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 …

Many biological and neural systems can be seen as networks of interacting periodic
processes. Importantly, their functionality, ie, whether these networks can perform their …

Taking a step-by-step approach to modelling neurons and neural circuitry, this textbook
teaches students how to use computational techniques to understand the nervous system at …

Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and
technology. For example, adaptive couplings appear in various real-world systems, such as …

Spike-frequency adaptation (SFA) is a fundamental neuronal mechanism taking into account
the fatigue due to spike emissions and the consequent reduction of the firing activity. We …

Alzheimer's disease is the most common cause of dementia and is linked to the spreading of
pathological amyloid-β and tau proteins throughout the brain. Recent studies have …

Neural mass models have been used since the 1970s to model the coarse-grained activity
of large populations of neurons. They have proven especially fruitful for understanding brain …

Low-dimensional neural mass models are often invoked to model the coarse-grained activity
of large populations of neurons and synapses and have been used to help understand the …

Computational models lie at the intersection of basic neuroscience and healthcare
applications because they allow researchers to test hypotheses in silico and predict the …

Most human neuroscience research to date has focused on statistical approaches that
describe stationary patterns of localized neural activity or blood flow. While these patterns …