An open-source Modular Online Psychophysics Platform (MOPP)

TL;DR

MOPP is an open-source, web-based platform that simplifies online psychophysics experiments, enabling researchers to easily build, share, and run experiments with calibration and participant verification, producing lab-like data remotely.

Contribution

This paper introduces MOPP, a modular, open-source online platform that addresses key challenges in conducting psychophysics research remotely.

Findings

Pilot data matched laboratory results

Platform enabled large-scale online data collection

Built-in calibration and participant verification features

Abstract

In recent years, there is a growing need and opportunity to use online platforms for psychophysics research. Online experiments make it possible to evaluate large and diverse populations remotely and quickly, complementing laboratory-based research. However, developing and running online psychophysics experiments poses several challenges: i) a high barrier-to-entry for researchers who often need to learn complex code-based platforms, ii) an uncontrolled experimental environment, and iii) questionable credibility of the participants. Here, we introduce an open-source Modular Online Psychophysics Platform (MOPP) to address these challenges. Through the simple web-based interface of MOPP, researchers can build modular experiments, share them with others, and copy or modify tasks from each others environments. MOPP provides built-in features to calibrate for viewing distance and to measure visual acuity. It also includes email-based and IP-based authentication, and reCAPTCHA verification. We developed five example psychophysics tasks, that come preloaded in the environment, and ran a pilot experiment which was hosted on the AWS (Amazon Web Services) cloud. Pilot data collected for these tasks yielded similar results to those reported in laboratory settings. MOPP can thus help researchers collect large psychophysics datasets online, with reduced turnaround time, and in a standardized manner.