Abstract: Independent component analysis (ICA) can find distinct sources of electroencephalographic (EEG) activity, both brain-based and artifactual, and has become a common pre-preprocessing step in ...
Free academic toolboxes have gained increasing prominence in MEG/EEG analysis as a means to disseminate cutting edge methods, share best practices between different research groups and pool resources ...
I have implemented a Correlation layer presented in DispNet. When using it OOM happens. Here is the code. class Corr(nn.Module): def __init__(self, stride=1, D=40 ...
Electroencephalography (EEG) source localization approaches are often used to disentangle the spatial patterns mixed up in scalp EEG recordings. However, approaches differ substantially between ...
This is highly comparable to the reported performance of CORRMAP, for which mean correlations with expert judgments for each study were 0.85–0.91 for lateral eye movements and 0.83–0.99 for blinks.
Independent component analysis (ICA) can disentangle multi-channel electroencephalogram (EEG) signals into a number of artifacts and brain-related signals. However, the identification and ...
A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results