PsychoPy

PsychoPy is a software package for creating experiments in the fields of neuroscience and experimental psychology. The software enables the generation of precise visual and auditory stimuli, the collection of participant responses, and the recording of temporal data. Its architecture is based on Python and uses graphical libraries to ensure precision in stimulus presentation and timing measurement.

★★★★★

5.0(1 ratings)

• Builder Interface. A graphical environment for designing experiments without needing to write code. It allows organizing trials via a timeline and adding stimulus and response components by dragging and dropping. The interface automatically generates an executable Python script.
• Coder Interface. An integrated code editor for developing experiments through Python programming. It includes syntax highlighting, autocompletion, and debugging tools. It provides full control over all experimental parameters and trial logic.
• Visual stimulus presentation. Ability to display geometric shapes, images, text, and Gabor patches. Precise control over parameters such as position, size, color, orientation, contrast, and presentation time. Support for high refresh rate monitors.
• Auditory stimulus generation. Functionality to play pure tones, noises, and external audio files. Control over parameters like frequency, volume, duration, and output channel. Precise temporal synchronization with other stimuli and response logs.
• Response collection. Mechanisms to capture inputs from keyboards, mice, gamepads, and specialized response devices. Recording of response latency with millisecond accuracy. Configuration of response periods and trial termination conditions.
• Experimental paradigm design. Tools to implement within-subject, between-subject, and mixed designs. Support for randomization, counterbalancing, and multiple experimental conditions. Creation of trial blocks with different parameters.
• Data logging and export. An automatic system to save data from each trial in CSV, JSON, or Excel formats. Recording of independent and dependent variables, presentation times, and participant responses. Data organization by session and participant.
• Temporal synchronization control. Mechanisms to ensure precision in stimulus presentation and response measurement. Compensation for monitor lag and calibration of the timing measurement system. Verification of hardware temporal performance.
• External hardware integration. Compatibility with devices such as eye-trackers, EEG systems, fMRI, and transcranial magnetic stimulation equipment. Connection via serial ports, Ethernet, or specific software interfaces. Synchronization of timestamps between systems.
• Questionnaire and scale creation. Components to implement Likert scales, multiple-choice questions, text fields, and visual analog scales. Response validation and navigation between items. Customization of question format and layout.
• Real-time data analysis. Functionalities to process responses and modify the experiment flow according to predefined criteria. Calculation of scores, thresholds, and performance parameters during execution. Adaptation of experimental parameters based on participant performance.
• Online execution. Ability to convert experiments to JavaScript format and run them in web browsers via the Pavlovia platform. Synchronization with servers for remote studies. Maintenance of temporal precision in web environments.
• Custom components library. A framework to develop and share specific experimental components. Creation of plugins that extend the base functionality of the software. Distribution of components via public or private repositories.
• Color and luminance calibration. Tools to measure and compensate for display characteristics. Creation of color profiles to ensure consistency in stimulus presentation across different systems. Gamma adjustment and linearization of video output.
• Integrated documentation and help. A reference system with detailed explanations of each component and function. Code examples and tutorials for different types of experimental paradigms. Guides for solving common technical problems.

The development of PsychoPy began in the year 2003. The main creator is Jonathan Peirce, a researcher in the field of experimental psychology. The program is written in the Python programming language, with components that use libraries such as wxPython for the graphical interface, OpenGL for graphical rendering, and NumPy for numerical calculations. The evolution of the software has included the incorporation of functionalities for cognitive neuroscience research and adaptation for online studies.

Alternatives to PsychoPy: