In this BrainTalks seminar, the first group of NeuroData students provide interesting glimpses into their master’s thesis topics, just before they move forward from JYU.
Giulio Benedetti: "Decoding Attention States from MEG Neural Activity in Childhood"
Austin Drake: "Structure and Function: decoding aerobic fitness and physical activity from contrasting brain measures using non-linear SVM regression."
Aracely Gutierrez-Lomelí: “Brain-Body Coupling: Decoding heart rate variability states across respiration patterns using magnetoencephalography”
Arna Aimysheva: “Decoding Arousal and Valence from MEG Frequency Bands with XGBoost”
Kanykei Mairambekova: "Classifying Aerobic Fitness and Physical Activity Levels from Structural and Functional Brain Connectivity: A Multimodal DTI and MEG Machine Learning Study".
NeuroData is a joint Erasmus Mundus master’s program in Brain and Data Science. It trains students to respond to the growing need of both science and society to integrate the most suitable computational methods to solve increasingly complex questions in neuroscience. The program comprises of at least two study periods, which must differ from the students’ country of residence.
