Inhibition Of Return (IOR)

It is strongly recommend to first read the lesson about cueing.

The effect of slowing down when responding to previously cued locations is relatively small. It is a slowing down of around 20 ms compared to detecting relevant stimuli at positions that were not previously attended.

The best way to understand this phenomenon is to run an example. In the following example, you will see:

In this experiment, you will see the following happening.

There are various things that can be done differently in this experiment. First of all, the irrelevant distraction left or right can be implemented differently. Here it was a small x, but it can be anything, as long as you direct your attention there. Second, the relevant stimulus, the target can be anything, as long as you tell the participant how to respond.

The duration between cue and target is important. And so is the fact that the cue is irrelevant. The figure below is adapted from Figure 1b of Klein (2000) and shows the relationship between IOR and the cue-target duration (SOA = Stimulus Onset Asynchrony). What you see is that when the time between the cue and the target is very short (below 200 ms), people respond more quickly to cued than to uncued targets. But this changes when the SOA becomes longer (from 300 ms onward). The crossover point is where cueing changes from facilitating responses to inhibiting responses. This only happens when there are both valid and invalid cues. If all cues are valid, it does not happen (as was the case in the cueing lesson).

The following is only for advanced use, it is not necessary to understand the basic phenomenon. Analyzing your own data requires some extra skills. For those who would like to analyze the data, please download the zip file with the PsyToolkit experiment files and the R files.

You can analyze the produced data file using the R file analyze1.r

Next, you need to use the R file that comes with the downloaded files. It is called, analyze1.r. Before you run this file in R, you need to specify which experimental data file you want to analyze.

In cognitive psychology, we are primarily interested in processes that are common to most (if not all) people. The repeated measures design is commonly used to study different conditions in multiple people, whereby each person performs a number of conditions. The "repeated" refers to the fact that each participant performs the experiment in multiple conditions (sometimes, students confuse this; just the fact that you carry out multiple trials does not mean that the design is a "repeated measures design").

The following example is identical to the first study, except for the variation in the SOA. The example R file shows you how to plot a graph similar to the above one for your own data.