Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data during an inner...

Area of Science:

• Neuroscience
• Cognitive Science
• Biomedical Engineering

Background:

• Inner speech, or covert speech, is crucial for communication, especially for individuals with speech impairments.
• Decoding inner speech is a key goal for developing advanced brain-computer interfaces (BCIs).

Purpose of the Study:

• To introduce a novel, publicly available dataset of simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data.
• To support research in inner speech processing, multimodal neuroimaging, and BCI applications.

Main Methods:

• Collected simultaneous EEG and fMRI data from three participants performing an inner speech task (silent word repetition).
• Utilized a 64-channel MR-compatible EEG cap and a 3T fMRI scanner with an EPI sequence.
• Applied artifact correction for gradient and cardioballistic noise in EEG and fMRI data.

Main Results:

• A comprehensive dataset of neural activity during inner speech is now publicly accessible.
• The data allows for the investigation of neural correlates of inner speech using complementary neuroimaging modalities.

Conclusions:

• This dataset provides a valuable resource for advancing the understanding of inner speech.
• Facilitates research in EEG-fMRI fusion and the development of BCI-driven speech prostheses.