Posted on 26 June 2017 in Pietro's Data Bulletin
TL;DR: If you use a certain criteria to first select a part of your data (e.g. a certain set of neurons) and then test another related measure on this subset, you might be heavily biasing your results. An easy way to prevent this is to use half of your data for selection, and the other half for testing.
Posted on 20 June 2017 in Pietro's Data Bulletin
TL;DR: With little effort, you can get a lot more from your data than by just comparing means and plotting bar plots: a recent paper elaborates on graphical methods that could be an good addition to your data analysis toolbox.
Posted on 10 June 2017 in tutorials
A comparison of LDA scores or decoding accuracies between neural recordings with different numbers of neurons may be contaminated by the dimensionality of the data, and should thus be handled with care.