Neural decoding of EEG signals

  • Teaching

    Details

    Faculty Faculty of Humanities
    Domain Psychology
    Code UE-L25.01822
    Languages English
    Type of lesson Seminar
    Level Master
    Semester SS-2025

    Schedules and rooms

    Summary schedule Wednesday 09:15 - 12:00, Hebdomadaire (Spring semester)

    Teaching

    Teachers
    • Stacchi Lisa
    Description

    The course Neural decoding of EEG signals will introduce the theoretical background of applying machine learning techniques to EEG data. It will focus on brain decoding using linear Support Vector Machine (SVM), which has proven to be very effective in the field. The course will cover the principle behind SVM classification, methods for evaluating classifier performance, and how to interpret the results. Theory will be paired with concrete examples demonstrating how these techniques have been applied in literature. Additionally, hands-on exercices in Matlab - using both simulated and real EEG data - will provide practical experience. The course will also explore how neural representations measured by EEG can be compared and related across populations and methodologies.
    Softskills No
    Off field Yes
    BeNeFri No
    Mobility No
    UniPop No
  • Dates and rooms
    Date Hour Type of lesson Place
    02.04.2025 09:15 - 12:00 Cours RM 01, Room C-01.109
    09.04.2025 09:15 - 12:00 Cours RM 01, Room C-01.109
    16.04.2025 09:15 - 12:00 Cours RM 01, Room C-01.109
    30.04.2025 09:15 - 12:00 Cours RM 01, Room C-01.109
    07.05.2025 09:15 - 12:00 Cours RM 01, Room C-01.109
  • Assessments methods

    Travail écrit - SS-2025, Session d'été 2025

    Assessments methods By rating

    Travail écrit - SS-2025, Autumn Session 2025

    Assessments methods By rating

    Travail écrit - AS-2025, Session d'hiver 2026

    Assessments methods By rating

    Travail écrit - SS-2026, Session d'été 2026

    Assessments methods By rating
  • Assignment
    Valid for the following curricula:
    Psychology 30 [MA]
    Version: SA21_MA_PS_fr_de_bil_v01
    Option Cognitive Neuroscience > Social, Cognitive and Affective Neuroscience – SCAN
    Psychology 30 [MA]
    Version: SA22_MA_PS_fr_de_bil_v01
    Option Cognitive Neuroscience > Social, Cognitive and Affective Neuroscience – SCAN