Contribution of low-level image statistics to EEG decoding of semantic content in multivariate and u...
Contribution of low-level image statistics to EEG decoding of semantic content in multivariate and univariate models with feature optimization
About this item
Full title
Author / Creator
Publisher
United States: Elsevier Inc
Journal title
Language
English
Formats
Publication information
Publisher
United States: Elsevier Inc
Subjects
More information
Scope and Contents
Contents
•Optimized univariate models outperform multivariate models in EEG visual decoding.•Model performance is confounded by low-level image features.•Model optimization can increase the sensitivity of model towards this confound.•Low-level image feature confounds also appear when decoding of concept categories.
Spatio-temporal patterns of evoked brai...
Alternative Titles
Full title
Contribution of low-level image statistics to EEG decoding of semantic content in multivariate and univariate models with feature optimization
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_5b33981640954aab8edd93a533e43432
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_5b33981640954aab8edd93a533e43432
Other Identifiers
ISSN
1053-8119
E-ISSN
1095-9572
DOI
10.1016/j.neuroimage.2024.120626
