Post-hoc Labeling of Arbitrary M/EEG Recordings for Data-Efficient Evaluation of Neural Decoding Methods
Many cognitive, sensory and motor processes have correlates in oscillatory neural source activity, which is embedded as a subspace in the recorded brain signals. Decoding such processes from noisy magnetoencephalogram/electroencephalogram (M/EEG) signals usually requires data-driven analysis methods...
Main Authors: | Sebastián Castaño-Candamil, Andreas Meinel, Michael Tangermann |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2019-08-01
|
Series: | Frontiers in Neuroinformatics |
Subjects: | |
Online Access: | https://www.frontiersin.org/article/10.3389/fninf.2019.00055/full |
Similar Items
-
Neural decoding of expressive human movement from scalp electroencephalography (EEG)
by: Zachery Ryan Hernandez, et al.
Published: (2014-04-01) -
Decoding Brain Responses to Names and Voices across Different Vigilance States
by: Tomasz Wielek, et al.
Published: (2021-05-01) -
Deep Learning Algorithms in EEG Signal Decoding Application: A Review
by: Ramesh Babu Vallabhaneni, et al.
Published: (2021-01-01) -
Adaptive Neural Decoder for Prosthetic Hand Control
by: Andrew E. Montgomery, et al.
Published: (2021-04-01) -
Characteristics of Kinematic Parameters in Decoding Intended Reaching Movements Using Electroencephalography (EEG)
by: Hyeonseok Kim, et al.
Published: (2019-11-01)