Action Video Games Improve Multisensory Perceptual Noise Exclusion in Children with Dyslexia

Introduction Developmental dyslexia (DD) is not only characterized by a reading difficulty, but also by phonological (Snowling et al., 2019), motor (Iversen et al., 2005) and visual attention deficits (Vidyasagar & Pammer, 2010). Some studies have argued the crucial role played by altered auditory and visual mechanisms of perceptual noise exclusion in DD (Hancock et al., 2017; Sperling et al. 2005). Method To test the causal role of perceptual noise exclusion in reading abilities, we proposed two different training with action and non-action video games (AVG and NAVG) to a group of 14 children with DD (aged 7 to 11 years, mean = 8,8 years) using a randomized, controlled crossover experiment. Reading and phonological decoding skills as well as auditory and visual perceptual noise exclusion efficiency were measured before and after AVG and NAVG training sessions. Results Our findings show that phonological decoding skills (i.e., pseudoword reading speed) as well as multisensory (auditory and visual) perceptual noise exclusion efficiency were significantly improved only after the AVG training session. Conclusion This study supports the conclusion that a disorder of the multisensory perceptual noise exclusion mechanism is causally linked to the reading deficits that characterize DD. Indeed, a training that enhances the efficiency of this attentional mechanism appears to improve phonological decoding skills in children with DD. Aspects of Novelty in Research This research is consistent with some previous studies that have shown that AVG training appears to improve, not only visual selective attention, but also auditory and phonological processing in healthy adults (Green & Bavelier, 2019, Mancarella et al., under review) and in children with DD (Franceschini et al., 2013; 2017; Franceschini & Bertoni, 2019;). In this study we directly investigated the causal role of multisensory mechanisms of perceptual noise exclusion in children with DD by using AVG training.