2025/05/29 by Yuval Samoilov-Kats, Matan Ben Noach, Samoilov-Kats, Yuval +6
Psychology · #Digital Mental Health Interventions #Emotion and Mood Recognition #FOS: Biological sciences #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Mental Health Research Topics #Neurons and Cognition (q-bio.NC) #Software Engineering (cs.SE)
paper · pdf · doi:10.48550/arxiv.2505.23137
openalex publication_date 2025/05/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.