脑动力学的生物物理复杂性:展望

N. Shettigar, Chunbin Yang, Kuan-Chung Tu, C. Suh
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引用次数: 4

摘要

人脑是一个复杂的网络,其集合时间进化是由其细胞成分(如神经元和神经胶质细胞)的累积相互作用指导的。通过化学神经传递和受体激活,这些个体通过触发各种细胞活动,从内部生物重组到与其他网络代理的外部相互作用,在不同程度上相互作用。因此,这种局部动态连接介导细胞对彼此的影响程度和方向是高度非线性的,并分别促进非线性和潜在混沌的多细胞高阶协作。因此,作为一个统计物理系统,局部相互作用的非线性顶点产生复杂的全局突发网络行为,使宏观大脑网络的高度动态、自适应和高效响应成为可能。微观状态的重新配置通常通过突触和结构可塑性机制来促进,这些机制改变了神经元相互之间的耦合程度(影响的大小),从而决定了神经细胞群体中协调的宏观状态出现的类型。这些可以以同步集群的局部区域的形式出现,这些集群的中心频率由单个神经细胞协作组成,作为集体组织的基本形式。单一的同步模式不足以满足大脑的计算需求。因此,当神经成分相互影响时(细胞成分、同步种群的多个集群、脑核甚至脑区域),不同的神经行为模式相互作用,产生与脑网络动态状态相对应的神经活动的紧急时空频谱带宽。此外,分层和自相似的结构支持这些网络属性有效和高效地运行。神经科学自诞生以来已经走过了漫长的道路;然而,对大脑如何工作的全面和直观的理解仍然是错误的。越来越明显的是,对于大脑中宏大的生物物理复杂性,任何单一的观点都是不够的。本文的目的是通过多种角度提供展望,包括基本的生物学机制以及这些机制如何在自然的物理约束下运作。在评估先前研究工作的状态后,在本文中,我们确定了未来研究工作应该追求的路径,以激发神经科学的进步。
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On The Biophysical Complexity of Brain Dynamics: An Outlook
The human brain is a complex network whose ensemble time evolution is directed by the cumulative interactions of its cellular components, such as neurons and glia cells. Coupled through chemical neurotransmission and receptor activation, these individuals interact with one another to varying degrees by triggering a variety of cellular activity from internal biological reconfigurations to external interactions with other network agents. Consequently, such local dynamic connections mediating the magnitude and direction of influence cells have on one another are highly nonlinear and facilitate, respectively, nonlinear and potentially chaotic multicellular higher-order collaborations. Thus, as a statistical physical system, the nonlinear culmination of local interactions produces complex global emergent network behaviors, enabling the highly dynamical, adaptive, and efficient response of a macroscopic brain network. Microstate reconfigurations are typically facilitated through synaptic and structural plasticity mechanisms that alter the degree of coupling (magnitude of influence) neurons have upon each other, dictating the type of coordinated macrostate emergence in populations of neural cells. These can emerge in the form of local regions of synchronized clusters about a center frequency composed of individual neural cell collaborations as a fundamental form of collective organization. A single mode of synchronization is insufficient for the computational needs of the brain. Thus, as neural components influence one another (cellular components, multiple clusters of synchronous populations, brain nuclei, and even brain regions), different patterns of neural behavior interact with one another to produce an emergent spatiotemporal spectral bandwidth of neural activity corresponding to the dynamical state of the brain network. Furthermore, hierarchical and self-similar structures support these network properties to operate effectively and efficiently. Neuroscience has come a long way since its inception; however, a comprehensive and intuitive understanding of how the brain works is still amiss. It is becoming evident that any singular perspective upon the grandiose biophysical complexity within the brain is inadequate. It is the purpose of this paper to provide an outlook through a multitude of perspectives, including the fundamental biological mechanisms and how these operate within the physical constraints of nature. Upon assessing the state of prior research efforts, in this paper, we identify the path future research effort should pursue to inspire progress in neuroscience.
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