Background:
The spectrum of autism encompasses High Functioning Autism (HFA)
and Low Functioning Autism (LFA). Brain mapping studies have revealed that autism individuals
have overlaps in brain behavioural characteristics. Generally, high functioning individuals are
known to exhibit higher intelligence and better language processing abilities. However, specific
mechanisms associated with their functional capabilities are still under research.
Objective:
This work addresses the overlapping phenomenon present in autism spectrum through
functional connectivity patterns along with brain connectivity parameters and distinguishes the
classes using deep belief networks.
Methods:
The task-based functional Magnetic Resonance Images (fMRI) of both high and low
functioning autistic groups were acquired from ABIDE database, for 58 low functioning against
43 high functioning individuals while they were involved in a defined language processing task.
The language processing regions of the brain, along with Default Mode Network (DMN) have
been considered for the analysis. The functional connectivity maps have been plotted through
graph theory procedures. Brain connectivity parameters such as Granger Causality (GC) and
Phase Slope Index (PSI) have been calculated for the individual groups. These parameters have
been fed to Deep Belief Networks (DBN) to classify the subjects under consideration as either
LFA or HFA.
Results:
Results showed increased functional connectivity in high functioning subjects. It was
found that the additional interaction of the Primary Auditory Cortex lying in the temporal lobe,
with other regions of interest complimented their enhanced connectivity. Results were validated
using DBN measuring the classification accuracy of 85.85% for high functioning and 81.71% for
the low functioning group.
Conclusion:
Since it is known that autism involves enhanced, but imbalanced components of intelligence,
the reason behind the supremacy of high functioning group in language processing and
region responsible for enhanced connectivity has been recognized. Therefore, this work that suggests
the effect of Primary Auditory Cortex in characterizing the dominance of language processing
in high functioning young adults seems to be highly significant in discriminating different
groups in autism spectrum.
Nonlinear modeling of the polymer Membrane Fuel Cells using Deep Belief Networks and Modified Water Strider Algorithm
