表观遗传学在焦虑症中作用的高阶自适应动力学系统建模

IF 2.1 3区 心理学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Shivant Kathusing, Natalie Samhan, Jan Treur
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引用次数: 0

摘要

在本文中,引入了一个五阶自适应自建模网络模型来描述表观遗传学参与焦虑症的发展及其通过一种可能的基于表观遗传学的治疗方法的调节。模型中使用了多个自适应阶数来描述发展过程,其中任何自适应阶数中的较高阶数适应较低阶数中路径的特征,并作为一种控制形式。根据自建模网络建模原理,将这些自适应阶及其层间相互作用建模为一个高阶自适应动力系统。该模型的灵感来源于相关的人类生物和神经过程的结构。除了对焦虑症的发展进行建模外,本文还提出了基于表观遗传学的治疗方法,并对其进行了计算分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Higher-order adaptive dynamical system modeling of the role of epigenetics in anxiety disorders

In this paper, a fifth-order adaptive self-modelling network model is introduced to describe epigenetic involvement in the development of anxiety disorders and its regulation by a possible epigenetics-based therapeutic method. Multiple orders of adaptivity are used in the model to depict the development process, where a higher pathway of any order of adaptivity adapts characteristics of pathways in lower orders and acts as a form of control. These orders of adaptivity and their interlevel interaction were modelled as a higher-order adaptive dynamical system according to the self-modelling network modelling principle. The model was inspired by the structure of the relevant human biological and neurological processes. In addition to modelling the development of an anxiety disorder, also the possibility of an epigenetics-based therapy is suggested and computationally analyzed in this paper.

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来源期刊
Cognitive Systems Research
Cognitive Systems Research 工程技术-计算机:人工智能
CiteScore
9.40
自引率
5.10%
发文量
40
审稿时长
>12 weeks
期刊介绍: Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial. The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition. Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.
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