Easy and fast preprocessing of EEG ERP data. Support for input and output in Excel format. Powerful tools for data visualization and analysis. Modular architecture for scalability and maintainability.

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The analysis and processing of EEG signals is complex since EEG are nonstationary ... Section III analyzes the effect of CCCA method on the feature components extraction of multi-channel event-related ...

Methods: This study used neurophysiological methods, specifically EEG, to examine the impact of voice attractiveness on cooperative behavior in the Stag Hunt Game. Participants played a two-person ...

The human brain can learn through experience to filter out disturbing and distracting stimuli—such as a glaring roadside ...

This study aims to explore the neurophysiological and neurocognitive characteristics of COMISA using electroencephalographic (EEG) spectral analysis and subjective and objective neurocognitive ...

Summary: Our brains can adapt to filter out repeated distractions, according to a new EEG study. Participants learned to ignore frequent visual distractions, such as a red shape in the same location, ...

Adapting to changes through repeated exposure. The human brain can learn to filter out distracting or disruptive stimuli, ...

Abstract: The underlying time-variant and subject-specific brain dynamics lead to inconsistent distributions in electroencephalogram (EEG) topology and representations within and between individuals.

Abstract: We propose GC-VASE, a graph convolutional-based variational autoencoder that leverages contrastive learning for subject representation learning from EEG data. Our method successfully learns ...