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浦肯野细胞模型:过去、现在与未来。

Purkinje cell models: past, present and future.

作者信息

Fernández Santoro Elías Mateo, Karim Arun, Warnaar Pascal, De Zeeuw Chris I, Badura Aleksandra, Negrello Mario

机构信息

Department of Neuroscience, Erasmus MC, Rotterdam, Netherlands.

Netherlands Institute for Neuroscience, Royal Academy of Arts and Sciences, Amsterdam, Netherlands.

出版信息

Front Comput Neurosci. 2024 Jul 10;18:1426653. doi: 10.3389/fncom.2024.1426653. eCollection 2024.

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.

摘要

对浦肯野细胞(PC)活动动力学的研究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。在小脑皮质(CC)内,这些神经元接收所有传入的感觉和运动信息,对其进行转换并产生整个小脑输出。CC相对均匀且重复的结构是所有脊椎动物物种共有的,这表明所有PC共享一种单一的计算机制。虽然自70年代以来就已经开发了PC模型,但目前缺乏对当代模型的全面综述。在这里,我们提供了PC模型的概述,从专注于单细胞细胞内PC动力学的模型,到包括突触和突触外输入的复杂模型。我们回顾了PC模型如何能够重现神经元的生理活动,包括放电模式、电流和多稳态动力学、平台电位、钙信号传导、内在和突触可塑性以及输入/输出计算。我们考虑了专注于体细胞和树突计算的模型。我们的综述针对已知的生理数据对PC模型进行了关键的性能分析。我们期望我们的综述有助于指导未来计算模型的开发,这些模型能够在小脑计算的背景下捕捉真实的PC动力学。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b04a/11266113/049f21eae41c/fncom-18-1426653-g0001.jpg

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