Designing a model to detect the brain connections abnormalities in children with autism using 3D-cellular neural networks

Abstract

In neuropsychological disorders, the significant abnormalities in the brain connections in some regions are observed. This paper presents a novel model to demonstrate the connections between different regions in children with autism. The proposed model first conducts the wavelet decomposition of electroencephalography signals by wavelet transform then the features are extracted, such as relative energy and entropy. These features are fed to the 3D-cellular neural network model as inputs to indicate the brain connections. The results showed that there are significant differences and abnormalities in the left hemisphere, (p<0.05) at the electrodes AF3, F3, P7, T7 and O1 in alpha band, AF3, F7, T7 and O1 in beta band, T7 and P7 in gamma band for children with autism compared with the control children. Also, the evaluation of the obtained connections values between brain regions indicated that there are more abnormalities in the connectivity of frontal and parietal lobes and the relations of the neighboring regions in all three bands especially in gamma band for autistic children. Evaluation of the analysis demonstrated that alpha frequency band had the best distinction level of 96.6% based on the obtained values of the cellular neural network using support vector machine method.

Investigating EEG Patterns for Dual-Stimuli Induced Human Fear Emotional State

“…Commercial grade Emotiv EPOC EEG Headset was used for capturing brain signals during the experiments. It is a wireless headset that requires less placement time and effort and offers improved mobility and flexibility when compared with other medical grade EEG headsets [32,33,34,35,36]. The EEG signals were recorded with a sampling frequency of 256 Hz from the Emotiv EPOC headset with fourteen EEG channels, namely, AF3, AF4, F3, F4, FC5, FC6, F7, F8, T7, T8, P7, P8, O1, and O2, as shown in Figure 1.…”

The Acceptability, Feasibility, and Utility of Portable Electroencephalography to Study Resting-State Neurophysiology in Rural Communities

“…The EPOC device has been available for over a decade, and a recent review has examined its use in research studies ( Williams et al, 2020 ). This review found that while most studies using the EPOC headset have been conducted with adults, some groups have begun exploring its potential for use with children over the age of 5 years, including those with special needs such as Autism ( Askari et al, 2018 ) and Attention Deficit Hyperactivity Disorder (ADHD) ( Martínez et al, 2016 ; Mercado-Aguirre et al, 2019 ). The utility of this device to collect EEG data and extract a variety of metrics ranging from power across spectral frequency bands such as alpha, beta and gamma in resting-state eyes open condition ( Askari et al, 2018 ), as well as while children are engaged in a game targeting cognitive, attention and reasoning skills ( Martínez et al, 2016 ); and event-related potentials (ERPs) elicited in response to auditory stimuli ( Badcock et al, 2015 ; Mercado-Aguirre et al, 2019 ) has already been demonstrated.…”

New results on stability of periodic solution for CNNs with proportional delays and $D$ operator

“…The cellular neural networks(CNNs) was first requested back in 1988 by Chua and Yang [6], which is investigated in various fields of science and technology. The possibility of wide practical applications of CNNs explains the still growing interests of many researchers, the recent literatures on this subject which can be found in [3,13,14,23,[30][31][32][33]36]. Oscillation and instability of CNNs may be caused by the delay, the research of the dynamic properties for delayed neural network has been attracted broad attention by many authors, see e. g. [8,10,24,37,38].…”