Raw birdsong data for "Vocal changes in a zebra finch model of Parkinson’s Disease characterized by alpha-synuclein overexpression in the song-dedicated anterior forebrain pathway"

Parkinson's disease is the second most common neurodegenerative disease affecting motor behavior. In addition to the typical peripheral limb motor symptoms, vocal motor issues such as deteriorated vocal quality are present in Parkinson's patients. Unfortunately, very little is known about the biological mechanisms underlying these vocal changes. Here, we developed a Parkinsonian model using the zebra finch songbird to study the underlying neural mechanisms of these changes. Finch song and supportive brain areas are similar to human speech and brain pathways. To do this, we recorded song for 2 hours from zebra finches injected with an adeno-associated virus expressing either the causally-related human Parkinsonian gene SNCA or control GFP protein in finch brain. Song was then segmented using a specially designed matlab program called Vocal Inventory Clustering Engine (VoICE) into unique syllables. Acoustic features such as duration, pitch, mean frequency, amplitude, Wiener Entropy, frequency modulation, and amplitude modulation were measured from 75 individual copies of these syllables. The mean, mean variance, and coefficient of variation of these syllables were also measured. Motif-level data was also collected to monitor how much each bird sang (i.e., how many copies of song were uttered over a 2 hour period). We found that overexpression of SNCA led to shorter and poorer quality syllables that are similar to Parkinsonian vocal changes. To cite this work, please cite both the associated PLoS One paper "Vocal changes in a zebra finch model of Parkinson’s Disease characterized by alpha-synuclein overexpression in the song-dedicated anterior forebrain pathway" and this dataset. For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to [e-mail]

帕金森病（Parkinson's Disease）是影响运动行为的第二大常见神经退行性疾病。除典型的外周肢体运动症状外，帕金森患者还会出现发声运动障碍，如发声质量下降。遗憾的是，目前对这类发声改变背后的生物学机制尚所知甚少。本研究以斑胸草雀（zebra finch，鸣禽）为对象构建帕金森病模型，以探究此类发声改变的潜在神经机制。斑胸草雀的鸣唱及其相关脑区与人类言语及脑通路具有相似性。为此，我们向斑胸草雀脑内注射腺相关病毒（adeno-associated virus, AAV），分别携带与帕金森病致病相关的人类SNCA基因或对照绿色荧光蛋白（GFP）基因，并录制2小时的鸣唱音频。随后，使用自研的Matlab程序「发声库聚类引擎（Vocal Inventory Clustering Engine, VoICE）」将鸣唱音频分割为独特的音节单元。我们从75份独立的音节拷贝中提取声学特征，包括时长、基频、平均频率、振幅、维纳熵（Wiener Entropy）、频率调制及振幅调制。同时还计算了这些音节的均值、均值方差及变异系数。此外，我们还收集了鸣唱模式（motif）层面的数据，以监测每只斑胸草雀的鸣唱量（即2小时内发出的鸣唱拷贝数）。研究发现，SNCA基因过表达会导致音节时长缩短、质量下降，这与帕金森患者的发声改变特征一致。如需引用本研究，请同时引用关联的《PLOS ONE》论文《基于鸣唱特异性前脑通路α-突触核蛋白过表达的帕金森病斑胸草雀模型的发声改变》及本数据集。若对数据集内容有疑问，请联系README.txt文件中列出的通讯作者。行政类咨询（如移除请求、下载故障等）请发送邮件至[e-mail]