Changes in EEG complexity with neurofeedback and multi-sensory learning in children with dyslexia: A multiscale entropy analysis.

Multiscale entropy analysis (MSE) is a novel entropy-based approach for measuring dynamical complexity in physiological systems over a range of temporal scales. MSE has been successfully applied in the literature when measuring autism traits, Alzheimer's, and schizophrenia. However, until now, there has been no research on MSE applied to children with dyslexia. In this study, we have applied MSE analysis to the EEG data of an experimental group consisting of children with dyslexia as well as a control group consisting of typically developing children and compared the results. The experimental group comprised 16 participants with dyslexia who visited Ankara University Medical Faculty Child Neurology Department, and the control group comprised 20 age-matched typically developing children with no reading or writing problems. MSE was calculated for one continuous 60-s epoch for each experimental and control group's EEG session data. The experimental group showed significantly lower complexity at the lowest temporal scale and the medium temporal scales than the typically developing group. Moreover, the experimental group received 60 neurofeedback and multi-sensory learning sessions, each lasting 30 min, with Auto Train Brain. Post-treatment, the experimental group's lower complexity increased to the typically developing group's levels at lower and medium temporal scales in all channels.

A mobile app that uses neurofeedback and multi-sensory learning methods improves reading abilities in dyslexia: A pilot study.

Reading comprehension is difficult to improve for children with dyslexia because of the continuing demands of orthographic decoding in combination with limited working memory capacity. Children with dyslexia get special education that improves spelling, phonemic and vocabulary awareness, however the latest research indicated that special education does not improve reading comprehension. With the aim of improving reading comprehension, reading speed and all other reading abilities of children with dyslexia, Auto Train Brain that is a novel mobile app using neurofeedback and multi-sensory learning methods was developed. With a clinical study, we wanted to demonstrate the effectiveness of Auto Train Brain on reading abilities. We compared the cognitive improvements obtained with Auto Train Brain with the improvements obtained with special dyslexia training. Auto Train Brain was applied to 16 children with dyslexia 60 times for 30 minutes. The control group consisted of 14 children with dyslexia who did not have remedial training with Auto Train Brain, but who did continue special education. The TILLS test was applied to both the experimental and the control group at the beginning of the experiment and after a 6-month duration from the first TILLS test. Comparison of the pre- and post- TILLS test results indicated that applying neurofeedback and multi-sensory learning method improved reading comprehension of the experimental group more than that of the control group statistically significantly. Both Auto Train Brain and special education improved phonemic awareness and nonword spelling.