IOR_Reward is an experiment program for a study looking at how the attentional phenomenon of "inhibition of return" (IOR) interacts with attentional biases to colours that result from reward learning within a bandit task.
IOR_Reward is programmed in Python 2.7 using the KLibs framework. It has been developed and tested on macOS (10.9 through 10.13), but should also work with minimal hassle on computers running Ubuntu or Debian Linux. It is not currently compatible with any version of Windows, nor will it run under the Windows Subsystem for Linux.
The experiment is designed to be run with an EyeLink eye tracker, but it can be downloaded and tested without one (using the mouse cursor as a stand-in for gaze position) by adding the flag -ELx to the klibs run command.
This experiment also requires a microphone to function, as it makes use of vocal responses.
First, you will need to install the KLibs framework by following the instructions here.
Then, you can then download and install the experiment program with the following commands (replacing ~/Downloads with the path to the folder where you would like to put the program folder):
cd ~/Downloads
git clone https://github.com/TheKleinLab/IOR_Reward.git
IOR_Reward is a KLibs experiment, meaning that it is run using the klibs command at the terminal (running the 'experiment.py' file using python directly will not work).
To run the experiment, navigate to the IOR_Reward folder in Terminal and run klibs run [screensize],
replacing [screensize] with the diagonal size of your display in inches (e.g. klibs run 24 for a 24-inch monitor). If you just want to test the program out for yourself and skip demographics collection, you can add the -d flag to the end of the command to launch the experiment in development mode.
By default, the experiment warns participants that they made the wrong response type if they make a vocal response on a bandit trial. However, on some computers with sensitive microphones (e.g. laptops), the noise from pressing a key can accidentally set this off, resulting in false positives.
If you encounter this problem, you can disable this warning by opening the experiment's parameters file (ExpAssets/Config/IOR_Reward_params.py) and change the value of the variable ignore_vocal_for_bandits from 'False' to 'True'.