MedRead Journal of Addiction Science

Focus on Addictions and Mental Health Problems

Modeling and Simulation of Mental Disorders: Autism

T.R.S. Moura
Faculty Of Physics, Federal University Of Pará, Brazil

Published on: 2020-03-10

Abstract

The absence of biomarkers handicaps an early diagnosis of children with autism spectrum disorders (ASD) difficult. The routine procedures in newborns are ineffective for detecting autism. In the early, postnatal years, social interaction difficulties and other emerging factors are used for the assessment of children with ASD (autism spectrum disorders). We reported numerical results that analyze the social interaction and repetitive behavior of children with ASD and without ASD (autism spectrum disorders). To represent the interaction, by analogy, we used two sets of random walkers. These sets are labeled in two ways, one group, let‘s say, the first set of random walkers represents children with autism as Patient (P), characterized by persistent and change-resistant microscopic dynamics. 

Keywords

Autism, Random walks, Non-Markovian processes, Diagnosis, Entropy.

Introduction

The developmental disorders are classified into two subtypes: specific di- sorder and invasive disorder. Developmental delays in one or more specific areas is a feature of specific developmental disorder. The other subtype, invasive disorder, has deficiencies in basic functions in multiple contexts including socialization and communication. The Invasive Developmental Disorders (PDD) are part of the Autism Spectrum Disorders (ASD) group, known as neurodevelopmental disorder. The symptoms that accompany individuals with ASD (autism spectrum disorders) are delayed verbal and nonverbal communication; resistance to routine change; restricted and persistent interests in relation to an activity, topic, object, speech, idiosyncratic phrases, etc.; abnormalities in eye contact and body expression; difficulties in initiating and maintaining social relations. Each of these symptoms may range from mild, moderate or severe and are part of the diagnostic criteria for autistic spectrum disorders used in routine examinations[1-3]. Inspired by these symptoms and the diagnostic criteria of ASD (autism spectrum disorders), we built a model using discrete random walking as a diagnostic tool for autism. Our starting point is to define a model to compare with autistic behavior. The model we have chosen as a standard of comparison is the Elephant Random Walks model (ERW).

The ERW presents pertinent characteristics to be chosen as a standard model: its diffusive regimes are well known, the model is accurate and several variations have been proposed aiming to explore distinct memory search mechanisms, information loss and its impact on the diffusive process, among other features [4-7]. More details can be found in [8-15].