This lecture provides an introduction to entropy in general, and multi-scale entropy (MSE) in particular, highlighting the potential clinical applications of the latter.
In this lecture, you will learn about various neuroinformatic resources which allow for 3D reconstruction of brain 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.
In this lesson you will learn about the Bayesian Virtual Epileptic Patient (BVEP), a research use case using TVB supported on the EBRAINS infrastructure.
This lecture covers the rationale for developing the DAQCORD, a framework for the design, documentation, and reporting of data curation methods in order to advance the scientific rigour, reproducibility, and analysis of data.