Introduction to analysis of neural data and brain connectivity

Venue: Universitat Politecnica de Barcelona (XII Summer School UPC-UB edition)
Date: from 2nd to 6th of July 2018 (afternoons), 15 hours in total



The course is an introduction to data analysis in neuroscience. The aim is to understand standard concepts and methods used to study and interpret brain connectivity (e.g., Granger causality, graph theory, machine learning) with a focus on their statistical aspects. During the course, students will use real data (whole-brain functional and structural MRI) and improve their programming skills (Python with numpy, scipy and scikit-learn) to implement such methods and discuss their findings.

Specific objectives:

Transversal objectives:


The students will be evaluated via a hands-on project developed during the course in small groups (up to three participants). They will be asked to summarize their results and present them in front of the whole class.
For those students willing to have a certificate, an evaluation will be given by the UPC.


Students are expected to have basic knowledge in applied maths (linear algebra and calculus), as well as some programming skills. Knowledge of Python is recommended, but we will provide a small set of exercises to level up before the course for those that are familiar with other programming languages.