The electroencephalogram (EEG) is a neuroimaging technique used to record the electrical fluctuations occurring in the brain in correspondence to cognitive, sensory, and motor processes. Thanks also to its non-invasiveness and high-temporal resolution, EEG is a widespread tool used to investigate human cognition in a variety of settings. This course will introduce the physics and physiological principles underlying EEG signals and will provide an overview of the methodologies used in this field, with a particular emphasis on event-related potentials and frequency tagging. The course will first provide an overview of how different techniques are used in visual neuroscience. It will then move to a more practical part that will introduce the different steps involved in digital signal processing, including their advantages and disadvantages. The course will include practical sessions during which students will be able to familiarize themselves with signal processing using Matlab and the eeglab toolbox. Most of data processing will be done through the program interface but a basic understanding of Matlab (i.e., loops, variables, functions) is recommended. This class will provide students with tools to approach EEG research from both a theoretical and practical point of view. This course is aimed at Master students interested in working with EEG, from data recording to signal processing. |