Computational Neuroscience

This study track is intended for those with either a background in neurobiology or informatics looking to gain a basic understanding of computational neuroscience.

Computational neuroscience is a branch of neuroscience that employs mathematical models, theoretical analysis, and abstractions of the brain to understand the principles that govern the development, structure, physiology, and cognitive abilities of the nervous system. Computational neuroscience focuses on the description of biologically plausible neurons and their physiology and dynamics, and it is therefore not concerned with biologically unrealistic disciplines such as connectivity, machine learning, artificial neural networks, artificial intelligence, and computational learning theory. 

Computational neuroscience

Computational neuroscience: the basics

Introduction to modeling the brain.
Statistical models

Statistical models

Introductory lectures on different aspects of statistical models.
Biophysical models

Biophysical models

Introductory lectures on different aspects of Biophysical models.
Biochemical models

Biochemical models

Introductory lectures on different aspects of biochemical models.
Dynamical neural systems

Dynamical neural systems

Introductory lectures on different aspects of biochemical models.
Cajal Programme

Cajal Course in Computational Neuroscience

The CAJAL computational neuroscience courses are held at the Champalimaud Centre for the Unknown, Lisbon, Portugal. They are part of the CAJAL Advanced Neuroscience Training Programme, which offers state-of-the-art hands-on training courses in neuroscience.