PsychoPy

PsychoPy is a free, open-source application for running psychology and neuroscience experiments. It’s written in Python and provides precise control over stimulus presentation timing, essential for behavioral research and human/animal experiments.

Why PsychoPy?

• Precise Timing: Millisecond-accurate stimulus presentation
• Flexible: Python scripting for complex designs
• Hardware Support: Interfaces with response boxes, eye trackers, EEG, fMRI
• Cross-Platform: Runs on Windows, macOS, and Linux
• GUI & Code: Use Builder interface or write Python scripts

Key Features

Stimulus Presentation

from psychopy import visual, core, event

# Create window
win = visual.Window(size=(800, 600), fullscr=False)

# Create stimuli
fixation = visual.TextStim(win, text='+')
image = visual.ImageStim(win, image='stimulus.png')

# Present sequence
fixation.draw()
win.flip()
core.wait(0.5)

image.draw()
win.flip()
core.wait(2.0)

Response Collection

from psychopy import event

# Wait for keyboard response
keys = event.waitKeys(keyList=['left', 'right', 'escape'])

# Get reaction time
rt_clock = core.Clock()
keys = event.waitKeys(keyList=['space'], timeStamped=rt_clock)

Experiment Flow

# Trial structure
for trial in range(n_trials):
    # Present stimulus
    stim.draw()
    win.flip()
    trial_clock.reset()

    # Collect response
    keys = event.waitKeys(
        keyList=['left', 'right'],
        timeStamped=trial_clock
    )

    # Save data
    data.append({
        'trial': trial,
        'response': keys[0][0],
        'rt': keys[0][1]
    })

Hardware Integration

# Parallel port for triggers
from psychopy import parallel
port = parallel.ParallelPort(address=0x0378)
port.setData(1)  # Send trigger

# Serial port for devices
from psychopy import serial
arduino = serial.Serial('COM3', baudrate=9600)

Builder Interface

PsychoPy Builder provides a graphical interface:

• Drag-and-drop components
• Visual timeline of experimental flow
• Generate Python code automatically
• Good for standard experimental designs

Coder Interface

For complex experiments, write Python directly:

• Full control over experiment logic
• Custom stimulus generation
• Advanced timing control
• Integration with data analysis

Common Experimental Paradigms

Visual Search

# Display array of items
# Record search time and accuracy

N-Back Task

# Present sequence of stimuli
# Detect matches N items back

Oddball Paradigm

# Standard and deviant stimuli
# For ERP studies

Reaction Time Tasks

# Measure speed of response to stimuli
# Simple or choice RT

Getting Started

Install PsychoPy:

# Standalone application (recommended for beginners)
# Download from psychopy.org

# Or install via pip
pip install psychopy

Simple experiment:

from psychopy import visual, core, event

# Setup
win = visual.Window()
msg = visual.TextStim(win, text='Press space to start')

# Welcome screen
msg.draw()
win.flip()
event.waitKeys(keyList=['space'])

# Run trial
stim = visual.TextStim(win, text='Stimulus')
stim.draw()
win.flip()
core.wait(1.0)

# Cleanup
win.close()
core.quit()

Best Practices

Timing

• Use win.flip() for frame-accurate timing
• Call win.flip() regularly to avoid dropped frames
• Test timing with photodiode
• Use StaticPeriod for non-drawing operations

Data Saving

• Save data incrementally (after each trial)
• Use structured formats (CSV, JSON)
• Include timestamps and metadata
• Back up data files

Stimulus Preparation

• Pre-load stimuli before experiment
• Use appropriate image formats
• Consider display refresh rate
• Test on actual experimental setup

Tips

• Always pilot experiments thoroughly
• Use logging module for debugging
• Test on the actual experimental computer
• Validate timing with external measurement
• Keep experiment scripts under version control
• Document experimental parameters clearly
• Use try/except to handle errors gracefully
• Include informed consent and debriefing screens