Physics is a field of science that has traditionally used the scientific method to answer
questions about why natural phenomena occur and to make testable models that explain the …

Alzheimer's disease (AD) is the most common type of neurodegenerative disorder, typically
causing dementia along aging. AD is mainly characterized by a pathological extracellular …

We introduce in this survey the major concepts, models, and algorithms proposed so far to
infer causal relations from observational time series, a task usually referred to as causal …

Identifying causal networks is important for effective policy and management
recommendations on climate, epidemiology, financial regulation, and much else. We …

The problem of reconstructing nonlinear and complex dynamical systems from measured
data or time series is central to many scientific disciplines including physical, biological …

An important shift is taking place in social cognition research, away from a focus on the
individual mind and toward embodied and participatory aspects of social understanding …

Granger causality is a statistical notion of causal influence based on prediction via vector
autoregression. Developed originally in the field of econometrics, it has since found …

Many complex and interesting phenomena in nature are due to nonlinear phenomena. The
theory of nonlinear dynamical systems, also called 'chaos theory', has now progressed to a …

Multivariate time series analysis is extensively used in neurophysiology with the aim of
studying the relationship between simultaneously recorded signals. Recently, advances on …

This paper reviews recent progress in the diagnosis of Alzheimer's disease (AD) from
electroencephalograms (EEG). Three major effects of AD on EEG have been observed …