EEG-based BCI Dataset of Semantic Concepts for Imagination and Perception Tasks
Abstract Electroencephalography (EEG) is a widely-used neuroimaging technique in Brain Computer Interfaces (BCIs) due to its non-invasive nature, accessibility and high temporal resolution. A range of input representations has been explored for BCIs. The same semantic meaning can be conveyed in diff...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-06-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-023-02287-9 |
| _version_ | 1797801602745106432 |
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| author | Holly Wilson Mohammad Golbabaee Michael J. Proulx Stephen Charles Eamonn O’Neill |
| author_facet | Holly Wilson Mohammad Golbabaee Michael J. Proulx Stephen Charles Eamonn O’Neill |
| author_sort | Holly Wilson |
| collection | DOAJ |
| description | Abstract Electroencephalography (EEG) is a widely-used neuroimaging technique in Brain Computer Interfaces (BCIs) due to its non-invasive nature, accessibility and high temporal resolution. A range of input representations has been explored for BCIs. The same semantic meaning can be conveyed in different representations, such as visual (orthographic and pictorial) and auditory (spoken words). These stimuli representations can be either imagined or perceived by the BCI user. In particular, there is a scarcity of existing open source EEG datasets for imagined visual content, and to our knowledge there are no open source EEG datasets for semantics captured through multiple sensory modalities for both perceived and imagined content. Here we present an open source multisensory imagination and perception dataset, with twelve participants, acquired with a 124 EEG channel system. The aim is for the dataset to be open for purposes such as BCI related decoding and for better understanding the neural mechanisms behind perception, imagination and across the sensory modalities when the semantic category is held constant. |
| first_indexed | 2024-03-13T04:53:03Z |
| format | Article |
| id | doaj.art-d6a86ff060fb4a2b8fcf2076d7d8fabd |
| institution | Directory Open Access Journal |
| issn | 2052-4463 |
| language | English |
| last_indexed | 2024-03-13T04:53:03Z |
| publishDate | 2023-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj.art-d6a86ff060fb4a2b8fcf2076d7d8fabd2023-06-18T11:06:11ZengNature PortfolioScientific Data2052-44632023-06-0110111110.1038/s41597-023-02287-9EEG-based BCI Dataset of Semantic Concepts for Imagination and Perception TasksHolly Wilson0Mohammad Golbabaee1Michael J. Proulx2Stephen Charles3Eamonn O’Neill4Department of Computer Science, University of BathDepartment of Engineering Mathematics, University of BristolDepartment of Psychology, University of BathDepartment of Computer Science, University of BathDepartment of Computer Science, University of BathAbstract Electroencephalography (EEG) is a widely-used neuroimaging technique in Brain Computer Interfaces (BCIs) due to its non-invasive nature, accessibility and high temporal resolution. A range of input representations has been explored for BCIs. The same semantic meaning can be conveyed in different representations, such as visual (orthographic and pictorial) and auditory (spoken words). These stimuli representations can be either imagined or perceived by the BCI user. In particular, there is a scarcity of existing open source EEG datasets for imagined visual content, and to our knowledge there are no open source EEG datasets for semantics captured through multiple sensory modalities for both perceived and imagined content. Here we present an open source multisensory imagination and perception dataset, with twelve participants, acquired with a 124 EEG channel system. The aim is for the dataset to be open for purposes such as BCI related decoding and for better understanding the neural mechanisms behind perception, imagination and across the sensory modalities when the semantic category is held constant.https://doi.org/10.1038/s41597-023-02287-9 |
| spellingShingle | Holly Wilson Mohammad Golbabaee Michael J. Proulx Stephen Charles Eamonn O’Neill EEG-based BCI Dataset of Semantic Concepts for Imagination and Perception Tasks Scientific Data |
| title | EEG-based BCI Dataset of Semantic Concepts for Imagination and Perception Tasks |
| title_full | EEG-based BCI Dataset of Semantic Concepts for Imagination and Perception Tasks |
| title_fullStr | EEG-based BCI Dataset of Semantic Concepts for Imagination and Perception Tasks |
| title_full_unstemmed | EEG-based BCI Dataset of Semantic Concepts for Imagination and Perception Tasks |
| title_short | EEG-based BCI Dataset of Semantic Concepts for Imagination and Perception Tasks |
| title_sort | eeg based bci dataset of semantic concepts for imagination and perception tasks |
| url | https://doi.org/10.1038/s41597-023-02287-9 |
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