Decoding visual colour from scalp electroencephalography measurements
Recent advances have made it possible to decode various aspects of visually presented stimuli from patterns of scalp EEG measurements. As of recently, such multivariate methods have been commonly used to decode visual-spatial features such as location, orientation, or spatial frequency. In the curre...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
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Elsevier
2021
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| _version_ | 1797070757204852736 |
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| author | Hajonides, J Nobre, AC Van Ede, F Stokes, M |
| author_facet | Hajonides, J Nobre, AC Van Ede, F Stokes, M |
| author_sort | Hajonides, J |
| collection | OXFORD |
| description | Recent advances have made it possible to decode various aspects of visually presented stimuli from patterns of scalp EEG measurements. As of recently, such multivariate methods have been commonly used to decode visual-spatial features such as location, orientation, or spatial frequency. In the current study, we show that it is also possible to track visual colour processing by using Linear Discriminant Analysis on patterns of EEG activity. Building on other recent demonstrations, we show that colour decoding: (1) reflects sensory qualities (as opposed to, for example, verbal labelling) with a prominent contribution from posterior electrodes contralateral to the stimulus, (2) conforms to a parametric coding space, (3) is possible in multi-item displays, and (4) is comparable in magnitude to the decoding of visual stimulus orientation. Through subsampling our data, we also provide an estimate of the approximate number of trials and participants required for robust decoding. Finally, we show that while colour decoding can be sensitive to subtle differences in luminance, our colour decoding results are primarily driven by measured colour differences between stimuli. Colour decoding opens a relevant new dimension in which to track visual processing using scalp EEG measurements, while bypassing potential confounds associated with decoding approaches that focus on spatial features. |
| first_indexed | 2024-03-06T22:43:30Z |
| format | Journal article |
| id | oxford-uuid:5c61b6d9-e6e7-4a1f-beae-9dbe07ee8e52 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T22:43:30Z |
| publishDate | 2021 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:5c61b6d9-e6e7-4a1f-beae-9dbe07ee8e522022-03-26T17:27:55ZDecoding visual colour from scalp electroencephalography measurementsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:5c61b6d9-e6e7-4a1f-beae-9dbe07ee8e52EnglishSymplectic ElementsElsevier2021Hajonides, JNobre, ACVan Ede, FStokes, MRecent advances have made it possible to decode various aspects of visually presented stimuli from patterns of scalp EEG measurements. As of recently, such multivariate methods have been commonly used to decode visual-spatial features such as location, orientation, or spatial frequency. In the current study, we show that it is also possible to track visual colour processing by using Linear Discriminant Analysis on patterns of EEG activity. Building on other recent demonstrations, we show that colour decoding: (1) reflects sensory qualities (as opposed to, for example, verbal labelling) with a prominent contribution from posterior electrodes contralateral to the stimulus, (2) conforms to a parametric coding space, (3) is possible in multi-item displays, and (4) is comparable in magnitude to the decoding of visual stimulus orientation. Through subsampling our data, we also provide an estimate of the approximate number of trials and participants required for robust decoding. Finally, we show that while colour decoding can be sensitive to subtle differences in luminance, our colour decoding results are primarily driven by measured colour differences between stimuli. Colour decoding opens a relevant new dimension in which to track visual processing using scalp EEG measurements, while bypassing potential confounds associated with decoding approaches that focus on spatial features. |
| spellingShingle | Hajonides, J Nobre, AC Van Ede, F Stokes, M Decoding visual colour from scalp electroencephalography measurements |
| title | Decoding visual colour from scalp electroencephalography measurements |
| title_full | Decoding visual colour from scalp electroencephalography measurements |
| title_fullStr | Decoding visual colour from scalp electroencephalography measurements |
| title_full_unstemmed | Decoding visual colour from scalp electroencephalography measurements |
| title_short | Decoding visual colour from scalp electroencephalography measurements |
| title_sort | decoding visual colour from scalp electroencephalography measurements |
| work_keys_str_mv | AT hajonidesj decodingvisualcolourfromscalpelectroencephalographymeasurements AT nobreac decodingvisualcolourfromscalpelectroencephalographymeasurements AT vanedef decodingvisualcolourfromscalpelectroencephalographymeasurements AT stokesm decodingvisualcolourfromscalpelectroencephalographymeasurements |