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神经元群体跨越静止到活跃边界及分支的转变

Neuronal Population Transitions Across a Quiescent-to-Active Frontier and Bifurcation.

作者信息

Juanico Drandreb Earl O

机构信息

DataSc/ense TechnoCoRe, Technological Institute of the Philippines, Quezon City, Philippines.

NICER Program, Center for Advanced Batteries, Quezon City, Philippines.

出版信息

Front Physiol. 2022 Feb 10;13:840546. doi: 10.3389/fphys.2022.840546. eCollection 2022.

DOI:10.3389/fphys.2022.840546
PMID:35222095
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8867020/
Abstract

The mechanistic understanding of why neuronal population activity hovers on criticality remains unresolved despite the availability of experimental results. Without a coherent mathematical framework, the presence of power-law scaling is not straightforward to reconcile with findings implying epileptiform activity. Although multiple pictures have been proposed to relate the power-law scaling of avalanche statistics to phase transitions, the existence of a phase boundary in parameter space is until now an assumption. Herein, a framework based on differential inclusions, which departs from approaches constructed from differential equations, is shown to offer an adequate consolidation of evidences apparently connected to criticality and those linked to hyperexcitability. Through this framework, the phase boundary is elucidated in a parameter space spanned by variables representing levels of excitation and inhibition in a neuronal network. The interpretation of neuronal populations based on this approach offers insights on the role of pharmacological and endocrinal signaling in the homeostatic regulation of neuronal population activity.

摘要

尽管已有实验结果,但关于神经元群体活动为何徘徊在临界状态的机制理解仍未得到解决。没有一个连贯的数学框架,幂律缩放的存在就难以与暗示癫痫样活动的研究结果相协调。尽管已经提出了多种图景来将雪崩统计的幂律缩放与相变联系起来,但到目前为止,参数空间中相边界的存在仍是一个假设。在此,一个基于微分包含的框架被证明能够充分整合明显与临界性相关的证据以及与过度兴奋相关的证据,该框架不同于由微分方程构建的方法。通过这个框架,在由代表神经网络中兴奋和抑制水平的变量所构成的参数空间中阐明了相边界。基于这种方法对神经元群体的解释为药理学和内分泌信号在神经元群体活动稳态调节中的作用提供了见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/384f/8867020/20abb0ee2d87/fphys-13-840546-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/384f/8867020/4e41a13d8857/fphys-13-840546-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/384f/8867020/8160ed2ea97b/fphys-13-840546-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/384f/8867020/a095b6cf25a3/fphys-13-840546-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/384f/8867020/800f4dc9cbb7/fphys-13-840546-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/384f/8867020/20abb0ee2d87/fphys-13-840546-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/384f/8867020/4e41a13d8857/fphys-13-840546-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/384f/8867020/8160ed2ea97b/fphys-13-840546-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/384f/8867020/a095b6cf25a3/fphys-13-840546-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/384f/8867020/800f4dc9cbb7/fphys-13-840546-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/384f/8867020/20abb0ee2d87/fphys-13-840546-g005.jpg

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