najafi-2018-nwb

This project presents the data accompanying the paper

Najafi, Farzaneh, Gamaleldin F. Elsayed, Eftychios Pnevmatikakis, John Cunningham, and Anne K. Churchland. "Inhibitory and excitatory populations in parietal cortex are equally selective for decision outcome in both novices and experts." bioRxiv (2018): 354340.

https://www.biorxiv.org/content/early/2018/10/10/354340

The original data are available from Cold Spring Harbor Laboratory: http://repository.cshl.edu/36980/

Conversion to NWB 2.0 file

This repository will contain the Python 3+ code to convert the dataset into the NWB 2.0 format (See https://nwb.org)

To start, download the dataset from http://repository.cshl.edu/36980/, follow the instruction to concatenate and extract data. The resulted data directory includes a manifest.txt file specifying all available data, and a data folder containing the ".mat" files

The conversion to NWB 2.0 format is done via the NWB_conversion.py script. This script takes one argument, a .json config file, specifying the manifest file, output directory, and some metadata.

An example content of the .json config file is as follow:

{
	"manifest": "data/manifest-md5.txt",
	"general": 
		{
			"experimenter" : "Farzaneh Najafi",
			"institution" : "Cold Spring Harbor Laboratory",
			"related_publications" : "https://doi.org/10.1101/354340"
		},
	"error_log" : "data/conversion_error_log.txt",
	"output_dir" : "data/NWB 2.0"
}

The converted NWB 2.0 files will be saved in the output_dir directory specified in the .json file. Running the conversion script is as follow:

python NWB_conversion conversion_config.json

Showcase work with NWB:N files

This repository will contain Jupyter Notebook demonstrating how to navigate and query the dataset.

See this Jupyter Notebook for a tutorial on using PyNWB API to access NWB 2.0 data, to process and plot some of the key figures presented in this study (https://doi.org/10.1101/354340).