PLFest: A new platform for accessible, reproducible and open perceptual learning research

Abstract

In recent decades, perceptual learning (PL) has witnessed significant advancements, but the field has faced questions regarding reliability, replication issues, and challenges in understanding individual differences, hindering accessibility to diverse populations. To address these issues, we introduce PLFest, a novel, cross-platform UNITY-based app designed to promote accessible, reproducible, and open PL research. PLFest supports a variety of training and assessment procedures, focusing on psychophysics and PL of contrast sensitivity. It facilitates data collection on computers, tablets, and smartphones, enhancing accessibility and portability, making it ideal for large-scale, multi-site studies. PLFest aims to promote open science, data sharing, and reproducible research, fostering collaboration within the research community. As a first step, to validate PLFest, we conducted tests on healthy participants, assessing visual acuity and contrast sensitivity on both desktop and tablet setups. These measures were specifically chosen as they represent fundamental assessments of visual functions in healthy and clinical populations and are also known to be sensitive to display characteristics. The results demonstrated that PLFest produces reliable measurements, in particular on Apple iPad tablets, suggesting that the app is appropriate for visual psychophysics. This validation supports PLFest as a robust platform for PL research, emphasizing its potential to overcome limitations associated with high-end desktop/monitor setups and ensuring its applicability across diverse hardware configurations.