Neuroscience Tutorials

Learning resources for neuroscience students

The goal of this page is to provide beginning neuroscience students with resources that will help them prepare for the first-year graduate course work in Neuroscience at the University of Washington.

Programming Resources

Proficiency in programming languages such as MATLAB or Python has become an essential tool for neuroscience research. Developing programming skills requires years of consistent work. We have compiled some resources to help you learn to program. The MATLAB and Python cheatsheets provide the most basic programming examples for those starting out. We also provide more advanced resources. The Allen Brain Institute has kindly provided resources for learning Python.

• Basic MATLAB Programming Cheatsheet
• Basic Python Programming Cheatsheet
• Introduction to Matlab Programming from Vanderbilt U.
• Advanced MATLAB Resources from MathWorks
• Allen Institute Python Resources

Calculus

• Integration
  • Grant Sanderson’s tutorials on basic calculus concepts with nice illustrations of the concepts.
  • Khan Academy Calculus Tutorials
• Differentiation
  • Grant Sanderson’s tutorials on basic calculus concepts with nice illustrations of the concepts.
  • Khan Academy Calculus Tutorials

Linear Algebra

Linear algebra is a very important tool in neuroscience and machine learning. Below, are some resources for learning these concepts. I recommend starting with the videos from Grant Sanderson illustrating the basic concepts of linear algebra. In preparation for the neuroscience course work, gaining a solid conceptual understanding of matrix multiplication will help in understanding the more advanced topics covered in the course work such as eigendecomposition and singular value decomposition.

• Resources
  • Grant Sanderson’s illustrations of basic concepts of linear algebra. I highly recommend watching these before diving into an online course.
  • Gilbert Strang’s online linear algebra course at MIT.

Statistics

1. 1. Khan Academy course on statistics and probability
   2. Methods for determining the differences between two distributions
      • Signal Detection Theory
      • Information Theory
        • Entropy
        • Mutual Information

General Resources

Adrienne Fairhall and Raj Rao here at UW have put together a very nice online introduction to computational neuroscience, which can be accessed HERE. This course is a very nice overview of computational neuroscience concepts and does not take much time to complete.