About this Research Topic
Currently, artificial intelligence (AI), and machine learning (ML) in particular, allow a better understanding of brain activity and a better brain-computer interface (BCI) mechanism of interaction. The integration of AI/ML in the data collection and monitoring phases of neuromodulation or neurofeedback can be used for early diagnosis and accurate non-pharmacological treatment of neurological diseases and disorders. Moreover, ML enables analyzing large volumes of patient information to improve the efficiency of neuromodulation and neurofeedback. The introduction of AI/ML in BCI and neuroimaging empowers these techniques for data acquisition, monitoring, analysis and prevention of neurological diseases and disorders. Thus, further investigation is necessary to understand and extend brain-computer interfaces and neuroimaging techniques implementing AI/ML. The latter integration into neuromodulation or neurofeedback can provide new opportunities to improve significantly the efficiency in the output response of these types of treating neurological diseases and disorders.
The goal of this research topic is to cover studies at the intersection of AI/ML-based BCI and neuroimaging with neuromodulation and neurofeedback in the treatment of neurological diseases and disorders. The research topic welcomes submission on topics related, but not limited, to:
• AI/ML techniques for signal conditioning of BCI and neuroimaging in neuromodulation or neurofeedback
• AI/ML techniques for pattern recognition of BCI and neuroimaging in neuromodulation or neurofeedback
• Novel algorithms in AI/ML for improving neuromodulation or neurofeedback
• Intelligent system applications with neuromodulation or neurofeedback
• AI/ML techniques applied for neurodegenerative diseases
• AI/ML for interpretability in neuromodulation or neurofeedback
• Early diagnosis and/or treatment monitoring using neuromodulation or neurofeedback with AI/ML
• AI/ML-based treatment of data in neuromodulation or neurofeedback
• Cross-disciplinary theory and methodologies between AI/ML, BCI, neuroimaging, and neuromodulation or neurofeedback
• BCI, electroencephalogram (EEG), magnetic resonance imaging (MRI), and other related interfaces with AI/ML using for neuromodulation or neurofeedback
Keywords: Artificial intelligence, neurofeedback, neuromodulation, neurodegeneration, medical engineering
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.