Adaptive and Interactive Design Based on Big Data Computational Model for Treating Autism

We propose an affordable and adaptive computer interaction design to treat autism, where the progress monitoring can eliminate the danger of addiction. The suggested plan is based on the concept of the Big Data computational model that selects only a small part of information to operate explicitly while the rest of information contributes to this selection just implicitly. Understanding the information-processing model of the brain is vital in order to treat mental disorders such as autism. Evolutionary biology asserts that the unconsciousness is vital for the functionality of the brain. The human brain consists of billions of neurons and trillions of synapses. Its active memory is just 1 gigabit (Fig. 1). Yet, it is able to processes and retrieve information faster than a computer. Given the small active memory but efficient processing, we hypothesize that the brain´s information processing is influenced by the unconsciousness or background information. Mental disorders occur due to distortions in this background information. Fundamental distortions are (Fig. 2): (1) presence of excessive and unwanted information in the background, and (2) absence of vital information. Depression is an example for the first (e.g. traumatic events stored in background). Autism is an example of the later. Our suggested approach (Fig. 3) will have an Oracle machine -- a qualified psychiatrist or supervisor computer program -- will provide specific suggestions to the individual based on their type of mental disorder and supervise their selections. The Oracle machine will show individual the ideal choice in case they have selected a wrong choice. Given the information- processing model of the brain, these suggested selections and ideal choices among the selections would presumably affect the unconsciousness of the brain thus inserting new information in the contextual background of the brain. After a certain period of time, we may expect to see the improvements in the behavior of the - ndividual with autism.