Stimuli and Code
About this stimulus space: ------------------------- 1. Stimuli are numerically numbered as (VCS_stim), where stim refers to a degree on a 2D circle. 2. Changing these numbers are OK, as long as the relational structure of the shapes are maintained (e.g. VCS_1, VCS_2, and VCS_3 can be renamed to VCS_151, VCS_152, and VCS_153, but VCS_1, VCS_2, and VCS_3 should not renamed to VCS_150, VCS_4, VCS_6). ---------- About the code: ------------------- 1. **VCSspace.mat** contains example code to display these shapes on a 2D circle. 2. This script requires Psychtoolbox-3 to run, which is available here: http://psychtoolbox.org/ 3. Set the folder to path on MATLAB, then simply run in console. To close the script, press "q" while it is running. 4. To use this code in an experiment, one possible way is to run everything within a for loop, and index memory performance as the distance between a reported shape and a target shape. I'm happy to provide some example code that can do this. ![enter image description here] : https://files.osf.io/v1/resources/d9gyf/providers/osfstorage/5bb4d6d036cd3c0018040e67?mode=render ---------- Circularity simulations: ------------------------ For more detailed information, please see the section in the wiki titled "Circularity Simulations". All files must be in the same directory. 1. The **rand_c_value_sim** contains code to simulate how C behaves with stimuli projected into completely randomized coordinates in two dimensional space. 2. The **idealized_c_value_sim** contains code to simulate how C behaves, when starting with a perfect idealized circular space perturbed by noise along each coordinate in two dimensions. This code gives us a large distribution of possible C values at different geometries. 3. A **mds_pred.mat** file, which contains xy coordinates for an idealized circular space. Visualize after loading mds_pred.mat in MATLAB using the command: `plot([mds_pred(:,1);mds_pred(1,1)], [mds_pred(:,2);mds_pred(1,2)], '-x')` 4. The **visualize_c** file contains code to visualize simulated results at different C values. Run either **rand_c_value_stim** or **idealized_c_value_sim** first (simulations may take awhile if the `number_of_simulations` variable is a large number), then visualize with the **visualize_c** code.