Title: A hybrid approach for analysis of brain lateralisation in autistic children using graph theory techniques and deep belief networks

Authors: Vidhusha Srinivasan; N. Udayakumar; Hualou Liang; Kavitha Anandan

Addresses: Department of Information Technology, Centre for Healthcare Technologies, SSN College of Engineering, Chennai, Tamil Nadu 603110, India ' Department of Pediatrics, Sri Ramachandra Institute of Higher Education and Research, Sri Ramachandra Medical University, Chennai, India ' School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, USA ' Department of Biomedical Engineering, Centre for Healthcare Technologies, SSN College of Engineering, Chennai, Tamil Nadu 603110, India

Abstract: Lateralisation is the quality of a neural function specialised towards one hemisphere of the brain over the other for a specific activity. Autism individuals possess reduced language processing and impaired communication. This work analyses the lateralisation patterns present at the language regions of the brain for controls, low functioning (LFA) and high functioning autistic (HFA) individuals using resting state fMRI. Totally, 101 participants were considered for this study. The active and inactive regions in the left and right hemisphere, responsible for language processing have been analysed through graph theory. Results showed overall left hemisphere (LH) activation for controls while impaired LH activation for LFAs and unique right hemisphere (RH) activation for the HFAs. Using deep belief networks, the classification accuracy for lateralisation was measured. The accuracy was highest in LH for controls with 97.88% and LFA measuring 78.17% in LH while, the HFA group showed dominance at RH with 94.23%.

Keywords: autism; autism spectrum disorder; ASD; functional magnetic resonance imaging; fMRI; lateralisation; language processing in autism; high functioning autistic; HFA; graph theory; deep belief networks; DBNs.

DOI: 10.1504/IJBET.2022.123258

International Journal of Biomedical Engineering and Technology, 2022 Vol.39 No.1, pp.40 - 64

Received: 03 Jan 2019
Accepted: 04 Apr 2019
Published online: 07 Jun 2022 *

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