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Data science for psychology and neuroscience in Python

An introduction to data management, manipulation, visualization, and analysis for neuroscience. Students will learn scientific programming in Python, and use this to work with example data from areas such as cognitive-behavioral research, single-cell recording, EEG, and structural and functional MRI. Basic signal processing techniques including filtering are covered. The course includes a Jupyter Notebook and video tutorials.


Topics covered in this lesson
  • Introduction to the technologies used in the course
  • Introduction to data science and tools for neural data science
  • Introduction to Python 
    • Intro to Jupyter Notebooks in CoCalc
    • Data types
    • Flow control
    • Working with data
  • Introduction to Data Visualization
    • Intro to Plotting with Matplotlib
    • Procedural vs Object-Oriented Plotting
    • Subplots
    • Intro to plotting with Seaborn
  • Introduction to Exploratory data analysis
    • Working with repeated measures data
    • Data cleaning: dealing with outliers
    • Basic Statistics in Python: tests with SciPy
  • Introduction to single unit data
    • Single unit data and Spike Trains
    • Introducing multi-electrode data
  • Introduction to EEG/ERP data
    • EEG in the Time and Frequency Domains
    • MNE-Python
    • EEG-ERP Preprocessing
    • Group Analysis of ERP data
  • Introduction to MRI data
    • Reading and visualizing structural MRI data 
    • Working with NIftTi images
  • Experience with Python Programming Language
  • Experience with Jupyter Notebooks
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