Is a detailed look at the synchronization and neural code fidelity of gamma oscillations.

A 2015 SFN poster outlining the motivation, methods, and results of this work is available here

Simulation and initial analysis is in Python 2.7. Plotting and some light analysis is in R. Code has been tested *Nix systems, in OSX (10.11) and Linux (Ubuntu 4.10). It won't work on Windows.

1. Download or clone this repo to somewhere on your python path
2. Run all experiments (via the command line) by callling make sfn from the top-level syncological directory.

Note: the experiments are run in parallel, on up to 12 cores (though this can expanded in the Makefile). If you have 12 cores available, as I do. These simulation will take several hours to complete.

Open the analysis/sfn_figures.Rmd in Rstudio (see below) and run it.

The R and Python (combined() code has substantial dependencies. It you already have basic scientific installs of each, these should be easy to fulfill. That said, I've not created a proper install file so you'll have to do it by hand.

The Python dependencies are:

• Brian2
• numpy
• scipy
• fakespikes
• PySpike

For R based plotting I highly recommend you download and install Rstudio from which is it very easy to install the following

• ggplot2
• grid
• gridExtra
• plyr
• dplyr
• reshape
• png
• psd
• tidyr
• doParallel
• bspec

The final 'system' dependency is GNU Parallel, which can be install on Linux via your package manager or on OSX by brew install parallel.