L.-H. Tan, S.-Y. Cho and Y.-Y. Nguwi
School of Business (IT), James Cook University, Singapore
ABSTRACT
Autism is a pervasive neuro-developmental disorder, primarily encompassing difficulties in the social,
language, and communicative domains. Because autism is a spectrum disorder, it affects each individual
differently and has varying degrees. There are three core aspects of impairment based upon the Diagnostic
and Statistical Manual of Mental Disorders (DSM-IV), namely impairment in socialization, impairment in
communication, and restricted repetitive activities or interests. This work describes the experiment aims at
expressing autistic traits through the use of self-organizing map. Works related to simulating autism
through self-organizing map is limited. This work compare and contrast the difference in attention index
for normal learning and marred attention shift learning ability. It was found that the attention index of
normal learning is 9 times better marred attention shift for both random and pre-fixed input data. In the
marred attention shift context, neurons adapt more towards the mean of both sources combined under
marred context while some neurons adapt towards mean of one source under normal context. The normal
learning ability produces maps with neurons orienting towards mean values of combined stimuli source.
Impairment in learning ability produces similar cortical maps compared to normal learning ability. The
major difference is in the attention index.
KEYWORDS
self-organizing map, attention shift, autism, neural network
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