In this work, we propose a natural model for information flow in the brain through a neural message-passing dynamics on a structural network of macroscopic regions, such as the human connectome (HC). In our model, each brain region is assumed to have a binary behavior (active or not), the strengths of interactions among them are encoded in the anatomical connectivity matrix defined by the HC, and the dynamics of the system is defined by the Belief Propagation (BP) algorithm, working near the critical point of the network. We show that in the absence of direct external stimuli the BP algorithm converges to a spatial map of activations that is similar to the Default Mode Network (DMN) of the brain, which has been defined from the analysis of functional MRI data. Moreover, we use Susceptibility Propagation (SP) to compute the matrix of long-range correlations between the different regions and show that the modules defined by a clustering of this matrix resemble several Resting State Networks (RSN) determined experimentally. Both results suggest that the functional DMN and RSNs can be seen as simple consequences of the anatomical structure of the brain and a neural message-passing dynamics between macroscopic regions. With the new model, we explore predictions on how functional maps change when the anatomical brain network suffers structural alterations, like in Alzheimer's disease and in lesions of the Corpus Callosum. The implications and novel interpretations suggested by the model, as well as the role of criticality, are discussed.

中文翻译：

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通过在人类连接体上传递的神经信息对功能性静止状态大脑网络进行建模。

在这项工作中，我们提出了一个自然的模型，用于通过宏观区域（例如人类连接体（HC））的结构网络上的神经传递消息来在大脑中传递信息。在我们的模型中，假定每个大脑区域都具有二元行为（活动的或不活动的），它们之间的相互作用强度在HC定义的解剖学连通性矩阵中进行编码，而系统的动力学则在Belief Propagation中定义（BP）算法，在网络的关键点附近工作。我们表明，在没有直接外部刺激的情况下，BP算法收敛到类似于大脑的默认模式网络（DMN）的激活的空间图，这是通过对功能性MRI数据进行分析而定义的。而且，我们使用敏感性传播（SP）来计算不同区域之间的远程相关性矩阵，并表明由该矩阵的聚类定义的模块类似于实验确定的几个静止状态网络（RSN）。两项结果均表明，功能性DMN和RSN可以看作是大脑解剖结构和宏观区域之间的神经信息传递动力学的简单结果。使用新模型，我们探索了在解剖性大脑网络遭受结构改变（例如在阿尔茨海默氏病和Call体病变中）时功能图如何变化的预测。讨论了模型所暗示的含义和新颖的解释，以及临界的作用。