算法代理视角与计算神经精神病学:从病因学到重度抑郁症的高级疗法》。

IF 2.1 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY
Entropy Pub Date : 2024-11-06 DOI:10.3390/e26110953
Giulio Ruffini, Francesca Castaldo, Edmundo Lopez-Sola, Roser Sanchez-Todo, Jakub Vohryzek
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引用次数: 0

摘要

重度抑郁症(MDD)是一种复杂的异质性疾病,影响着全球数百万人。通过对这种疾病进行机理建模,计算神经精神病学有望取得突破性进展。我们利用柯尔莫哥洛夫意识理论(KT)建立了一个基础模型,在这个模型中,算法代理与世界相互作用,以最大化评估情感价位的目标函数。抑郁症的定义是情绪持续低落的状态,可能由多种因素引起,包括不准确的世界模型(认知偏差)、失调的目标函数(失乐症、焦虑)、计划缺陷(执行缺陷)或不利的环境。结合算法、动力系统和神经生物学概念,我们将代理模型映射到大脑回路和功能网络,勾勒出潜在的病因路径,并将其与抑郁症的生物类型联系起来。最后,我们将探讨脑刺激、心理治疗和可塑性增强化合物(如迷幻药)如何协同修复神经回路,并利用个性化计算模型优化疗法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Algorithmic Agent Perspective and Computational Neuropsychiatry: From Etiology to Advanced Therapy in Major Depressive Disorder.

Major Depressive Disorder (MDD) is a complex, heterogeneous condition affecting millions worldwide. Computational neuropsychiatry offers potential breakthroughs through the mechanistic modeling of this disorder. Using the Kolmogorov theory (KT) of consciousness, we developed a foundational model where algorithmic agents interact with the world to maximize an Objective Function evaluating affective valence. Depression, defined in this context by a state of persistently low valence, may arise from various factors-including inaccurate world models (cognitive biases), a dysfunctional Objective Function (anhedonia, anxiety), deficient planning (executive deficits), or unfavorable environments. Integrating algorithmic, dynamical systems, and neurobiological concepts, we map the agent model to brain circuits and functional networks, framing potential etiological routes and linking with depression biotypes. Finally, we explore how brain stimulation, psychotherapy, and plasticity-enhancing compounds such as psychedelics can synergistically repair neural circuits and optimize therapies using personalized computational models.

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来源期刊
Entropy
Entropy PHYSICS, MULTIDISCIPLINARY-
CiteScore
4.90
自引率
11.10%
发文量
1580
审稿时长
21.05 days
期刊介绍: Entropy (ISSN 1099-4300), an international and interdisciplinary journal of entropy and information studies, publishes reviews, regular research papers and short notes. Our aim is to encourage scientists to publish as much as possible their theoretical and experimental details. There is no restriction on the length of the papers. If there are computation and the experiment, the details must be provided so that the results can be reproduced.
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