Research Topic

Brain-Computer Interfaces for Perception, Learning, and Motor Control

About this Research Topic

This Research Topic is concerned with new technologies for Electroencephalography (EEG) and magnetoencephalography (MEG)-based Brain-Computer Interfaces (BCI) with special emphasis to neural underpinnings of Perception, Learning, and Motor control.

The method of EEG/MEG-data analysis may include emerging technologies of brain signal/image processing, including new algorithms on spatial filtering, feature extraction/selection, classifier design, and new control algorithms for BCI-based external robotic manipulators and Functional Electrical Stimulation based rehabilitative systems. Areas of interest include development of new algorithms for non-stationarity handling in single-trial classification of BCI data, implementing transfer learning/domain adaptation approaches in BCI.

Hybrid and multi-modal BCI also are gaining interest among researchers. Hybrid BCI attempts to utilize multiple brain signals to design and develop the BCI experiments. In contrast, multi-modal BCI employs multiple modalities of acquiring brain signals/images simultaneously or independently then attempts to fuse the brain signals/imaging information/attributes. These methods might help diagnose brain diseases and/or study cognitive functions.
We welcome both Original and Review articles using the above-mentioned technologies to develop practical stand-alone systems for future automated systems used in rehabilitative aids and to diagnose psychological diseases, memory malfunctioning (especially short-term and working memory), learning disability, neuro-motor disorders. We also welcome papers identifying brain activation regions and/or brain-connectivity involved in olfactory and tactile perception, learning, or mind-controlled artificial robotic limbs and motor control developed in BCI settings.


Keywords: Brain-computer Interfaces, Perception, Learning, Motor Control, Electroencephalography, Magnetoencephalography, Brain Stimulation


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.

This Research Topic is concerned with new technologies for Electroencephalography (EEG) and magnetoencephalography (MEG)-based Brain-Computer Interfaces (BCI) with special emphasis to neural underpinnings of Perception, Learning, and Motor control.

The method of EEG/MEG-data analysis may include emerging technologies of brain signal/image processing, including new algorithms on spatial filtering, feature extraction/selection, classifier design, and new control algorithms for BCI-based external robotic manipulators and Functional Electrical Stimulation based rehabilitative systems. Areas of interest include development of new algorithms for non-stationarity handling in single-trial classification of BCI data, implementing transfer learning/domain adaptation approaches in BCI.

Hybrid and multi-modal BCI also are gaining interest among researchers. Hybrid BCI attempts to utilize multiple brain signals to design and develop the BCI experiments. In contrast, multi-modal BCI employs multiple modalities of acquiring brain signals/images simultaneously or independently then attempts to fuse the brain signals/imaging information/attributes. These methods might help diagnose brain diseases and/or study cognitive functions.
We welcome both Original and Review articles using the above-mentioned technologies to develop practical stand-alone systems for future automated systems used in rehabilitative aids and to diagnose psychological diseases, memory malfunctioning (especially short-term and working memory), learning disability, neuro-motor disorders. We also welcome papers identifying brain activation regions and/or brain-connectivity involved in olfactory and tactile perception, learning, or mind-controlled artificial robotic limbs and motor control developed in BCI settings.


Keywords: Brain-computer Interfaces, Perception, Learning, Motor Control, Electroencephalography, Magnetoencephalography, Brain Stimulation


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.

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Submission Deadlines

30 September 2020 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

30 September 2020 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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