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Predicting Motor Imagery Performance From Resting-State EEG Using Dynamic Causal Modeling
Frontiers in Human Neuroscience 14 (2020)
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Citations of this work
Vividness of Visual Imagery and Personality Impact Motor-Imagery Brain Computer Interfaces.Nikki Leeuwis, Alissa Paas & Maryam Alimardani - 2021 - Frontiers in Human Neuroscience 15.
A Fusion-Based Technique With Hybrid Swarm Algorithm and Deep Learning for Biosignal Classification.Sunil Kumar Prabhakar, Harikumar Rajaguru, Chulho Kim & Dong-Ok Won - 2022 - Frontiers in Human Neuroscience 16.
Multimodal resting-state connectivity predicts affective neurofeedback performance.Lucas R. Trambaiolli, Raymundo Cassani, Claudinei E. Biazoli, André M. Cravo, João R. Sato & Tiago H. Falk - 2022 - Frontiers in Human Neuroscience 16:977776.
References found in this work
Critiquing the Concept of BCI Illiteracy.Margaret C. Thompson - 2019 - Science and Engineering Ethics 25 (4):1217-1233.
Does Motor Simulation Theory Explain the Cognitive Mechanisms Underlying Motor Imagery? A Critical Review.Helen O’Shea & Aidan Moran - 2017 - Frontiers in Human Neuroscience 11.
Breathing is coupled with voluntary initiation of mental imagery.Timothy J. Lane - 2022 - NeuroImage 264.
User’s Self-Prediction of Performance in Motor Imagery Brain–Computer Interface.Minkyu Ahn, Hohyun Cho, Sangtae Ahn & Sung C. Jun - 2018 - Frontiers in Human Neuroscience 12.
Effects of user mental state on EEG-BCI performance.Andrew Myrden & Tom Chau - 2015 - Frontiers in Human Neuroscience 9.
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