Name

Affiliation

Country

Title

Benjamin Blankertz

TU Berlin

Germany

The virtue of combining a model-based and a data-driven approach for Brain-Computer Interfacing.

Guan Cuntai

Nanyang University of Technology

Singapore

Brain-Computer Interface-based Gait Prediction for Lower-Limb Stroke Rehabilitation

Pamela Douglas

UCLA

USA

Towards a White Matter Ephaptic Coupling Model for EEG/MEG Spectral Densities

Martin Hebart

Max Planck Institute for Human Cognitive and Brain Sciences

Germany

Revealing interpretable object representations from human visual cortex and artificial neural networks

Andrea Kübler

University of Würzburg

Germany

Correlation between neurophysiological measures of consciousness and BCI performance in a locked-in patient

Klaus-Robert Müller

TU Berlin

Germany

Interpreting Deep Learning Models for Multi-modal Neuroimaging

Marieke Mur

Western University

Canada

TBA

Srikantan Nagarajan

University of California, San Francisco

USA

Advances in Imaging of Neural Oscillations

Daniel B. Rubin

Harvard Medical School

USA

BrainGate: An Intracortical Brain-Computer Interface for the Restoration of Communication and Functional Independence for People with Paralysis