The growing applications of Brain-Computer Interface (BCI) urge researchers to find optimized solutions for efficient, non-invasive brain activity pattern recognition, particularly for cognitive analytics. The existing cognitive analytic techniques and methods have adopted extensively in various areas such as image recognition, voice recognition, artificial intelligence, etc. The study on Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) pattern recognition is becoming increasingly crucial nowadays. Non-invasive cognitive analytics methods offer safe and efficient solutions for brain activity analysis, especially when several different non-invasive methods are combined to solve complicated cognitive analysis problems.
The main focus of this special issue is on the recent advances and applications of noninvasive mechanisms for cognitive analytics. The topics may include but are not limited to the following list:
• Brain signal analytics based on noninvasive methods
• Complex networks and graph theory on cognitive analytics
• Cutting edge technologies on EEG/fMRI/MEG
• Computer vision and cognitive analytics
• Hybrid noninvasive methods for cognitive analytics
• Machine learning and deep learning on cognitive analytics
• New models and theories of cognitive analytics
• Noninvasive mechanisms for brain signal analysis
• Practical applications of noninvasive cognitive analytics
• Temporal-spatial improvement for noninvasive methods

Important Dates
Paper Submission deadline: Dec 20, 2021
First round notification: Jan 20, 2022
Final decision notification: March 1, 2022

Submission Instructions
For submission instructions please visit the journal website at https://braininformatics.springeropen.com/
or contact Hao Lan Zhang at haolan.zhang@nit.zju.edu.cn