The Embodied Neural Computation and Awareness Lab at the University of Montana

Projects

Some of our more popular tools (together, downloaded more than 20,000 times from conda-forge and the PyPi package server!) are featured here. You can find more software on my or the lab’s Github accounts. We also make contributions to other open source projects, like MNE-Python, PyPREP, and more.

p2prev
p2prev Software Package

For making inferences about the population prevalence of experimental effects

niseq
niseq Software package

Non-parametric sequential tests with multiple testing. You can use this to determine your sample size for neuroimaging (or other!) experiments adaptively.

MNE-ARI
MNE-ARI Software package

All Resolutions Inference a.k.a. statistically-valid circular analysis. Useful for making claims about the spatiotemporal extent of effects in neuroimaging data. Included with MNE-Python’s standalone installer.