Predictive Analysis of the Principal Components that Configure Autistic Spectrum Disorder

Abstract

At currently, developments regarding to autism spectrum disorder have enabled its diagnostic group to be defined as a multilateral neurodevelopmental disorder characterised by peculiarities in the procedural functioning of perceptual-cognitive parameters, derived from a characteristic connexional form in the pathway of interconnection between intrinsic information and contextual stimuli. In this characteristic process, neuronal networks are involved a fundamental processing task for working memory to be able to perform the set of executive functions with a certain degree of stability, which is severely limited in people diagnosed with this disorder. In this study, the reports of 403 participants diagnosed with the disorder were analysed with the following basic goals: 1) to analyse the relationship between relational deficits and the elaboration of semantic content, 2) to analyse the etiological attribution of the GABAergic pathway responsible for the limitations in these connections and, consequently, 3) to conclude the main predictive-explanatory level of this disorder. The data have been found by means of different statistical tests, both initial correlational tests, statistical calculation processes, univariate one-factor ANOVA tests and final consequential ordinal multinomial logit regression tests. Data found allow us to delimit that the regression equation of the model fitting information explaining the disorder shows a final logit model chi-square: 217.23, with a significant associated critical level (sig: .00), which are complemented by the significantly positive Pearson and Deviance data significantly related to the logit level (sig: .00), which confirms the importance of the predictive-explicative level of the neuronal and semantic variables derived from the GABAergic limitations in order to be able to be converted into the main propositional components of autism as a highly related neurocognitive systemic process.