Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …

Understanding how neural systems integrate, encode, and compute information is central to
understanding brain function. Frequently, data from neuroscience experiments are …

Objective: This paper investigates the multivariate oscillatory nature of
electroencephalogram (EEG) signals in adaptive frequency scales for epileptic seizure …

The understanding of neurophysiological mechanisms responsible for motor imagery (MI) is
essential for the development of brain-computer interfaces (BCI) and bioprosthetics. Our …

We apply artificial neural network (ANN) for recognition and classification of
electroencephalographic (EEG) patterns associated with motor imagery in untrained …

Electroencephalographic measurement of cortical activity subserving motor behavior varies
among different individuals, restricting the potential of brain computer interfaces (BCIs) …

The use of extreme events theory for the analysis of spontaneous epileptic brain activity is a
relevant multidisciplinary problem. It allows deeper understanding of pathological brain …

The ultimate goal of epileptology is the complete abolishment of epileptic seizures. This
might be achieved by a system that predicts seizure onset combined with a system that …

A review of physical and mathematical methods for reconstructing the functional networks of
the brain based on recorded brain activity is presented. Various methods are considered, as …

In this paper we study the structural properties of a functional network of the human brain
during the evaluation of mental tasks using the concept of betweenness centrality. We carry …