ArticleScientific data2023
Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning.Scientific data · 2026Article
- Imagined Speech Brain-Computer Interface: A Task-Oriented Review of Neural Decoding.Sensors (Basel, Switzerland) · 2026Review
- The current status of foundation models in decoding inner speech from non-invasive brain signals: a mini review.Frontiers in human neuroscience · 2026Review
- Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data during an inner speech task.Data in brief · 2025Article
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Authors and funding
10 authors.
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Abstract
The recognition of inner speech, which could give a 'voice' to patients that have no ability to speak or move, is a challenge for brain-computer interfaces (BCIs). A shortcoming of the available datasets is that they do not combine modalities to increase the performance of inner speech recognition. Multimodal datasets of brain data enable the fusion of neuroimaging modalities with complimentary properties, such as the high spatial resolution of functional magnetic resonance imaging (fMRI) and the temporal resolution of electroencephalography (EEG), and therefore are promising for decoding inner speech. This paper presents the first publicly available bimodal dataset containing EEG and fMRI data acquired nonsimultaneously during inner-speech production. Data were obtained from four healthy, right-handed participants during an inner-speech task with words in either a social or numerical category. Each of the 8-word stimuli were assessed with 40 trials, resulting in 320 trials in each modality for each participant. The aim of this work is to provide a publicly available bimodal dataset on inner speech, contributing towards speech prostheses.
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