2026-05-30T05:23:06Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/244152026-02-03T12:18:12Zcom_10630_2254col_10630_37959

00925njm 22002777a 4500 dc Formoso, Marco A. author Ortiz-García, Andrés author Martínez-Murcia, Francisco Jesús author Aquino Brítez, Diego author Escobar, Juan José author Luque-Vilaseca, Juan Luis author 2022 The search for a dyslexia diagnosis based on exclusively objective methods is currently a challenging task. Usually, this disorder is analyzed by means of behavioral tests prone to errors due to their subjective nature; e.g. the subject’s mood while doing the test can affect the results. Understanding the brain processes involved is key to proportionate a correct analysis and avoid these types of problems. It is in this task, biomarkers like electroencephalograms can help to obtain an objective measurement of the brain behavior that can be used to perform several analyses and ultimately making a diagnosis, keeping the human interaction at minimum. In this work, we used recorded electroencephalograms of children with and without dyslexia while a sound stimulus is played. We aim to detect whether there are significant differences in adaptation when the same stimulus is applied at different times. Our results show that following this process, a machine learning pipeline can be built with AUC values up to 0.73. https://hdl.handle.net/10630/24415 Neuroplasticidad Dislexia Electroencefalografía Temporal phase synchrony disruption in dyslexia: anomaly patterns in auditory processing