Lecture
2024. 2
Neuroinformatics
- TimeTue 10:30~12:00/ Thr 10:30~12:00
- Teacher Assistance
- 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)
