Excitation-inhibition (E/I) imbalance is theorized as a key mechanism in the pathophysiology
of epilepsy, with a mounting body of previous research focusing on elucidating its cellular …

With significant investments in neuroscience over the past years, our understanding of the
brain, its link to behavior, and related disorders has greatly improved. However, a notable …

We derive a next generation neural mass model of a population of quadratic-integrate-and-
fire neurons, with slow adaptation, and conductance-based AMPAR, GABAR and nonlinear …

The motor learning theory anticipates that cerebro-cerebellar loops perform sensorimotor
prediction thereby regulating motor control. This operation has been identified during action …

Understanding the intracellular dynamics of brain cells entails performing three-dimensional
molecular simulations incorporating ultrastructural models that can capture cellular …

Neurons are considered to be the most basic structural and functional units of the nervous
system. The functions of brain are closely related to the firing activity of neurons. However, a …

We report half a century ago, in his foundation paper More is different, Anderson stated the
relevance of including multiple scales of interaction, instead of trying to reduce everything to …

Gaussian processes (GPs) are a powerful machine learning tool to reveal hidden patterns in
data. GPs hyperparameters are estimated from data, providing a framework for regression …

According to the motor learning theory by Albus and Ito, synaptic depression at the parallel
fibre to Purkinje cells synapse (pf-PC) is the main substrate responsible for learning …

The Neocortical Computational Microscale model (NeoCoMM) is a unique
neurophysiologically-inspired software. It offers a friendly graphical user interface that allows …