When to use PsyNet?

PsyNet can be used for many kinds of psychology experiments. However there are certain applications to which PsyNet is particularly well suited.

Online experiments. PsyNet experiments run in the web browser and therefore can be used either for in-person or online data collection.

Experiments using large stimulus sets. PsyNet provides extensive support for managing stimulus sets, including useful hooks for generating stimuli in Python and hosting media assets on web servers.

Experiments whose state evolves over time. PsyNet makes it easy to implement certain kinds of experiments that are very difficult to implement in static platforms such as jsPsych and PsychoPy, for example cultural evolution or serial reproduction studies.

Experiments using recordings. Recording media from e.g. the webcam or the microphone is straightforward in PsyNet. The results can be processed in near real-time using custom Python functions and used to determine experiment logic (e.g. feedback).

Experiments using financial rewards. PsyNet integrates with crowdsourcing services (e.g. Prolific, Amazon Mechanical Turk) and can automate the dispensation of performance-related financial rewards, which is a great way to motivate good task performance.


Here are a few examples of research projects that have successfully used PsyNet since its inception in 2020. These projects were carried out by a variety of researchers based at institutions including the Max Planck Institute for Empirical Aesthetics, the University of Cambridge, City University of New York, Princeton University, and the University of Oxford.

Gibbs Sampling with People. This project developed a new adaptive technique for mapping semantic associations of a stimulus space. The procedure constructs a series of stimulus ‘chains’, where a stimulus is passed from one participant to the next, and each participant adjusts a particular stimulus dimension in order to maximise a particular subjective criterion (e.g. ‘beauty’). The project takes advantage of PsyNet’s support for experiments whose state evolves over time.

Consonance and timbre. This project explored ways in which the timbre of chord tones affects the consonance subjective pleasantness) of musical chords. PsyNet enabled the exploration of very large stimulus spaces, with each stimulus corresponding to a different combination of timbre and pitch intervals.

Large-scale tapping experiments. This project used PsyNet to conduct large-scale online studies where participants had to tap along to the beat of musical pieces. The paradigm used a newly constructed signal-processing pipeline that records participant tapping through the laptop microphone. Implementing this in PsyNet allowed participant performance to be monitored in real time, enabling live feedback and financial rewards for good performances.

Vocal pitch matching. This project investigated participants’ abilities to identify and sing back the notes in musical chords. This took advantage of PsyNet’s support for audio recording and online signal-processing.

Emotional connotations of musical scales. This project studied how different musical scales evoke different kinds of emotions within listeners. This took advantage of PsyNet’s support for large, programmatically generated stimulus sets.

Governance simulations. This project studied the success of different self-governance systems within a online social network. Participants experienced this network through a 3D video game programmed in the Unity game engine. This took advantage of PsyNet’s ability to orchestrate complex interactions between many participants.