Description
In this project you will be part of a scientific collaboration between the Neural Data Science group and the LWL-Universitätsklinikum Bochum (Clinic for Psychiatry). The goal is to find signatures in EEG data that correlate with emotional and cognitive states in humans. The data is measured in ongoing experiments at the Klinikum, in which participants are asked to imagine positive and negative emotions, as well as different objects and abstract concepts. We will apply various spectral methods to analyse the EEG in relation to the different task conditions. In addition, we will use machine learning algorithms, such as Hidden Markov Models, to determine whether the different task conditions are related to specific oscillatory latent states. In your project you will be responsible for processing and analysing the data sets, using state-of-the-art signal processing and machine learning tools. You will also have the opportunity to learn about EEG data recording procedures and participate in conducting experiments at the Klinikum. This project is ideal for an MSc Cognitive Science student with strong interests in neuroscience, data analysis, and the clinical context of mental health research.
Prerequisites: Python programming, completed courses related to neuroscience and artificial intelligence