This lecture provides an introduction to entropy in general, and multi-scale entropy (MSE) in particular, highlighting the potential clinical applications of the latter.
This lecture gives an overview of how to prepare and preprocess neuroimaging (EEG/MEG) data for use in TVB.
In this lecture, you will learn about various neuroinformatic resources which allow for 3D reconstruction of brain models.
This lecture provides an general introduction to epilepsy, as well as why and how TVB can prove useful in building and testing epileptic models.
This lesson provides a brief introduction to the Computational Modeling of Neuronal Plasticity.
This lesson covers spike-rate adaptation, the process by which a neuron's firing pattern decays to a low, steady-state frequency during the sustained encoding of a stimulus.
In this lesson, you will learn a computational description of the process which tunes neuronal connectivity strength, spike-timing-dependent plasticity (STDP).
This lesson briefly wraps up the course on Computational Modeling of Neuronal Plasticity.