Fractal characterization of stochastic series fluctuations of children with reading disorders

Reading is an emerging process from human brain activity. This process sometimes is subject to disorders which has been studied from the performance of studies that provide data that are treated with qualitative and quantitative linear tools to obtain the average behavior determined and the causality of it. This research focuses on the nonlinear quantitative study of reading disorder and in this way fractal geometry and roughness interface growth theory approach were selected to be used in the processing of brain wave quantification (EEG). From the EEG of children with and without reading disorders in the State of Mexico (experimental and control group) were built time series of standard deviation for each of the 19 channels distributed in cerebral cortex. The self-affinity of these time series (treated as interfaces in motion) is studied by the scaling behavior of their structure functions ∝, with as the roughness or local exponent, and ∝, with b as the fluctuation growth exponent. It was found that the behavior of the time series of children with reading problems (experimental group) and without them (control group) is similar to the Family-Vicsek scaling dynamic for a kinetic roughening of moving interface.