Dataset Open Access

Infant Sibling Project: Sample Files

Levin, April Robyn; Gabard-Durnam, Laurel Joy; Mendez Leal, Adriana Sofia; O'Leary, Heather Marie; Wilkinson, Carol Lee; Tager-Flusberg, Helen; Nelson, Charles Alexander

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. J. Neurodev. Disord. 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.

Acquisition information: baselineEEG01.mat: Sampling rate 250, Net type HydroCel GSN 128 1.0 baselineEEG02.mat: Sampling rate 250, Net type Geodesic Sensor Net 64 2.0 baselineEEG03.mat: Sampling rate 250, Net type Geodesic Sensor Net 64 2.0 baselineEEG04.mat: Sampling rate 250, Net type HydroCel GSN 128 1.0 baselineEEG05.mat: Sampling rate 250, Net type HydroCel GSN 128 1.0 baselineEEG06.mat: Sampling rate 250, Net type HydroCel GSN 128 1.0 baselineEEG07.mat: Sampling rate 250, Net type HydroCel GSN 128 1.0 baselineEEG08.mat: Sampling rate 500, Net type HydroCel GSN 128 1.0 baselineEEG09.mat: Sampling rate 500, Net type HydroCel GSN 128 1.0 baselineEEG10.mat: Sampling rate 500, Net type HydroCel GSN 128 1.0 baselineEEG11.mat: Sampling rate 250, Net type HydroCel GSN 128 1.0 baselineEEG12.mat: Sampling rate 250, Net type HydroCel GSN 128 1.0 Note that for several of the event-tagged files, an offset was introduced by the EEG acquisition equipment. Therefore, the event tag in the file occurs prior to when the participant was exposed to the stimulus. Offsets are detailed below for each file. auditoryEEG01.mff: Sampling rate 250, Net type HydroCel GSN 128 1.0, Offset 0 msec auditoryEEG02.mff: Sampling rate 250, Net type Geodesic Sensor Net 64 2.0, Offset 0 msec auditoryEEG03.mff: Sampling rate 250, Net type Geodesic Sensor Net 64 2.0, Offset 0 msec auditoryEEG04.mff: Sampling rate 250, Net type HydroCel GSN 128 1.0, Offset 0 msec auditoryEEG05.mff: Sampling rate 250, Net type HydroCel GSN 128 1.0, Offset 0 msec auditoryEEG06.mff: Sampling rate 250, Net type HydroCel GSN 128 1.0, Offset 0 msec auditoryEEG07.mff: Sampling rate 250, Net type HydroCel GSN 128 1.0, Offset 8 msec auditoryEEG08.mff: Sampling rate 500, Net type HydroCel GSN 128 1.0, Offset 18 msec auditoryEEG09.mff: Sampling rate 500, Net type HydroCel GSN 128 1.0, Offset 18 msec auditoryEEG10.mff: Sampling rate 500, Net type HydroCel GSN 128 1.0, Offset 18 msec
Files (2.0 GB)
Name Size
auditoryEEG01.mff.zip
md5:256cc672e80f746ae5e7abf9170b801e
86.9 MB Download
auditoryEEG02.mff.zip
md5:23f5ae833122e1d03e12bace362942a9
48.5 MB Download
auditoryEEG03.mff.zip
md5:fceafc443fd313944b03abe66359467a
18.0 MB Download
auditoryEEG04.mff.zip
md5:b6c5724a532e208702a8ab0aab0476d4
57.4 MB Download
auditoryEEG05.mff.zip
md5:6856edaf6b9321b203da2e61f0e522f8
36.9 MB Download
auditoryEEG06.mff.zip
md5:99da9d071a44947646aa10965de80df2
94.1 MB Download
auditoryEEG07.mff.zip
md5:32e6999125595dcbf146dc1b3a7d0d4e
90.3 MB Download
auditoryEEG08.mff.zip
md5:86922b5eff7a7bdb88a91112902d7ee5
228.3 MB Download
auditoryEEG09.mff.zip
md5:247ab83134a9032f245ce3391c2146bc
188.5 MB Download
auditoryEEG10.mff.zip
md5:964f64773301b7611d669c6e722e29c9
162.0 MB Download
baselineEEG01.mat
md5:c1ce4ce1d1948c249d93aab22fa604a8
51.9 MB Download
baselineEEG02.mat
md5:7f165764f129b2d0821887ff4897da3d
9.7 MB Download
baselineEEG03.mat
md5:57f86bb999b725eb7c526de8d9b19279
5.9 MB Download
baselineEEG04.mat
md5:06b08c244f1aee734881a6b0056a4d82
48.8 MB Download
baselineEEG05.mat
md5:806b14a754f1d3c5b0ed5a819f5320ff
42.3 MB Download
baselineEEG06.mat
md5:dd524899bb8ac9be1f9810e1320f1889
202.3 MB Download
baselineEEG07.mat
md5:6d965e02368b4ce67924d7da8fe32d00
37.4 MB Download
baselineEEG08.mat
md5:dff294b88000ead8767216e649f44644
144.0 MB Download
baselineEEG09.mat
md5:b3f3d1e5f502ab2b55869d8d7f9fcdb8
83.1 MB Download
baselineEEG10.mat
md5:0b4557c51a72031465c367d0f2966313
194.0 MB Download
baselineEEG11.mat
md5:d2009d3483f12a2906d7c8f48a3942d8
47.5 MB Download
baselineEEG12.mat
md5:0f0d54ff95d48cd964c557ee34435d65
73.3 MB Download
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