About this Research Topic
Brain-machine interface (BMI) has been introduced as a potential bi-directional medium between humans/animals and machines in robotics and medicine. Different neural recording modalities such as single-unit, multi-unit, LFP, ECoG, and EEG can provide different local or global information with differences in spatial-temporal-spectral resolution, long-term stability, noise/artifact contamination, and invasiveness. There are still many key challenges toward making reliable BMIs for both neural restorative technologies and understanding the neural mechanism of the movement/speech/cognitive functions. Topics include, but are not limited to:
• Motor/sensory and speech/language recovery in different neurological disorders
• BCI for human-AI alignment
• Dimensionality reduction for neural population data analysis
• Latent dynamic analysis of neural populations
• Machine learning strategies to improve BMI decoding performance
• Novel experimental design for BMI applications
• Sensory/Neurofeedback to improve BMI efficiency
• Artifact issues in real-world BMI applications with diverse environments and conditions.
• Nonstationary neural signals across sessions/days/subjects
• Speech decoding for natural language processing
• Understanding speech generation and language processing in human subjects
We accept original studies addressing the above challenges. We are also happy to consider theory and review papers.
• Motor/sensory and speech/language recovery in different neurological disorders
• BCI for human-AI alignment
• Dimensionality reduction for neural population data analysis
• Latent dynamic analysis of neural populations
• Machine learning strategies to improve BMI decoding performance
• Novel experimental design for BMI applications
• Sensory/Neurofeedback to improve BMI efficiency
• Artifact issues in real-world BMI applications with diverse environments and conditions.
• Nonstationary neural signals across sessions/days/subjects
• Speech decoding for natural language processing
• Understanding speech generation and language processing in human subjects
We accept original studies addressing the above challenges. We are also happy to consider theory and review papers.
Keywords: Brain-Computer Interfaces, BCI, BMI, restorative technologies, movement-speech, neurfeedback, real-world BMI applications, speech decoding
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
