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Hierarchical dynamics of informational patterns and decision-making

机译:信息模式和决策的层次动态

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摘要

Traditional studies on the interaction of cognitive functions in healthy and disordered brains have used the analyses of the connectivity of several specialized brain networks—the functional connectome. However, emerging evidence suggests that both brain networks and functional spontaneous brain-wide network communication are intrinsically dynamic. In the light of studies investigating the cooperation between different cognitive functions, we consider here the dynamics of hierarchical networks in cognitive space. We show, using an example of behavioural decision-making based on sequential episodic memory, how the description of metastable pattern dynamics underlying basic cognitive processes helps to understand and predict complex processes like sequential episodic memory recall and competition among decision strategies. The mathematical images of the discussed phenomena in the phase space of the corresponding cognitive model are hierarchical heteroclinic networks. One of the most important features of such networks is the robustness of their dynamics. Different kinds of instabilities of these dynamics can be related to ‘dynamical signatures’ of creativity and different psychiatric disorders. The suggested approach can also be useful for the understanding of the dynamical processes that are the basis of consciousness.
机译:关于健康和混乱的大脑中认知功能相互作用的传统研究使用了对几种专用大脑网络(功能连接体)的连接性的分析。但是,越来越多的证据表明,脑部网络和功能性自发性全脑网络通信本质上都是动态的。根据研究不同认知功能之间协作的研究,我们在此考虑认知空间中分层网络的动力学。我们使用一个基于顺序情节记忆的行为决策示例,说明基本认知过程基础上的亚稳态模式动力学的描述如何帮助理解和预测复杂过程,例如顺序情节记忆回忆和决策策略之间的竞争。在相应的认知模型的相空间中讨论的现象的数学图像是层次异质网络。这种网络的最重要特征之一是其动态性的鲁棒性。这些动力学的不同类型的不稳定性可能与创造力和不同精神病的“动力学特征”有关。建议的方法对于理解作为意识基础的动力过程也可能有用。

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