Overview of this book and the subject matter
This book is a work in progress as I myself go through the book, take notes, and rewrite my notes in an appealing format here!
The Textbook
The Textbook I am referring to is Analyzing Neural Time Series Data: Theory and Practice, by Mike X Cohen. This book has been very enlightening to me, however expect some prerequisites:
- A basic understanding of basic neuroscience
- The ability to read graphs
- Some basic knowledge of statistics
- A basic understanding of scientific experiment design and data analysis
- Some programming background (this book uses MATLAB)
- Patience
Any experience in analog signal processing comes handy here, and likewise, the knowledge gained from learning EEG analysis can absolutely be applied in many other places too!
My work here is essentially a "sparknotes" summary, it is not a replacement for the full textbook. The textbook contains many illustrations, examples, and further reading. For context, each chapter subsection is typically 1-2 pages long, but I summarize them typically to the size of a paragraph.
Further Resources from this author
This Github of the data and answers to the exercises can be found here
Please note I am not affiliated or have any relation to this author, I just find their work to be a good resource
Other resources that may be useful
The Psyched YouTube channel has some relevant overview videos. Personally I suggest watching videos from oldest forward. Found here
If you wish to learn some data analysis in python, I also suggest checking out NeuroMatch Acadamies CompNeuro course free here
- They also have paid courses, taught using discord, for several hundred dollars where you can work with other students on various projects and data analysis for some hands on learning
- They also have courses on other subjects, see more info here
- These courses don't strictly use EEG, but do use time series data collected from implanted electrodes, so a lot of the analysis are similar!