从信号到音乐:一种自下而上的方法来研究神经元活动的结构
Gabriel D Noel1,2, Lionel E Mugno3, Daniela S Andres4,5
1College of Interdisciplinary and Advanced Studies in the Social Sciences, National University of San Martin (UNSAM), San Martín, Argentina.
Frontiers in systems neuroscience
|August 28, 2023
概括
神经科学研究表明,神经代码可能和音乐一样复杂. 分析老鼠大脑活动揭示了神经元信号和音乐组成之间的结构相似性,支持同源性假设.
科学领域:
- 神经科学是一个神经科学.
- 信息理论 信息理论
- 计算神经科学是一种神经科学.
- 音乐学 音乐学 音乐学
背景情况:
- 神经科学中寻找神经代码的研究在很大程度上依赖于隐喻,忽视了信息理论,语言学和语义学中的正式定义.
- 复杂的通信系统,如人类语言和音乐,表现出多层次,结构化的组织,这表明需要类似的分析方法在神经科学.
- 结构主义强调了应用语言方法来理解其他复杂系统的潜力.
研究的目的:
- 为了测试神经代码与音乐等人造代码一样复杂的假设.
- 提出并应用一个自下而上的方法,使用符号逻辑来将神经元信号转化为乐谱.
- 为了研究神经元活动和音乐之间的潜在结构同质性.
主要方法:
- 在警觉,蒙眼和无声条件下记录了来自大鼠globus pallidus pars interna的单细胞活动.
- 使用统计,光谱和复杂的方法分析神经元信号,包括快速里埃变换,赫斯特指数和复发图分析.
- 通过构建符号逻辑,将神经元信号转化为乐谱.
主要成果:
- 神经元活动表现出复杂的行为和碎形一致的复发图,赫斯特指数>0.5表明时间持久性.
- 这些特征与古典音乐中发现的特征相似,支持神经元活动和音乐之间结构相似性的假设.
- 从神经元数据中生成的乐谱是自发的音调,并显示了人类音乐作品的特征结构.
结论:
- 这项研究支持了神经代码和音乐代码之间结构同质性的假设.
- 语言学和语义学理论为分析超越隐喻解释的神经代码提供了宝贵的方法学资源.
- 神经元信号具有与复杂的人类象征系统相比较的固有结构复杂性.
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