No Description

Andrey Sobolev cbd7b0a698 merged that shit 2 years ago
assets a87cb42fd4 added water stream wav files to assets 2 years ago
controllers 8ceb05744f fixed HD angle computation in position controller 2 years ago
profiles 8ceb05744f fixed HD angle computation in position controller 2 years ago
sandbox 2b5b4399d9 small fixes + MOG2 sandbox added 3 years ago
.gitignore a40e3e9d9f moved settings to profiles 3 years ago
LICENSE 8031b2dffc added license file and authors to the authors list 4 years ago
README.md 8031b2dffc added license file and authors to the authors list 4 years ago
SIT.ipynb cbd7b0a698 merged that shit 2 years ago
postrack.ipynb 049409909c updates to the hippoSIT - added unaudible trials 3 years ago
requirements.txt 6ae89c1673 refactored postprocessing in a separate notebook 3 years ago

README.md

Sensory Island Task (SIT)

The project provides several Jupyter notebooks for the behavioral testing of animals in open-field-based sensory perception experiments, the Sensory Island Task, as described in Ferreiro et al. 2020 (doi:XYZ TODO) and the pre-processing of the output data for subsequent analysis in MATLAB.

Installation

This project was developed and tested on different Windows (Win7 and Win10) machines. We recommend using Anaconda to run the project notebooks.

To install Anaconda, download the Anaconda installer with Python 3 (tested with Anaconda3-2019.10, bundled with Python 3.7) and follow the instructions on the download page.

After installation, we recommend creating an Anaconda environment from which Jupyter Notebook will be started to run the provided notebooks. You can create new environments using Anaconda's navigator or from an Anaconda prompt using:

conda create --name myenv

Once created, activate the environment and make sure it has both, Python 3 and R installed. Usually, you will also have to install an R-Kernel for Jupyter Notebook. To do so, open an Anaconda promt and go to the environment you created:

activate myenv

Once the environment has been activated, install R, its essentials, and the kernel via:

conda install r-base
conda install r-essentials 
conda install -c r r-irkernel

Finally, for the notebooks to run, you will have to install additional python modules and R libraries and their dependencies to your environment. Notebooks may not run smoothly, if the wrong versions of the modules are installed. Especially having the wrong versions of openCV can cause trouble, which is why we provide the Jupyter notebooks that run on Python 3 for two different versions of openCV (3.4.2 & 4.0.1). The code below will install the latest version of the modules/libraries to your environment. Version numbers in brackets are the latest module/library versions the notebooks were tested with (5th of Febuary, 2020).

Python modules: numpy (1.18.1), openCV (3.4.2 or 4.0.1), tkinter (8.6.8), scipy (1.3.2), sounddevice (0.3.14), pyfirmata (1.1.0)

conda install numpy
conda install opencv
conda install tk
conda install scipy
conda install -c conda-forge python-sounddevice
conda install -c conda-forge pyfirmata

R libraries: R.matlab (3.6.2), xlsx (0.6.1)

conda install -c r r-R.matlab
conda install -c r r-xlsx

Once you have installed the modules and libraries, run Juypter Notebook from your environment

jupyter notebook

To work with the different notebooks, select the folder to which you downloaded the files of this repository in the Jupyter browser and follow the instruction provided in the respective notebook.

Authors

  • Daniel Schmidtke
  • Diana Amaro
  • Andrey Sobolev

License

This project is licensed under the MIT License (see the license file for details).

Acknowledgments