Frontiers in Human Neuroscience | Brain-Computer Interfaces

Confident young woman gesturing while teaching students in class

Submit your research

Start your submission and get more impact for your research by publishing with us.

Active senior woman concentrating while working on laptop

Author guidelines

Ready to publish? Check out our author guidelines for everything you need to know about submission, from choosing a journal and section to preparing your manuscript.

Front view portrait of African American man wearing lab coat and raising hand asking question while sitting in audience and listening to lecture on medicine

Editor guidelines

Reviewing a manuscript? See our editorial guidelines for everything you need to know about Frontiers’ peer review process.

Smiling colleagues doing research over laptop computer on desk in office

Peer review

Our efficient and rigorous peer review means you’ll get a decision on your manuscript in just 77 days.

Interior of a library with desks and bookshelves

Publishing fees

Article processing charges (APCs) apply to articles that are accepted for publication by our external editors, following rigorous peer review.

Editors

See all

gernot r müller-putz

Graz University of Technology

Graz, Austria

Specialty Chief Editor

Brain-Computer Interfaces
jinung an

Daegu Gyeongbuk Institute of Science and Technology (DGIST)

Daegu, Republic of Korea

Associate Editor

Brain-Computer Interfaces
george alexandrakis

University of Texas at Arlington

Arlington, United States

Associate Editor

Brain-Computer Interfaces
kai keng ang

Institute for Infocomm Research (A*STAR)

Singapore, Singapore

Associate Editor

Brain-Computer Interfaces

Brain-Computer Interfaces

Submit your research

Author guidelines

Editor guidelines

Peer review

Publishing fees

Editors

gernot r müller-putz

jinung an

george alexandrakis

kai keng ang

Articles

Neurophysiological predictors of deep learning based unilateral upper limb motor imagery classification

Editorial: Forward and inverse solvers in multi-modal electric and magnetic brain imaging: theory, implementation, and application

Hybrid brain-computer interface using error-related potential and reinforcement learning

Editorial: Sensorimotor decoding: characterization and modeling for rehabilitation and assistive technologies, volume II

Research Topics

Advancing Brain-Computer Interfaces through fNIRS and EEG integration

Neurophysiological foundations of videoconference fatigue

Brain-Computer Interfaces (BCIs) for daily activities: Innovations in EEG signal analysis and machine learning approaches

Clinically meaningful applications and evaluations of brain-computer interfaces