Patterns of brain activity are associated with different brain processes and can be used to identify different brain states and make behavioral predictions. However, the relevant features are not readily apparent and accessible. To mine informative latent representations from multichannel EEG recordings, we propose a novel differentiable EEG decoding pipeline consisting of learnable filters and a pre-determined feature extraction module. Read the rest of this entry…
A new study reports for the first time functional interactions among brain rhythms in music perception using a novel, elegant, multiplex-aware approach based on a community detection algorithm.
We investigated the possibility of using a machine-learning scheme in conjunction with commercial wearable EEG-devices for translating listener’s subjective experience of music into scores that can be used in popular on-demand music streaming services.
An opinion study published in Frontiers in Human Neuroscience that focuses on the risk assessment of translating brain stimulation procedures to pediatric cases. Read the rest of this entry…
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