Python implementation of code in Analyzing Neural Time Series by Mike X. Cohen.

Click this badge to run interactive code in your browser:

Update Oct 2021: Cleaning files, and finishing the rest of the chapters whenever I have some time.

See environment.yml

Analyzing Neural Time Series by Mike Cohen is a great book written for neuroscientists working with continuous neural data. Although it may seem like the book is mainly written for EEG analysis, I found that the topics in the book are easily translatable to any domain requiring continuous-data signal processing. Each chapter introduces a new technique, with heavy emphasis on concepts rather than mathematical rigor, and even has summaries at the end of each chapter with tips on how to describe the analysis in the methods section of your paper.

• change scipy.io.loadmat to mne.externals.pymatreader.read_mat
• Chapter 6 cleanup
• Chapter 9 cleanup
• Chapter 10 cleanup
• Chapter 11 cleanup
• Chapter 12 cleanup
• Chapter 13 cleanup
• Chapter 14 cleanup
• Chapter 15 cleanup
• Chapter 16 cleanup
• Chapter 17 cleanup
• Chapter 18 cleanup
• Chapter 19 WIP
• Chapter 20
• Chapter 21 [no figs]
• Chapter 22 [requires external methods + topoplot]
• Chapter 23 [almost done except 23.4 needs topoplot]
• Chapter 24 [no figs]
• Chapter 25
• Chapter 26
• Chapter 27
• Chapter 28 [requires arm orf.m]
• Chapter 29 [one fig requires topoplot]
• Chapter 30
• Chapter 31
• Chapter 32 [no figs]
• Chapter 33
• Chapter 34
• Chapter 35 [no figs]
• Chapter 36 [no figs]