Object Category EEG Dataset.
- Kaneshiro, Blair
- Arnardóttir, Steinunn
- Primary advisor:
- Norcia, Anthony M.
- Principal investigator:
- Suppes, Patrick
- Date created:
- Type of resource:
- Software, multimedia
- This dataset contains scalp-recorded EEG responses from ten human participants viewing a set of photographs of objects with a planned category structure. EEG was recorded using the Electrical Geodesics, Inc. (EGI) GES 300 platform. Each participant viewed each of the 72 images in the stimulus set 72 times, for a total of 5,184 experimental trials per participant. Data files are split into six recordings per participant, each comprising 864 trials, 12 of each stimulus. In addition to the 60 primary recordings analyzed in the Kaneshiro et al. (2015) PLoS ONE paper, the dataset also includes 12 additional EEG recordings from three of the study participants. Data are published in Matlab (.mat) format. Each data file is around 1GB in size.
- Preferred Citation:
- Blair Kaneshiro, Steinunn Arnardóttir, Anthony M. Norcia, and Patrick Suppes (2015). Object Category EEG Dataset. Stanford Digital Repository. Available at: http://purl.stanford.edu/tc919dd5388
- Related Publication:
- Blair Kaneshiro, Marcos Perreau Guimaraes, Hyung-Suk Kim, Anthony M. Norcia, and Patrick Suppes (2015). A Representational Similarity Analysis of the Dynamics of Object Processing Using Single-Trial EEG Classification. PLoS ONE 10(8): e0135697. doi:10.1371/journal.pone.0135697
Blair Kaneshiro, Marcos Perreau Guimaraes, Hyung-Suk Kim, Anthony M. Norcia, and Patrick Suppes (2015). EEG data analyzed in "A Representational Similarity Analysis of the Dynamics of Object Processing Using Single-Trial EEG Classification". Stanford Digital Repository. Available at: http://purl.stanford.edu/bq914sc3730
- Stanford Research Data
- Electroencephalography (EEG)
Center for the Study of Language and Information
Stanford Vision and Neuro-Development Lab
Stanford Department of Psychology
- Use and reproduction:
- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.