空间分叉:新皮质功能模块化的出现。

Xiao-Jing Wang, Junjie Jiang, Roxana Zeraati, Aldo Battista, Julien Vezoli, Henry Kennedy, Ulises Pereira-Obilinovic
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引用次数: 0

摘要

功能模块化是如何在由典型局部电路结构的重复组成的多区域皮层中出现的?我们通过关注工作记忆(一种核心认知功能)的神经编码来研究这个问题。在这里,我们报道了一种被称为“空间分叉”的机制,并表明其显著特征是空间定位的“临界减慢”,导致在工作记忆过程中,神经元时间常数沿皮层层次呈倒V形分布。这一现象在基于连接体的小鼠和猴子皮层大规模模型中得到了证实,为评估工作记忆表示是否是模块化的提供了一个实验可测试的预测。空间中的许多分叉可以解释不同活动模式的出现,这些活动模式可能用于不同的认知功能。这项工作表明,由于大脑皮层神经生物学特性的宏观梯度,分布式心理表征与功能特异性相兼容,提出了理解大脑模块化组织的一般原则。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Bifurcation in space: Emergence of functional modularity in the neocortex.

Bifurcation in space: Emergence of functional modularity in the neocortex.

Bifurcation in space: Emergence of functional modularity in the neocortex.

Bifurcation in space: Emergence of functional modularity in the neocortex.

Recent studies have shown that neural representation and processing are widely distributed in the brains of behaving animals [1, 2, 3, 4]. These observations challenge functional specialization as a central tenet of Neuroscience, which refers to the notion that distinct brain regions are dedicated to specific aspects of cognition such as working memory or subjective decision-making. Here we develop the concept of bifurcation in space to mechanistically account for the emergence of functional specialization that is compatible with distributed neural coding in a large-scale neo-cortex. Our theory starts with a departure from the canonical local circuit principle [5] by highlighting differences between cortical areas in the form of experimentally quantified heterogeneities of synaptic excitation and inhibition. We investigated connectome-based modelling of a multiregional cortex for both macaque monkeys and mice, as well as a generative model of a spatially embedded neocortex. During working memory in a simulated delayed response task, surprisingly, we found an inverted-V-shaped pattern of neuronal timescales across the cortical hierarchy as a signature of functional modularity, in sharp contrast to an increasing pattern of timescales during the resting state, as reported previously [6]. Furthermore, our model cortex simultaneously and robustly displays a plethora of bifurcations in space and their associated rich repertoire of timescale profiles across a large-scale cortex; the corresponding functionally defined modules (spatial attractors) could potentially subserve various internal mental processes. This work yields several specific experimentally testable predictions, including an inverted-V pattern of timescales, a measure of comparison between functional modules and structural modules defined by the graph theory, and a new plot for revealing bifurcation in space in neural activity recorded from animals performing different tasks that engage various functional modules. We propose that bifurcation in space, resulting from the connectome and macroscopic gradients of neurobiological properties across the cortex, represents a fundamental principle for understanding the brain's functional specialization and modular organization.

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