Data and analyses for "Spontaneous Decoding of the Timing and Content of Human Object Perception from Cortical Surface Recordings Reveals Complementary Information in the Event-Related Potential and Broadband Spectral Change"
Abstract/Contents
- Abstract
- This data is from implanted electrodes in human epileptic patients who performed a basic face- and house- image viewing task. The .zip file contains MATLAB-based analysis scripts and data files. A manuscript appearing in PLoS computational biology in 2016 titled: "Spontaneous Decoding of the Timing and Content of Human Object Perception from Cortical Surface Recordings Reveals Complementary Information in the Event-Related Potential and Broadband Spectral Change”, by Kai J Miller and colleagues details some findings with these data, and describes the experiments, recordings and analyses (doi:10.1371/journal. pcbi.1004660). Please read this manuscript, as well as the file 'README_faceshouses_dataset_notes.pdf' in the unzipped folder. The abstract of the manuscript is: "The link between object perception and neural activity in visual cortical areas is a problem of fundamental importance in neuroscience. Here we show that electrical potentials from the ventral temporal cortical surface in humans contain sufficient information for spontaneous and near-instantaneous identification of a subject’s perceptual state. Electrocorticographic (ECoG) arrays were placed on the subtemporal cortical surface of seven epilepsy patients. Grayscale images of faces and houses were displayed rapidly in random sequence. We developed a template projection approach to decode the continuous ECoG data stream spontaneously, predicting the occurrence, timing and type of visual stimulus. In this setting, we evaluated the independent and joint use of two well-studied features of brain signals, broadband changes in the frequency power spectrum of the potential and deflections in the raw potential trace (event-related potential; ERP). Our ability to predict both the timing of stimulus onset and the type of image was best when we used a combination of both the broadband response and ERP, suggesting that they capture different and complementary aspects of the subject’s perceptual state. Specifically, we were able to predict the timing and type of 96% of all stimuli, with less than 5% false positive rate and a ~20ms error in timing. "
Description
| Type of resource | software, multimedia |
|---|---|
| Date created | [ca. 2005 - 2015] |
Creators/Contributors
| Principal investigator | Miller, Kai J |
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| Principal investigator | Ojemann, Jeffrey G |
Subjects
| Subject | human vision |
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| Subject | electrocorticography |
| Subject | broadband power |
| Subject | event-related potential |
| Subject | fusiform cortex |
| Genre | Dataset |
Bibliographic information
| Related Publication | Miller KJ, Schalk G, Hermes D, Ojemann JG, Rao RPN (2016) Spontaneous Decoding of the Timing and Content of Human Object Perception from Cortical Surface Recordings Reveals Complementary Information in the Event-Related Potential and Broadband Spectral Change. PLoS Comput Biol 12(1): e1004660. http://dx.doi.org/10.1371/journal.pcbi.1004660 |
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| Location | https://purl.stanford.edu/xd109qh3109 |
Access conditions
- 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.
Preferred citation
- Preferred Citation
- Miller, Kai J and Ojemann, Jeffrey G. (2015). Data and analyses for "Spontaneous Decoding of the Timing and Content of Human Object Perception from Cortical Surface Recordings Reveals Complementary Information in the Event-Related Potential and Broadband Spectral Change". Stanford Digital Repository. Available at: http://purl.stanford.edu/xd109qh3109
Collection
Stanford Research Data
View other items in this collection in SearchWorksContact information
- Contact
- kai.miller@stanford.edu
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