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大脑中的马尔可夫毯。

Markov blankets in the brain.

机构信息

Humboldt-Universität zu Berlin, Department of Philosophy & Berlin School of Mind and Brain, Germany; Wellcome Centre for Human Neuroimaging, University College London, United Kingdom.

Wellcome Centre for Human Neuroimaging, University College London, United Kingdom; Division of Social and Transcultural Psychiatry, Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Culture, Mind, and Brain Program, McGill University, Montreal, Quebec, Canada.

出版信息

Neurosci Biobehav Rev. 2021 Jun;125:88-97. doi: 10.1016/j.neubiorev.2021.02.003. Epub 2021 Feb 16.

Abstract

Recent characterisations of self-organising systems depend upon the presence of a 'Markov blanket': a statistical boundary that mediates the interactions between the inside and outside of a system. We leverage this idea to provide an analysis of partitions in neuronal systems. This is applicable to brain architectures at multiple scales, enabling partitions into single neurons, brain regions, and brain-wide networks. This treatment is based upon the canonical micro-circuitry used in empirical studies of effective connectivity, so as to speak directly to practical applications. The notion of effective connectivity depends upon the dynamic coupling between functional units, whose form recapitulates that of a Markov blanket at each level of analysis. The nuance afforded by partitioning neural systems in this way highlights certain limitations of 'modular' perspectives of brain function that only consider a single level of description.

摘要

最近对自组织系统的描述依赖于“马尔可夫毯”(Markov blanket)的存在:这是一个统计边界,调节着系统内部和外部之间的相互作用。我们利用这个概念来提供对神经元系统分区的分析。这个方法适用于多个尺度的大脑架构,可以将分区划分为单个神经元、脑区和全脑网络。这种处理方法基于在有效连接性的实证研究中使用的规范微电路,以便直接针对实际应用。有效连接性的概念取决于功能单元之间的动态耦合,其形式在每个分析层次上都再现了马尔可夫毯的形式。以这种方式对神经网络系统进行分区的细微差别突出了仅考虑单个描述层次的“模块”观点的某些局限性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6d7/8373616/517d0ba8d11c/gr1.jpg

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