眠和一夜SD之后分别接受视觉注意力测试,记录自发脑电和诱发脑电,采用二维插值构建19导脑电近似熵脑信息图(brain information map,BIM).结果表明,在SD状态下,自发脑电的近似熵在全脑范围内有不同程度的下降,额叶处大脑偏侧性发生变化,复杂度的中心从左脑转移到右脑;前额叶处诱发脑电近似熵值降低,而顶叶和颞叶处则升高.脑电近似熵可以作为指标来评价SD对脑认知功能的负向影响。BIM的变化趋势与从生理学及影像学角度的分析相吻合,与线性方法的研究结论一致,在一定程度上可以反映大脑功能状态,提供一条评价脑功能区状态变化趋势的思路.
基金supported in part by the US National Institutes of Health (NIH) (EB006433, EY023101, EB008389,and HL117664)the US National Science Foundation (NSF) (CBET1450956, CBET-1264782, and DGE-1069104),to Bin He
文摘In this paper, we review the current state- of-the-art techniques used for understanding the inner workings of the brain at a systems level. The neural activity that governs our everyday lives involves an intricate coordination of many processes that can be attributed to a variety of brain regions. On the surface, many of these functions can appear to be controlled by specific anatomical structures; however, in reality, numerous dynamic networks within the brain contribute to its function through an interconnected web of neuronal and synaptic pathways. The brain, in its healthy or pathological state, can therefore be best understood by taking a systems-level approach. While numerous neuroengineering technologies exist, we focus here on three major thrusts in the field of systems neuroengineering： neuroimaging, neural interfacing, and neuromodulation. Neuroimaging enables us to delineate the structural and functional organization of the brain, which is key in understanding how the neural system functions in both normal and disease states. Based on such knowledge, devices can be used either to communicate with the neural system, as in neural interface systems, or to modulate brain activity, as in neuromodulation systems. The consideration of these three fields is key to the development and application of neuro-devices. Feedback-based neuro-devices require the ability to sense neural activity （via a neuroimaging modality） through a neural interface （invasive or noninvasive） and ultimately to select a set of stimulation parameters in order to alter neural function via a neuromodulation modality. Systems neuroengineering refers to the use of engineering tools and technologies to image, decode, and modulate the brain in order to comprehend its functions and to repair its dysfunction. Interactions between these fields will help to shape the future of systems neuroengineering--to develop neurotechniques for enhancing the understanding of whole- brain function and dysfunction, and the management of neurological and mental disorders.
