DOI: 10.17045/sthlmuni.12582002
title: Open data: Visual load effects on the auditory steady-state responses to 20-, 40-, and 80-Hz amplitude-modulated tones

description: The main results file are saved separately:<br><br>- ASSR2.html: R output of the main analyses (N = 33)<br>- ASSR2_subset.html: R output of the main analyses for the smaller sample (N = 25)<br><br>FIGSHARE METADATA<br><br>Categories<br><br><br>- Biological psychology<br>- Neuroscience and physiological psychology<br>- Sensory processes, perception, and performance<br><br><br>Keywords<br><br><br>- crossmodal attention<br>- electroencephalography (EEG)<br>- early-filter theory<br>- task difficulty<br>- envelope following response<br><br><br>References<br><br><br>- https://doi.org/10.17605/OSF.IO/6FHR8<br>- https://github.com/stamnosslin/mn<br>- https://doi.org/10.17045/sthlmuni.4981154.v3<br>- https://biosemi.com/<br>- https://www.python.org/<br>- https://mne.tools/stable/index.html#- https://www.r-project.org/- https://rstudio.com/products/rstudio/<br><br><br>GENERAL INFORMATION<br><br><br>1. Title of Dataset:<br>Open data: Visual load effects on the auditory steady-state responses to 20-, 40-, and 80-Hz amplitude-modulated tones<br><br><br>2. Author Information<br> A. Principal Investigator Contact Information<br> Name: Stefan Wiens<br> Institution: Department of Psychology, Stockholm University, Sweden<br> Internet: https://www.su.se/profiles/swiens-1.184142<br> Email: sws@psychology.su.se<br><br><br> B. Associate or Co-investigator Contact Information<br> Name: Malina Szychowska<br> Institution: Department of Psychology, Stockholm University, Sweden<br> Internet: https://www.researchgate.net/profile/Malina_Szychowska<br> Email: malina.szychowska@psychology.su.se<br><br><br>3. Date of data collection: <br>Subjects (N = 33) were tested between 2019-11-15 and 2020-03-12.<br><br><br>4. Geographic location of data collection: Department of Psychology, Stockholm, Sweden<br><br><br>5. Information about funding sources that supported the collection of the data:<br>Swedish Research Council (Vetenskapsrådet) 2015-01181<br><br><br>SHARING/ACCESS INFORMATION<br><br><br>1. Licenses/restrictions placed on the data: CC BY 4.0<br><br><br>2. Links to publications that cite or use the data: Szychowska M., & Wiens S. (2020). Visual load effects on the auditory steady-state responses to 20-, 40-, and 80-Hz amplitude-modulated tones. Submitted manuscript.<br><br><br>The study was preregistered:<br>https://doi.org/10.17605/OSF.IO/6FHR8<br><br><br>3. Links to other publicly accessible locations of the data: N/A<br><br><br>4. Links/relationships to ancillary data sets: N/A<br><br><br>5. Was data derived from another source? No<br> <br>6. Recommended citation for this dataset: Wiens, S., & Szychowska M. (2020). Open data: Visual load effects on the auditory steady-state responses to 20-, 40-, and 80-Hz amplitude-modulated tones. Stockholm: Stockholm University. https://doi.org/10.17045/sthlmuni.12582002<br><br><br><br><br>DATA & FILE OVERVIEW<br><br><br>File List:<br>The files contain the raw data, scripts, and results of main and supplementary analyses of an electroencephalography (EEG) study. Links to the hardware and software are provided under methodological information.<br><br><br>ASSR2_experiment_scripts.zip: contains the Python files to run the experiment. <br><br><br>ASSR2_rawdata.zip: contains raw datafiles for each subject<br><br><br>- data_EEG: EEG data in bdf format (generated by Biosemi)<br>- data_log: logfiles of the EEG session (generated by Python)<br><br><br>ASSR2_EEG_scripts.zip: Python-MNE scripts to process the EEG data<br><br><br>ASSR2_EEG_preprocessed_data.zip: EEG data in fif format after preprocessing with Python-MNE scripts<br><br><br>ASSR2_R_scripts.zip: R scripts to analyze the data together with the main datafiles. The main files in the folder are: <br><br><br>- ASSR2.html: R output of the main analyses<br>- ASSR2_subset.html: R output of the main analyses but after excluding eight subjects who were recorded as pilots before preregistering the study<br><br><br>ASSR2_results.zip: contains all figures and tables that are created by Python-MNE and R.<br><br><br><br><br>METHODOLOGICAL INFORMATION<br><br><br>1. Description of methods used for collection/generation of data:<br>The auditory stimuli were amplitude-modulated tones with a carrier frequency (fc) of 500 Hz and modulation frequencies (fm) of 20.48 Hz, 40.96 Hz, or 81.92 Hz. <br>The experiment was programmed in python: https://www.python.org/ and used extra functions from here: https://github.com/stamnosslin/mn<br><br><br>The EEG data were recorded with an Active Two BioSemi system (BioSemi, Amsterdam, Netherlands; www.biosemi.com) and saved in .bdf format.<br>For more information, see linked publication.<br><br><br>2. Methods for processing the data:<br>We conducted frequency analyses and computed event-related potentials. See linked publication<br><br><br>3. Instrument- or software-specific information needed to interpret the data:<br>MNE-Python (Gramfort A., et al., 2013): https://mne.tools/stable/index.html#<br>Rstudio used with R (R Core Team, 2020): https://rstudio.com/products/rstudio/<br>Wiens, S. (2017). Aladins Bayes Factor in R (Version 3). https://www.doi.org/10.17045/sthlmuni.4981154.v3<br><br><br>4. Standards and calibration information, if appropriate:<br>For information, see linked publication.<br><br><br>5. Environmental/experimental conditions:<br>For information, see linked publication.<br><br><br>6. Describe any quality-assurance procedures performed on the data:<br>For information, see linked publication.<br><br><br>7. People involved with sample collection, processing, analysis and/or submission:<br><br><br>- Data collection: Malina Szychowska with assistance from Jenny Arctaedius.<br>- Data processing, analysis, and submission: Malina Szychowska and Stefan Wiens<br><br><br>DATA-SPECIFIC INFORMATION:<br>All relevant information can be found in the MNE-Python and R scripts (in EEG_scripts and analysis_scripts folders) that process the raw data. For example, we added notes to explain what different variables mean.