Elías Mateo Fernández Santoro, Arun Karim, Pascal Warnaar, Chris I. De Zeeuw, Aleksandra Badura, Mario Negrello
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引用次数: 0
Abstract
The investigation of the dynamics of Purkinje cell (PC) activity is crucial to unravel the role of the cerebellum in motor control, learning and cognitive processes. Within the cerebellar cortex (CC), these neurons receive all the incoming sensory and motor information, transform it and generate the entire cerebellar output. The relatively homogenous and repetitive structure of the CC, common to all vertebrate species, suggests a single computation mechanism shared across all PCs. While PC models have been developed since the 70′s, a comprehensive review of contemporary models is currently lacking. Here, we provide an overview of PC models, ranging from the ones focused on single cell intracellular PC dynamics, through complex models which include synaptic and extrasynaptic inputs. We review how PC models can reproduce physiological activity of the neuron, including firing patterns, current and multistable dynamics, plateau potentials, calcium signaling, intrinsic and synaptic plasticity and input/output computations. We consider models focusing both on somatic and on dendritic computations. Our review provides a critical performance analysis of PC models with respect to known physiological data. We expect our synthesis to be useful in guiding future development of computational models that capture real-life PC dynamics in the context of cerebellar computations.
研究浦肯野细胞(PC)的动态活动对于揭示小脑在运动控制、学习和认知过程中的作用至关重要。在小脑皮层(CC)中,这些神经元接收所有传入的感觉和运动信息,将其转化并产生整个小脑输出。小脑皮层的结构相对单一且具有重复性,是所有脊椎动物的共同特征,这表明所有小脑皮层都有一个共同的计算机制。虽然 PC 模型自上世纪 70 年代就已出现,但目前还缺乏对当代模型的全面回顾。在本文中,我们将概述 PC 模型,从侧重于单细胞胞内 PC 动态的模型,到包括突触和突触外输入的复杂模型。我们回顾了 PC 模型如何再现神经元的生理活动,包括发射模式、电流和多稳态动力学、高原电位、钙信号、内在和突触可塑性以及输入/输出计算。我们考虑的模型既关注体细胞计算,也关注树突计算。我们的综述结合已知的生理数据,对 PC 模型进行了重要的性能分析。我们希望我们的综述有助于指导未来计算模型的开发,从而在小脑计算的背景下捕捉现实生活中的PC动态。
期刊介绍:
Frontiers in Computational Neuroscience is a first-tier electronic journal devoted to promoting theoretical modeling of brain function and fostering interdisciplinary interactions between theoretical and experimental neuroscience. Progress in understanding the amazing capabilities of the brain is still limited, and we believe that it will only come with deep theoretical thinking and mutually stimulating cooperation between different disciplines and approaches. We therefore invite original contributions on a wide range of topics that present the fruits of such cooperation, or provide stimuli for future alliances. We aim to provide an interactive forum for cutting-edge theoretical studies of the nervous system, and for promulgating the best theoretical research to the broader neuroscience community. Models of all styles and at all levels are welcome, from biophysically motivated realistic simulations of neurons and synapses to high-level abstract models of inference and decision making. While the journal is primarily focused on theoretically based and driven research, we welcome experimental studies that validate and test theoretical conclusions.
Also: comp neuro