Over the past three decades, a number of seizure prediction, or forecasting, methods have
been developed. Although major achievements were accomplished regarding the statistical …

This research introduces a new method for functional brain imaging via a process of model
inversion. By estimating parameters of a computational model, we are able to track effective …

We present a framework for the identification of spatiotemporal linear dynamical systems.
We use a state-space model representation that has the following attributes: 1) the number …

This paper provides a new method for model-based estimation of intra-cortical connectivity
from electrophysiological measurements. A novel closed-form solution for the connectivity …

Engineered nanoparticles (NPs) offer great application potential in various fields, for
example the chemical industry, energy management or medical sciences. Nanoparticles are …

Several natural phenomena are known to exhibit a spatio-temporal evolution process. The
study of such processes, which is pivotal to our understanding of how best to predict and …

The paper analyzes wave-type partial differential equations that describe the transmission of
neural signals and proposes filtering for estimating the spatiotemporal variations of voltage …

In the present article, we implement a new numerical scheme, the quasilinearized semi-
orthogonal B-spline wavelet method, combining the semi-orthogonal B-spline wavelet …

The human brain is one of the most complex systems faced in research and science.
Different methods and theories from various categories of science and engineering have …

The integro-difference equation (IDE) is an increasingly popular mathematical model of
spatiotemporal processes, such as brain dynamics, weather systems, and disease spread …