Methodological Courses

Arduino and Microcontrollers Course

This course is intended as an introduction to using arduino and microcontrollers.

Data Modelling

In this course we will explore the data analysis process from the beginning —the moment a set of data comes out of a subject's brain and/or behaviour— to the end —the moment we make an inference about how the brain and/or cognition works. In doing this, we wil cover data treatment and management (e.g., tidy datasets), graphical data exploration, data manipulation (e.g., standardisation, centering) and, of course, data modelling. We will focus on mixed-effect models as our main statistical tool, which is a very general approach that covers essentially all kind of datasets a neuroscientist might ever want to tackle -- from cell biology, to system neuroscience, to psychophysics.  

Introduction to Electronics

Along this course you will be guided through a rational pathway touching different topics in the field of electronics. By following a theoretical approach with practical examples connected to the scientific laboratory environment, the course is open to everybody who aims to understand and take advantage of electronics as a tool for their research.

Methodologies of fMRI and TMS

Instructor : Sandra Arbula

Magnetic Resonance Imaging (MRI) and Transcranial Magnetic Stimulation (TMS) are common research tools in neuroscience used to investigate the neural correlates of human cognitive functions.

Scientific programming: A crash course

Basic coding skills are essential in science, but, unfortunately, many students do not receive formal training in programming and are often left to figure things out for themselves. The aim of this short crash course is cover enough of the core principles that you can feel confident in continuing your coding journey through self-directed learning and discovery. By the end of the course, you should be able to script a basic experiment, handle data, and plot graphs.

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