大脑复杂性和精神疾病
Ronald Miguel Hernández1, Jacqueline Cynthia Ponce-Meza2, Miguel Ángel Saavedra-López3
1Universidad Privada Norbert Wiener, Lima, Perú.
Iranian journal of psychiatry
|October 26, 2023
概括
神经生理学信号显示精神疾病的复杂性改变. 一些疾病,如痴呆症和自闭症,表现出较低的大脑复杂性,而其他疾病,如ADHD和情绪障碍,表现出更高的复杂性,为神经机制提供了新的见解.
科学领域:
- 神经科学是一个神经科学.
- 精神病学是一个精神病学.
- 复杂性科学 复杂性科学
背景情况:
- 非线性技术越来越多地用于分析神经生理信号 (fMRI,MEG,EEG).
- 了解神经复杂性对于描述神经机制复杂的动态方面至关重要.
研究的目的:
- 为非专家解释估计神经复杂性的算法.
- 审查精神疾病中的大脑复杂性分析结果及其临床影响.
主要方法:
- 对神经生理信号复杂性的研究进行了全面的文献搜索.
- 搜索的数据库包括PubMed和谷歌学者.
- 分析了来自EEG,MEG,fMRI和fNIRS的信号.
主要成果:
- 常见的复杂度指标包括,碎形维度和利亚普诺夫指数.
- 痴呆症,自闭症和成人ADHD显示神经生理信号复杂性降低.
- 儿童的ADHD,早期精神分裂症和情绪障碍的复杂性增加.
- 由于技术和异质性问题,对一些疾病存在矛盾的发现.
结论:
- 复杂性分析为理解精神疾病提供了一个新的维度.
- 复杂性科学可以为理解精神疾病的系统动态做出重大贡献.
- 复杂性分析的实际临床应用仍在开发中.
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