EEG-MEG
dc.contributor.advisor | Simon, Jonathan | |
dc.contributor.advisor | Anderson, Samira | |
dc.contributor.author | Presacco, Alessandro | |
dc.contributor.author | Simon, Jonathan | |
dc.contributor.author | Anderson, Samira | |
dc.date.accessioned | 2018-09-10T19:27:10Z | |
dc.date.available | 2018-09-10T19:27:10Z | |
dc.date.issued | 2018 | |
dc.description.abstract | Data collected from normal hearing younger adults (18-30) and from normal hearing and hearing impaired older adults (>= 60) to study age-related deficits in the representation of speech in noise. EEG data were collected with Biosemi system by using the ABR module from one electrode placed in Cz and reference with respect to the left and right ear lobes. The data uploaded are the raw ones in bdf format. BDF files can be opened by using matlab scripts that can be found in toolboxes such as EEGLab or that can be found directly from Biosemi's website. Each mat file contains information about sampling frequency, channels, triggers, etc. Each participants was tested in 9 conditions: Quiet, +3 dB, 0 dB, -3 dB and -6 dB with English (H) and Dutch (L) speakers used as background noise. Files were named based on the SNR and background speaker used. For instance, S01_M3_H, means Subject 01, SNR = -3 dB and English speaker in the background, while S01_P3_L, means Subject 01, SNR = +3 dB and Dutch speaker in the background. The "Q" denomination is used for the condition in quiet. Subjects id# from 1 to 17 are younger adults, subjects with id# from 21 to 35 are normal hearing older adults and subjects named S01_HL.....S17_HL are older adults with hearing loss. MEG data were collected from 157 sensors. Each mat file contains information about the data, such as sampling frequency. A 3D matrix is used to store the 3 repetitions recorded from each conditions. Each participants was tested in 10 conditions: Quiet, +3 dB, 0 dB, -3 dB and -6 dB with English (H) and Dutch (L) speakers used as background noise. Two conditions in quiet were played. Files were named based on the SNR and background speaker used, in the same way as for the EEG data. Auditory stimuli were also uploaded. The stimuli have been pre-processed as described in our publications "Evidence of degraded representation of speech in noise, in the aging midbrain and cortex" and "Effect of informational content of noise on speech representation in the aging midbrain and cortex". The envelope needs to be extracted. | en_US |
dc.description.sponsorship | University of Maryland College Park (UMCP) Department of Hearing and Speech Sciences, UMCP ADVANCE Program for Inclusive Excellence (NSF HRD1008117), and National Institute on Deafness and Other Communication Disorders (Grants R01DC008342;, R01DC014085;, and T32DC-00046). | en_US |
dc.description.uri | https://doi.org/10.1152/jn.00372.2016 | |
dc.description.uri | https://doi.org/10.1152/jn.00373.2016 | |
dc.identifier | https://doi.org/10.13016/M2599Z52H | |
dc.identifier.citation | EEG_MEG | en_US |
dc.identifier.uri | http://hdl.handle.net/1903/21184 | |
dc.language.iso | en_US | en_US |
dc.relation.isAvailableAt | Institute for Systems Research | en_us |
dc.relation.isAvailableAt | Digital Repository at the University of Maryland | en_us |
dc.relation.isAvailableAt | University of Maryland (College Park, MD) | en_us |
dc.subject | EEG, MEG, Aging, Hearing loss, Midbrain, Cortex | en_US |
dc.title | EEG-MEG | en_US |
dc.type | Dataset | en_US |
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