Restrictive Repetitive Behaviors (RRBs) and sensory processing disorders are core symptoms of Autism Spectrum Disorder (ASD); their impact on patients’ quality of life warrants extensive literature studying them. However, although their correlation is known, the nature of the relationship between them still leaves some question marks. The aim of our study is to investigate the association between demographic and clinical variables and RRBs and sensory profile abnormalities, using Artificial Neural Networks (ANNs) in a sample of children with ADS. The Short Sensory Profile (SSP) and the Repetitive Behavior Scale-Revised (RBS-R) were administered to the children’s caregivers, and clinical and demographic data were collected.

ANNs are adaptive models inspired by the functioning processes of the human brain particularly adapted to solving non-linear problems. These systems have been widely used in the medical field, but not yet applied to the analysis of RRBs and sensory abnormalities in general, much less in children with ASD.
The application of ANNs to our dataset confirmed the well-known correlation existing between RBBs and sensory abnormalities; moreover interesting association between demographic/clinical variables and SSP and RBS-R subscales, previously emerged by classical statistical analysis, were confirmed and deepened.

The Low Energy subscale (SSP-VI) has proven to be the central hub of the system; interesting links emerged between the subscale Self-Injurious Behaviors and Intellectual Disability and between Sleep Disturbance and various RRBs. In conclusion, our study provides new insight into the relationship between RRBs and sensory abnormalities in children with ASD by applying ANNs for the first time in this area.

Notes:

- IRCCS Istituto delle Scienze Neurologiche di Bologna
- Alma Mater Studiorum, Università di Bologna
- Villa Santa Maria Foundation, Tavernerio, Como