Using ANN to compute spike trains and position from electrophysiology. Usage :
./neuroEncoder <ann | bayes> <path> ...
"ann" mode extracts spikes from a .dat file, and creates a neural network graph from the spikes to the position. "bayes" mode loads units from .clu and .res files and use a bayesian decoder to get to the position. "decode" mode takes already existing graph from .json file to decode position of the animal from the new file. "compare" mode will plot the figures comparing results of bayesian decoder and neuroEncoders on the same file
The argument <path> specifies the path to the .xml of your dataset. The script assumes that the .dat is in the same folder as this .xml (and with the same name !). The position is taken from the variables AlignedXtsd and AlignedYtsd (in their absence - Xtsd and Ytsd) of the behavResources.mat file (in the same folder as the other files), unless the option -t or --target is used.
If you wish to decode something else than position, you can use the option --target <nameOfTsd> to specify the name of tsd object inside the behavResources.mat file. If specified, the data from this object will be used as target for the decoding. We get decoded features from Matlab files, which requires both Matlab installation and presense of Tsd package. Tsd package (originally written by Francesco Battaglia) will be distributed along with the main code because it is hard to find. One place to find it is here
The option --window <windowLength> allows you to specify the window size (in seconds). Default is 0.036 (s).
In "compare" mode, the script also uses data from a .fil file to get the spikes. If you don't have one of those, please create it by applying hipass filter on you .dat file (ndm_hipass command in Neuroscope suite)
If tensorflow is installed with gpu version, you can use the option --gpu so the script runs in gpu mode. The data isn't straightforward to load, so the gpu acceleration may not be great on a regular workstation.
The application is written in four languages: the main one is Python, the three auxiliary ones are Matlab, Julia and shell.
- Matlab was tested on versions from 2016 to 2019
- Shell part was only tested on Ubuntu computers <= 18.04
- Julia requires separate installation (make sure Julia interpreter is contained in the PATH)
- neuroEncoders was tested on 3.6 <= Python <= 3.8.8
Running the following command will install the CPU version of tensorflow (tested on Python >= 3.8)
sudo ./install.sh
To install GPU version, please install NVIDIA drivers, and compatible with your version of operating system, graphics card and tensorflow 2.4.1. More information here To test if installation was succesfull, please run
import tensorflow as tf
tf.test.is_gpu_available()