Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those
using motor-imagery (MI) data, have the potential to become groundbreaking technologies …

Recent advances in neuroscience have paved the way to innovative applications that
cognitively augment and enhance humans in a variety of contexts. This paper aims at …

Deep-learning models have enabled performance leaps in analysis of high-dimensional
functional MRI (fMRI) data. Yet, many previous methods are suboptimally sensitive for …

For people who cannot communicate due to severe paralysis or involuntary movements,
technology that decodes intended speech from the brain may offer an alternative means of …

The ability to measure functional brain responses non-invasively with ultra high field MRI (7
T and above) represents a unique opportunity in advancing our understanding of the human …

Denervation due to amputation is known to induce cortical reorganization in the
sensorimotor cortex. Although there is evidence that reorganization does not lead to a …

Brain-computer interfaces (BCIs) based on functional magnetic resonance imaging (fMRI)
provide an important complement to other noninvasive BCIs. While fMRI has several …

Brain–machine interfaces (BMIs) using motor cortical activity to drive an external effector like
a screen cursor or a robotic arm have seen enormous success and proven their great …

Network science and engineering provide a flexible and generalizable tool set to describe
and manipulate complex systems characterized by heterogeneous interaction patterns …

Neurofeedback training using real‐time functional magnetic resonance imaging (rtfMRI‐NF)
allows subjects voluntary control of localised and distributed brain activity. It has sparked …