tesser

Analysis of learning and neural representations of temporal community structure.

Installation

First, create a conda environment (if you don't have one for tesser yet) and activate it:

conda create -n tesser python=3.7
conda activate tesser

Clone the repository, change directory to it, then run:

pip install -e .

This should install the tesser project and all dependencies.

Running Jupyter notebooks

To run the jupyter notebooks, first install Jupyter Lab and the kernel:

pip install jupyterlab
python -m ipykernel install --user --name tesser

To run the notebooks, before you run Jupyter Lab you must define the path to a directory with the Tesser BIDS format data, and the path to save figures to. For region of interest analyses, you must also give the path to the directory where neural results are saved. For example:

export TESSER_BIDS=$HOME/Dropbox/work/tesser/bids
export TESSER_FIGURES=$HOME/Dropbox/tesser_successor/Figures/v2
export TESSER_RESULTS=$HOME/Dropbox/work/tesser/results
jupyter lab &

In Jupyter lab, load a notebook (in tesser/jupyter) and make sure the tesser kernel is selected.

Running neural analysis scripts

Running neural analysis scripts requires additional dependencies. If you have mpi (required for brainiak) installed, you should be able to just run:

pip install -e .[neural]

If you have problems installing brainiak or mpi4py, see the brainiak website for installation tips.

Reproducing analyses

See the analysis protocol for full instructions.

Authors

The modeling code was developed by Rodrigo Viveros Duran, Demetrius Manuel Hinojosa-Rowland, Neal W Morton, Athula Pudhiyidath, and Ida Momennejad. Code for behavioral and neural analysis was developed by Athula Pudhiyidath and Neal W Morton.