疼痛是一种不愉快的感觉和情感体验,其涉及到多级神经加工过程,神经活动模式十分复杂。非侵入性脑功能成像技术可以实现在全脑水平上解析人类疼痛的神经机制。其中,功能磁共振成像(functional magnetic resonance imaging,fMRI)技术因...疼痛是一种不愉快的感觉和情感体验,其涉及到多级神经加工过程,神经活动模式十分复杂。非侵入性脑功能成像技术可以实现在全脑水平上解析人类疼痛的神经机制。其中,功能磁共振成像(functional magnetic resonance imaging,fMRI)技术因具有高空间分辨率的优势,使其在探索人类疼痛的神经机制研究中得到了广泛的应用。本文聚焦于人类疼痛的fMRI研究,首先概述了疼痛相关的脑响应研究发现,梳理了与疼痛加工相关的多个脑区功能活动变化。然而,调节单一脑区的功能难以影响疼痛体验,提示疼痛加工涉及多脑区之间的协同作用。由此,本文综述了参与疼痛加工的脑区之间交互现象,这些研究揭示了多条神经通路以串行或并行的方式构成了复杂的疼痛神经网络,进而处理与疼痛相关的感觉、情绪和认知信息。基于上述研究,近年来不断更迭发展的超高场强f MRI及脑脊同步成像技术,助力人类疼痛研究深入到核团和脊髓层面,拓展了疼痛神经网络的精细度和全面性。综上,本文提出了人类疼痛的神经网络表征,并以此为基础指导神经调控技术调节异常的神经网络表征,进而实现缓解疼痛症状的目标。最后,本文讨论了当前疼痛神经表征研究的局限性,并提出了探索疼痛特异性表征,对比实验诱发性疼痛和临床自发性疼痛,以及疼痛个体化表征的研究展望。展开更多
A method and results of identification of wear debris using their morphological features are presented. The color images of wear debris were used as initial data. Each particle was characterized by a set of numerical ...A method and results of identification of wear debris using their morphological features are presented. The color images of wear debris were used as initial data. Each particle was characterized by a set of numerical parameters combined by its shape, color and surface texture features through a computer vision system. Those features were used as input vector of artificial neural network for wear debris identification. A radius basis function (RBF) network based model suitable for wear debris recognition was established, and its algorithm was presented in detail. Compared with traditional recognition methods, the RBF network model is faster in convergence, and higher in accuracy.展开更多
文摘疼痛是一种不愉快的感觉和情感体验,其涉及到多级神经加工过程,神经活动模式十分复杂。非侵入性脑功能成像技术可以实现在全脑水平上解析人类疼痛的神经机制。其中,功能磁共振成像(functional magnetic resonance imaging,fMRI)技术因具有高空间分辨率的优势,使其在探索人类疼痛的神经机制研究中得到了广泛的应用。本文聚焦于人类疼痛的fMRI研究,首先概述了疼痛相关的脑响应研究发现,梳理了与疼痛加工相关的多个脑区功能活动变化。然而,调节单一脑区的功能难以影响疼痛体验,提示疼痛加工涉及多脑区之间的协同作用。由此,本文综述了参与疼痛加工的脑区之间交互现象,这些研究揭示了多条神经通路以串行或并行的方式构成了复杂的疼痛神经网络,进而处理与疼痛相关的感觉、情绪和认知信息。基于上述研究,近年来不断更迭发展的超高场强f MRI及脑脊同步成像技术,助力人类疼痛研究深入到核团和脊髓层面,拓展了疼痛神经网络的精细度和全面性。综上,本文提出了人类疼痛的神经网络表征,并以此为基础指导神经调控技术调节异常的神经网络表征,进而实现缓解疼痛症状的目标。最后,本文讨论了当前疼痛神经表征研究的局限性,并提出了探索疼痛特异性表征,对比实验诱发性疼痛和临床自发性疼痛,以及疼痛个体化表征的研究展望。
文摘A method and results of identification of wear debris using their morphological features are presented. The color images of wear debris were used as initial data. Each particle was characterized by a set of numerical parameters combined by its shape, color and surface texture features through a computer vision system. Those features were used as input vector of artificial neural network for wear debris identification. A radius basis function (RBF) network based model suitable for wear debris recognition was established, and its algorithm was presented in detail. Compared with traditional recognition methods, the RBF network model is faster in convergence, and higher in accuracy.
