2024 2

• TimeTue 10:30~12:00/ Thr 10:30~12:00
• RoomRoom 301, Dasan Building
• Course DescriptionNeuroinformatics is the field to investigate the brain function with the information science methods and generally covers the studies regarding brain connections, neuronal networks, nervous systems’ genes and proteins, etc. The goal of this class is to learn the basic theories for information processing (e.g., signal processing, machine learning and statistics) and then how to apply them for the analysis of neuronal data such as EEG, fMRI and spike train time series, etc. Textbooks: 1. "Advanced Data Analysis in Neuroscience", Springers 2017 (Daniel Durstewitz) 2. "Statistical Signal Processing for Neuroscience and Neurotechnology", Academic Press 2010 (Karim G. Oweiss) References: 1. "Pattern Recognition and Machine Learning," Springer 2006 (Christopher M. Bishop) 2. "Neural Networks and Deep Learning," Springer 2018 (Charu C. Aggarwal) 3. "Handbook of Bio-/Neuro-Informatics," Springer 2014 (Nikola Kasabov) 4. "Analysis of Neural Data," Springer 2014 (Robert E. Kass, Uri T. Eden, Emery N. Brown)