This project presents the data accompanying the paper
Farzaneh Najafi, Gamaleldin F Elsayed, Robin Cao, Eftychios Pnevmatikakis, Peter E Latham, John Cunningham, Anne K Churchland. "Excitatory and inhibitory subnetworks are equally selective during decision-making and emerge simultaneously during learning" bioRxiv (2018): 354340.
https://doi.org/10.1101/354340
The original data are available from Cold Spring Harbor Laboratory: http://repository.cshl.edu/36980/
The data download instructions are for a Unix-family OS such as Linux or Mac OS with Python 3.7+ on the system path as python3
.
In the terminal window, git clone
$ git clone https://github.com/vathes/najafi-2018-nwb.git
$ cd najafi-2018-nwb
The following command will download the original data from CSHL (~70 GB).
$ mkdir data
$ python3 scripts/download.py
This may take several hours. If the download is interrupted, simply re-run download.py
and it will pick up where it left.
Verify that all 18 files have downloaded.
$ ls data
FN_dataSharing.tgz-aa FN_dataSharing.tgz-af FN_dataSharing.tgz-ak FN_dataSharing.tgz-ap
FN_dataSharing.tgz-ab FN_dataSharing.tgz-ag FN_dataSharing.tgz-al FN_dataSharing.tgz-aq
FN_dataSharing.tgz-ac FN_dataSharing.tgz-ah FN_dataSharing.tgz-am FN_dataSharing.tgz-ar
FN_dataSharing.tgz-ad FN_dataSharing.tgz-ai FN_dataSharing.tgz-an
FN_dataSharing.tgz-ae FN_dataSharing.tgz-aj FN_dataSharing.tgz-ao
Now unpack the tar files:
$ cat data/FN_dataSharing.tgz-a* | tar -C data -xzf -
Verify that the data have unpacked:
$ ls data/FN_dataSharing
bag-info.txt data manifest-sha256.txt tagmanifest-sha256.txt
bagit.txt manifest-md5.txt tagmanifest-md5.txt
$ ls data/FN_dataSharing/data
metaData metaData~ mouse1_fni16 mouse2_fni17 mouse3_fni18 mouse4_fni19
The FN_dataSharing
data directory includes a manifest.txt
file specifying all available data, and a data folder containing the .mat
files.
The following command will convert the dataset into the NWB 2.0 format (See https://neurodatawithoutborders.github.io/)
$ mkdir data/FN_dataSharing/nwb
$ python3 scripts/convert_to_nwb.py
The convert_to_nwb
uses the configuration file conversion_config.json
to specify the manifest file, the output file, and general data about the experiments.
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"
},
"output_dir" : "data/FN_dataSharing/nwb"
}
The converted NWB files will be saved in the output_dir
directory.
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 figures presented in this study (https://doi.org/10.1101/354340).