Data Analysis Hangout - February 16, 2018
Welcome to a neural data analysis and modelling - hangout
We are a team of experienced computational neuroscientists available to help you out with these and other data related questions.
Come sit with us and discuss your data analysis needs!
If you want:
- to understand a method from a published paper related to your work
- to know if a certain analysis is meaningful for your data
- to cross-validate your methods / implementation
- to explore new analysis possibilities
- to model your data
- help with MATLAB / PYTHON / R tools
This time we’ll talk about the use of Principal Component Analysis (PCA) for neuroscience data. This will be done during the first 30 minutes of our hangout.
PCA is a method that can simplify large datasets (e.g. many neurons simultaneously recorded in different experimental conditions) while preserving relevant information in them. This usually helps to
intuitively interpret experimental results and to guide further hypothesis-driven investigation.
We’ll have a showcase of some interesting published examples, from spike sorting all the way up to cognitive neuroscience, and will try work on the intuition behind each case.