Book
Interested in learning Python or MATLAB for neural data analysis?
Need to develop new skills to analyze the data you collected?
Looking for new material to teach your (remote) neuroscience course?
Print (MATLAB)
Case Studies in Neural Data Analysis with code here.
As neural data becomes increasingly complex, neuroscientists now require skills in computer programming, statistics, and data analysis. This website and book teaches practical neural data analysis techniques by presenting example datasets and developing techniques and tools for analyzing them. Each section begins with a specific example of neural data, which motivates mathematical and statistical analysis methods that are then applied to the data. This practical, hands-on approach is unique among data analysis textbooks and guides, and equips the reader with the tools necessary for real-world neural data analysis.
Each resource begins with an introduction to programming, in either Python or MATLAB (Readers familiar with programming may skip this content and instead focus on data type or method type.) The material goes on to cover neural field data and spike train data, spectral analysis, generalized linear models, coherence, and cross-frequency coupling. Each section offers a stand-alone case study that can be used separately as part of a targeted investigation. The material includes some mathematical discussion, but does not focus on mathematical or statistical theory, emphasizing the practical instead. References are included for readers who want to explore the theoretical more deeply. The data and accompanying code are freely available in Python and MATLAB. The material can be used for upper-level undergraduate or graduate courses or as a professional reference.
