no code implementations • 31 Jan 2024 • Jonathan W. Kim, Ahmed Alaa, Danilo Bernardo
In conventional machine learning (ML) approaches applied to electroencephalography (EEG), this is often a limited focus, isolating specific brain activities occurring across disparate temporal scales (from transient spikes in milliseconds to seizures lasting minutes) and spatial scales (from localized high-frequency oscillations to global sleep activity).