Journal
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Volume 44, Issue 12, Pages 9217-9220Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TPAMI.2021.3121268
Keywords
Object classification; EEG; human vision; neuroscience; neuroimaging; brain-computer interface
Funding
- U.S. National Science Foundation [1522954-IIS, 1734938-IIS]
- Intelligence Advanced Research Projects Activity (IARPA) via Department of Interior/Interior Business Center (DOI/IBC) [D17PC00341]
- National Institutes of Health [R01DC015989]
- Siemens Corporation, Corporate Technology
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Neuroimaging experiments, especially EEG experiments, need to be cautious of avoiding confounds. A recent TPAMI paper utilizes data that has been reported to have a serious confound issue before. It is demonstrated that their new model and analysis methods do not solve this confound issue, resulting in their claims of high accuracy and neuroscience relevance being invalid.
Neuroimaging experiments in general, and EEG experiments in particular, must take care to avoid confounds. A recent TPAMI paper uses data that suffers from a serious previously reported confound. We demonstrate that their new model and analysis methods do not remedy this confound, and therefore that their claims of high accuracy and neuroscience relevance are invalid.
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