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单神经元分辨率下全脑固有时间尺度的组织架构

Brain-wide organization of intrinsic timescales at single-neuron resolution.

作者信息

Shi Yan-Liang, Zeraati Roxana, Levina Anna, Engel Tatiana A

机构信息

Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.

Max Planck Institute for Biological Cybernetics, Tübingen, BW, Germany.

出版信息

bioRxiv. 2025 Aug 30:2025.08.30.673281. doi: 10.1101/2025.08.30.673281.

Abstract

Variations in intrinsic neural timescales across the mammalian forebrain reflect the anatomical structure and functional specialization of brain areas and individual neurons. Yet, the organization of timescales beyond the forebrain remains unexplored. We analyzed intrinsic timescales of single neurons across the entire mouse brain. Median timescales were up to fivefold longer in the midbrain and hindbrain than in the forebrain. Spatial patterns of gene expression predicted timescale variation at a resolution finer than brain-area boundaries. Across neurons, the diversity of timescales revealed a multiscale architecture, in which fast timescales determined regional differences in medians, while slow timescales universally followed a power-law distribution with an exponent near 2, indicating a shared dynamical regime across the brain consistent with the edge of instability or chaos. These organizing principles for the dynamics of single neurons across the brain provide a foundation for linking cellular activity with regional specialization and brain-wide computation.

摘要

哺乳动物前脑内在神经时间尺度的变化反映了脑区和单个神经元的解剖结构及功能特化。然而,前脑之外的时间尺度组织仍未得到探索。我们分析了整个小鼠脑内单个神经元的内在时间尺度。中脑和后脑的中位时间尺度比前脑长至多五倍。基因表达的空间模式在比脑区边界更精细的分辨率上预测了时间尺度变化。在神经元群体中,时间尺度的多样性揭示了一种多尺度结构,其中快速时间尺度决定了中位数的区域差异,而慢速时间尺度普遍遵循指数接近2的幂律分布,表明全脑存在一个与不稳定边缘或混沌相一致的共享动力学机制。这些关于全脑单个神经元动力学的组织原则为将细胞活动与区域特化及全脑计算联系起来奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/69a4/12407892/16f80aafd5e9/nihpp-2025.08.30.673281v1-f0001.jpg

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