Predictive Analysis of the Principal Components that Configure Autistic Spectrum Disorder

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. 当前，针对孤独症谱系障碍（Autism Spectrum Disorder, ASD）的研究进展已使其诊断范畴被界定为一类多维度神经发育障碍，其特征为感知认知参数的过程性功能异常，该异常源于内在信息与情境刺激间互联通路的典型连接模式。在这一典型过程中，神经元网络承担着工作记忆的核心加工任务，以确保执行功能集合能够在一定程度上稳定运行——而这一稳定性在该障碍的确诊患者中受到严重损害。本研究对403名确诊该障碍的参与者的报告数据进行了分析，核心研究目标包括：1）分析关系性缺损与语义内容构建之间的关联；2）剖析导致上述连接受限的γ-氨基丁酸能通路（GABAergic pathway）的病因学归因；3）归纳该障碍的核心预测-解释层级。本研究通过多种统计检验方法完成数据分析，涵盖初始相关检验、统计计算流程、单变量单因素方差分析（one-way ANOVA）以及最终的有序多分类logistic回归检验。分析结果显示，用于解释该障碍的模型拟合信息对应的回归方程，其最终对数回归模型的卡方值为217.23，且具有显著的临界显著性水平（显著性P值：0.00）；此外，与对数回归层级显著相关的皮尔逊相关系数与偏差统计量数据同样呈现显著正相关（显著性P值：0.00），这证实了源自γ-氨基丁酸能通路受限的神经元与语义变量的预测-解释层级的重要性，可将其转化为作为高度相关神经认知系统过程的孤独症的核心命题成分。