A neurophysiologically interpretable deep neural network predicts complex movement components from brain activity

Human Brain Mapping, Neuroimaging Journal

Topological data analysis for revealing dynamic brain reconfiguration in MEG data [PeerJ]

Deep Learning Methods for EEG Neural Classification

A Primer on Electroencephalography and Event-Related Potentials for Organizational Neuroscience - Ruxandra I. Tivadar, Micah M. Murray, 2019

Many but not all deep neural network audio models capture brain responses and exhibit correspondence between model stages and brain regions

Prediction and detection of virtual reality induced cybersickness: a spiking neural network approach using spatiotemporal EEG brain data and heart rate variability, Brain Informatics

Neural representational geometry underlies few-shot concept learning

Neurophysiological and Computational Principles of Cortical Rhythms in Cognition

Detection of ADHD From EEG Signals Using Different Entropy Measures and ANN - R. Catherine Joy, S. Thomas George, A. Albert Rajan, M.S.P. Subathra, 2022

PDF] Re-Thinking EEG-Based Non-Invasive Brain Interfaces: Modeling and Analysis

Frontiers Linear Modeling of Neurophysiological Responses to Speech and Other Continuous Stimuli: Methodological Considerations for Applied Research