About this Research Topic
Brain functional state estimation based on deep learning is an intelligent information processing approach to analyze brain imaging data and reveal the activity patterns of the brain under different tasks, environments, or physiological states. Deep learning neural networks extract and analyze complex patterns and features from large-scale brain imaging data, such as EEG, fMRI and MEG data, and so on. With deep learning, we can gain deeper insights into the relationships between different brain regions and the changes that occur during various tasks and cognitive processes.
This research topic aims to explore the advanced analysis approach for brain functional state estimation based on deep learning. Topics of interest include, but are not limited to, the following topics:
- Brain function modeling and analysis
- Brain signal estimation and reconstruction
- Neural decoding and encoding
- Brain activity and behavior
- Disease prediction and diagnosis
- Cognitive functions analysis
- Brain image processing and Neural signal processing
- Brain stimulation
- Brain imaging genomics
- Neurotechnology
- Brain-inspired AI
- Brain-computer interface applications
- Neural architecture optimization
Keywords: Brain signal estimation, Brain function, Deep Learning, Brain-inspired AI
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.