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Our lab’s open-source Python library for real-time EEG/MEG signal processing, neurofeedback, and BCI applications is now publicly available.
Holistic graph learning applied to resting-state MEG data reveals shared and individual network signatures of tinnitus.
Resting-state EEG combined with an explainable AI framework predicts individual responsiveness to acoustic tinnitus suppression.
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One is thus led to conclude that the description of reality as given by a wave function is not complete.
