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 …

This paper reviews the state-of-the-art neuromarkers development for the prognosis of
Alzheimer's disease (AD) and mild cognitive impairment (MCI). The first part of this paper is …

Objective. Despite the increase in calculation power over the last few decades, the
estimation of brain connectivity is still a tedious task. The high computational cost of the …

Graph thresholding is a frequently used practice of eliminating the weak connections in
brain functional connectivity graphs. The main aim of the procedure is to delete the spurious …

Growing evidence links impairment of brain functions in Alzheimer's disease (AD) with
disruptions of brain functional connectivity. However, whether the AD brain shows similar …

Human brain activity is intrinsically organized into resting-state networks (RSNs) that
transiently activate or deactivate at the sub-second timescale. Few neuroimaging studies …

Structural brain networks derived from diffusion magnetic resonance imaging data have
been used extensively to describe the human brain, and graph theory has allowed …

The resting activity of the brain can be described by so-called intrinsic connectivity networks
(ICNs), which consist of spatially and temporally distributed, but functionally connected …

In this paper, we review state-of-the-art approaches that apply signal processing (SP) and
machine learning (ML) to automate the detection of Alzheimer's disease (AD) and its …

Functional connectivity (FC) characterizes brain activity from a multivariate set of N brain
signals by means of an NxN matrix A, whose elements estimate the dependence within each …