Description: Neural decoding has applications in neuroscience from understanding neural populations to build brain-computer interfaces. In this computational tutorial, I will introduce neural decoding principles from a machine learning perspective using the Python programming language. The tutorial will be focused on data preprocessing, model selection and optimization for decoding neural information from spike trains and local field potentials. The studied dataset contains neural information from six cortical areas of the macaque brain spanning from the frontal to the occipital lobe.
To follow along with the tutorial, bring a laptop with Anaconda Python 3.7 installed. Download for Windows/MacOS/Linux: https://www.anaconda.com/distribution/.
If you are using your own Python distribution or older versions of Anaconda:
- Update scikit-learn to version 0.20.3:
pip install scikit-learn --upgrade - Update matplotlib to version 3.0.3:
pip install matplotlib --upgrade
Questions, feedback: @konet
Licence: BSD clause 3
Made with ❤️ @MIT