Infant Sibling Project: Sample Files

These electroencephalography (EEG) data files were collected through the Infant Sibling Project (ISP), a prospective investigation examining infants at high versus low familial risk for autism spectrum disorder over the first 3 years of life. Here we provide a subset of the full dataset, as example files for the Batch EEG Automated Processing Pipeline (BEAPP), and the Harvard Automated Processing Pipeline for EEG (HAPPE). Both BEAPP and HAPPE may be downloaded at www.github.com. Baseline EEG data was collected while a young child sat in a parent’s lap watching a research assistant blow bubbles or show toys for several minutes.¹ 12 sample baseline EEGs are provided here, in .mat format. Auditory (event-related) EEG data was collected using an auditory double oddball paradigm, in which a stream of consonant-vowel stimuli was presented. Stimuli included a “Standard” /ɖa/ sound 80% of the time, “Native” /ta/ sound 10% of the time, and “Non-Native” /da/ sound 10% of the time.² 10 sample auditory EEGs are provided here, in .mff format. This sample dataset was chosen for demonstration of BEAPP and HAPPE for several reasons. First, the longitudinal nature of the study led to data collection with different sampling rates (250 Hz and 500 Hz) and acquisition setups (64-channel Geodesic Sensor Net v2.0, and 128-channel HydroCel Geodesic Sensor Net, both from Electrical Geodesics, Inc., Eugene, OR). Additionally, because young children cannot follow instructions to “rest” or remain still, EEG in these children typically contains greater amounts of artifact than EEG in typical adults. BEAPP and HAPPE are targeted towards addressing these challenges. The Infant Sibling Project was carried out in accordance with the recommendations of the Institutional Review Board at Boston University and Boston Children’s Hospital (#X06-08-0374), with written informed consent from all caregivers prior to their child’s participation in the study. All files here have been deidentified, including alteration of exact acquisition dates. Acquisition times have not been altered. For additional information about data collection paradigms, and sample studies published on the larger ISP data set, please see the following references: 1. Levin, A. R., Varcin, K. J., O’Leary, H. M., Tager-Flusberg, H., and Nelson, C. A. (2017). EEG power at 3 months in infants at high familial risk for autism. <em>J. Neurodev. Disord.</em> 9, 1–13. 2. Seery A, Tager-Flusberg H, Nelson CA. Event-related potentials to repeated speech in 9-month-old infants at risk for autism spectrum disorder. J. Neurodev. Disord. 2014;6:43.本数据集的脑电图（electroencephalography, EEG）数据采集自婴儿同胞研究项目（Infant Sibling Project, ISP）——一项前瞻性研究，旨在追踪生命最初3年中，自闭症谱系障碍家族性高风险与低风险婴儿的发展情况。本次我们提供完整数据集的子集，作为批量EEG自动化处理流程（Batch EEG Automated Processing Pipeline, BEAPP）与哈佛EEG自动化处理流程（Harvard Automated Processing Pipeline for EEG, HAPPE）的示例文件。上述两款流程均可从www.github.com下载获取。 基线脑电数据采集时，幼儿坐在家长腿上，观看研究助手吹泡泡或展示玩具，时长约数分钟¹。本次提供12份基线脑电示例数据，格式为.mat。 听觉（事件相关）脑电数据采用听觉双oddball范式采集，该范式呈现连续的辅音-元音刺激序列。刺激包含三类：80%为“标准”/ɖa/音、10%为“母语型”/ta/音、10%为“非母语型”/da/音²。本次提供10份听觉脑电示例数据，格式为.mff。 本示例数据集被选中用于展示BEAPP与HAPPE的使用，原因如下：其一，本研究为纵向设计，数据采集采用了不同的采样率（250 Hz与500 Hz）及采集设备（均来自俄勒冈州尤金市Electrical Geodesics, Inc.的64通道Geodesic Sensor Net v2.0与128通道HydroCel Geodesic Sensor Net）；其二，幼儿无法遵从“放松”或保持静止的指令，因此幼儿脑电通常比健康成人脑电包含更多的伪迹。BEAPP与HAPPE正是针对此类挑战设计开发的。 本婴儿同胞研究项目严格遵循波士顿大学与波士顿儿童医院伦理审查委员会（编号X06-08-0374）的相关规范开展，所有儿童参与研究前，其看护者均已签署书面知情同意书。本次提供的所有数据文件均已完成去标识化处理，包括修改精确的采集日期，但采集时间未作改动。 如需了解更多关于数据采集范式以及基于更大规模ISP数据集发表的相关研究详情，请参阅以下参考文献： 1. Levin A R, Varcin K J, O'Leary H M, Tager-Flusberg H, Nelson C A. 自闭症家族高风险婴儿3月龄时的脑电功率. *J. Neurodev. Disord.*, 2017, 9:1–13. 2. Seery A, Tager-Flusberg H, Nelson C A. 自闭症谱系障碍高风险9月龄婴儿对重复语音的事件相关电位. *J. Neurodev. Disord.*, 2014, 6:43.