Exploring Neural Data

Try your hand at understanding the brain by learning to analyze neural data yourself! Working with real neural data sets from neuroscience research labs, you’ll learn data analysis techniques so you can discover for yourself how the brain works.

About The Course

Exploring Neural Data is an opportunity to learn about neuroscience research and explore questions related to how brains work. It is an introductory level course designed to help you understand the real-life challenges faced by neuroscientists as they work with the large amount of data they collect from the brain. Leading neuroscientists will give tours of their labs, describe their research, and explain their data analytic techniques. You will have the chance to explore actual data collected in these researchers' labs.

Throughout the course, you will gain knowledge in three main areas: basic principles of neuroscience and questions driving research in this field; programming with the open-source language Python; and essential techniques for data analysis. We will begin by exploring single neurons, then turn our attention to multiple neurons, and finally consider tools that sample from tens of thousands of neurons. At the end of the class, you will have the opportunity to investigate in detail a data set of your choice provided by one of the researchers whose work you've learned about.

Frequently Asked Questions

What are the basic requirements for this class?
You’ll need a reliable Internet connection, a computer onto which you can install the Python programming language and other free software, and some curiosity. While you can view course videos on some tablets and mobile phones, you will definitely need a computer to complete the assignments.

Will I receive a Statement of Accomplishment for completing this class?
Yes. If you successfully complete the class, you’ll receive a Statement of Accomplishment signed by the instructors.

Can I take this course on the Signature Track?
At this time we are not offering a Signature Track option for this class.

Do I need to be programmer to take this class?
No, you don't need to be an experienced programmer to be successful in this class, although some very basic knowledge of programming is helpful. If you’re entirely new to programming, you may have to work a little harder at the beginning—and you’ll probably want to go through the optional materials on Python programming that we will provide. But you can definitely make it through the course!

If you want to try to learn a little programming before the course begins, you’ll find many free online tutorials that can help you get started. For example, the Python tutorial offered by Codecademy is one that we recommend.

What kind of computer will I need to complete the assignments?
If you plan to complete the programming assignments for the course, you’ll need to make sure your computer can run the free software that we will be using. If your computer meets the following requirements, you should be fine.

For Windows users, the minimum system requirements are:
  • Windows XP/Vista/7/8
  • 32/64-bit x86 processor
  • 512 MB RAM (1 GB recommended)
  • 1024x768 screen resolution
For Macintosh users:
  • Mac OS X 10.5 or higher
  • 64-bit x86 processor
  • 1 GB RAM (2 GB recommended)
  • 1024x768 screen resolution
For Linux users:
  • 512 MB RAM (1 GB recommended)
  • 1024x768 screen resolution
  • Oracle JRE 1.6+ or OpenJDK 7+
Can I use a language other than Python to complete the course assignments?
We are assuming that you will use Python to complete the course assignments.  All data and example code provided to you will be in Python format.  Your submissions must also be in Python format.  We will support the use of Python on the Discussion Forums.
That being said, if you wish to convert everything to another language, you are welcome to do that.  However, your programming assignment submission will need to be converted back into Python for grading.  You can complete any problem set components graded via peer assessment (including the final project) without converting back to Python.

Recommended Background

There are no prerequisites for this class. We welcome anyone who is curious about the subject and wants to learn more about the collection and analysis of neuroscience data.

Knowledge of basic programming (arrays, loops, etc.) may help you get started quickly, but there is no expectation that you have prior experience with programming. Optional materials designed to help you get started with Python will be available at the beginning of the course.