Table of Contents

Implementation

Goal: Learn that timing and synchronization are challenging, and run the first experimental procedure

Prepare for the lab

Materials

  1. Short lecture: Implementation
  2. Q&A Session:
    1. Why don't we want to always use the same order of stimuli?
    2. How does random sampling with replacement differ from that without replacement?
  3. Practice session:
    1. Today we will explore the Stroop Task – a classic experiment first published in 1935 by J. Ridley Stroop. For original paper, see: PDF or HTML.
    2. Download and install the PsychoPy on your laptop/PC. We will use it during this lab.
    3. Run the PsychoPy3, e.g., in Windows: Start → PsychoPy3 → PsychoPy3. Three windows will appear:
      • PsychoPy Builder – it is the GUI-based creator of experiments. No coding skills needed! It is our base for today.
      • PsychoPy Coder – if you do not prefer GUI tools, here you can create, edit and run PsychoPy experiments written in Python code
      • PsychoPy Experiment Runner – the log from experiments will be presented here
    4. Load the Stroop Task demo in Builder: Demos → Experiments → stroop
      • If you do not see the Experiments, you need to unpack the demos first: Demos → Unpack Demos… (select any directory; PsychoPy will create a subdirectory called PsychoPy3 Demos there)
    5. Now, you can see the PsychoPy builder with the experiment loaded:
      • The whole overview of the protocol is visible in Flow (at the bottom). There will be three parts in Stroop Task: instruct, trial repeated in loop, thanks.
      • Each block from the Flow is visible as a separate tab in Routines (on the Figure above you can see the instruct routine).
      • Finally, each line in the Routines depicts one Component.
    6. Explore the interface. Click on the flow's and routines' elements. Take a look at dialog windows that will pop-up. We will modify these values later - now, it's time for some exploration.
    7. Run the experiment:
      1. Just click the big green button with an arrow.
      2. Insert any values in the small window that will appear (these are important for real experiment; not for exercises like now):
      3. Take part in the experiment! [there will be 30 items to evaluate]
    8. Go to the directory with the stroop (PsychoPy3 Demos\Experiments\stroop\). data directory was created here - take a look! There are four files for each participant:
      • [date].csv contains the actual experiment results (i.e., the stimuli presentation log and the subject's responses) – it is the most important file!
      • [date].xlsx contains a summary of the experiment – it do not add information and is not important at all.
      • [date].psydat contains a great deal of information from experiment; it is not easy to open, but keep it as a backup (you can recreate a [date].csv file from this one if the original csv file will be lost)
      • [date].log contains execution log (the same log is presented in Experiment Runner window during the experiment) – it's a proper place to check whether the protocol was correctly executed and no errors occurred
    9. Open the [date].csv file in MS Excel/LibreOffice Calc/Google Sheets/any similar and perform the simple analysis of the Stroop Effect!
      1. Sort the data by congruent column. The first half of the table will have congruent=0 (incongruent, i.e., text and colour are different), and the second will have congruent=1 (text and colour are the same)
      2. Simply calculate the averages of resp.rt (response.reaction_time) for both halves of the table
      3. Have you observed the Stroop Effect on yourself?
    10. Now it is time to make changes to the experiment. Change the screen colour for the whole experiment (e.g., to black). Also, change the instructions font colour (e.g., to red).
    11. More important task: change the language of the colour names (you can also change the messages, but it is not required).
      • If English is not your first language, then translate the study to your first language! If English is your first language, change it to French (red = rogue, green = vert, blue = bleu).
      • Tip 1: there is a trialTypes.csv file in PsychoPy3 Demos\Experiments\stroop\ directory. You need to create a new copy called, e.g. trialTypes-french.csv with alternated contents (letterColor column specifies the actual colour of the text; it should be written down in English or as an RGB value)
      • Tip 2: click on the trials block in the Flow (in Builder) – Conditions field should be interesting for you
    12. Run the experiment one more time (now, with the new language). Analyse the data (as above). Have you observed the Stroop Effect now? Is it stronger or weaker than before?
    13. Now, examine the Reverse Stroop Effect. As you probably observed, the meaning of the word interfered with your ability to report the letter colour (i.e., Stroop Effect). But is there an equivalent effect in which the letter colour interferes with your ability to read? Stroop's original paper (linked at the beginning) suggested a lack of effect in this direction but he was running his study with paper ink and asking participants to call out the answers while he timed them on a stopwatch. Maybe with the somewhat more precise timing of modern computers we can reveal such an effect? Modify the protocol accordingly.
    14. Check also the extended version of Stroop Task. To do so, in Builder select: Demos → Experiments → stroopExtended. What was changed? How it was done in the Builder?
    15. Finally, if you want to see the Python code instead of GUI-based builder, you can simply select: Tools → Compile, and the whole code will be generated and opened in the Coder.
  4. Advanced session:
    1. Synchronisation of data streams is one of the most important concerns in psychophysiological research. We want to test how this works with a simple example: one stream of data will be provided by the stroop experiment (implemented above), and the other will be a random number generator simulating the EEG data stream.
    2. To begin with, read about Lab Streaming Layer (LSL). It is a library/system for streaming and syncing various data over local network (you can also synchronise the data on one machine, as we will do now).
    3. There are ready-to-use modules/applications/examples of LSL. Let's start with two of them:
      1. SendData.py is a simple Python program that generates random values and puts them in the LSL stream called BioSemi. Simply run this program. Note: it is based on pylsl library.
      2. App-LabRecorder is an application that records the data streams available in the local network. Simply run the LabRecorder. You should see exactly one stream, called BioSemi – it is provided by the SendData.py example.
    4. Now it's time to work on your own: add LSL handling to the procedure in PsychoPy.
      1. Note 1: You can use the SendData.py code as an inspiration.
      2. Note 2: The use of the LSL consists of two steps. At the beginning (once, before starting the procedure), the appropriate data stream must be prepared using the StreamInfo and StreamOutlet classes. Then, in the actual loop handling the stimuli, we send consecutive samples to the stream using the push_sample() function.
      3. As a result, the stream you created should appear in LabRecorder.
    5. Now just run the experiment and save all the streams for each subject in a separate file. And that's it. The LSL authors did all the hard work for us by preparing the appropriate system libraries that synchronise the clocks of various devices on the local network, and then preparing the application to dump the streams to a file.

Learn more!

Timing and synchronization

Frameworks for psychological experiments

PsychoPy