About this Research Topic
The brain state is a recurring activity pattern distributed across the brain that emerges from physiological or cognitive processes. These patterns are neurobiological phenomena with functional (e.g., behavioral) relevance. However, many obstacles remain between the ability to accurately predict and estimate the brain state and further to perturb to force a transition from one brain state to another. Recent progress in computational analysis makes it possible to describe brain dynamics and their relation to brain function.
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
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
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