Modeling the connections of brain regions in children with autism using cellular neural networks and electroencephalography analysis

Askari, Elham; Setarehdan, Seyed Kamaledin; Sheikhani, Ali; Mohammadi, Mohammad Reza; Teshnehlab, Mohammad

doi:10.1016/j.artmed.2018.05.003

Cited by 18 publications

(12 citation statements)

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“…As is known to us, neural networks have tremendous application prospect in plenty of disciplines such as computer technology, biological engineering, artificial intelligence, and automatic control. [1][2][3][4][5][6][7][8][9][10] So the research on many dynamics of neural networks is a central issue in today's scientific community. Various methods are put up to study the dynamical nature of neural networks.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis on Hopf bifurcation of integer‐order and fractional‐order two‐neuron neural networks with delay

Aouiti

2020

Circuit Theory & Apps

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Summary This article mainly focuses on the stability and the existence of Hopf bifurcation of integer‐order and fractional‐order two‐neuron neural networks with delay. First of all, we obtain the sufficient criterion to ensure the stability and the existence of Hopf bifurcation of integer‐order two‐neuron neural networks with delay. Next, we establish the sufficient condition guaranteeing the stability and the existence of Hopf bifurcation of fractional‐order two‐neuron neural networks with delay. The study reveals that the time delay has a vital effect on the stability and Hopf bifurcation of integer‐order and fractional‐order two‐neuron neural networks with delay. By comparative analysis on Hopf bifurcation for integer‐order and fractional‐order two‐neuron neural networks with delay, we find that under an appropriate parameter conditions, the stability region can be enlarged, and the time of appearance of Hopf bifurcation of the involved two‐neuron neural networks can be postponed by using fractional‐order case. Finally, computer simulation results are presented to illustrate the theoretical findings. The established results of this article play an important role in designing and controlling networks.

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Section: Introductionmentioning

confidence: 99%

Comparative analysis on Hopf bifurcation of integer‐order and fractional‐order two‐neuron neural networks with delay

Aouiti

2020

Circuit Theory & Apps

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“…При этом клинические проявления заболевания отражают сформировавшиеся атипичные функциональные связи [8]. Большинство аномалий у детей с аутизмом связаны с функционированием лобных и височных долей мозга [10].…”

Section: резюме _____________________________________________________...unclassified

Dynamics of Neuropsychological Indicators of Block II Brain Functions Development in Autistic Children

Гуткевич¹,

Пустовая²

2023

Психиатрия, Психотерапия И Клиническая Психология

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Цель. Изучение изменений нейропсихологических показателей функций приема, переработки и хранения информации у детей с аутизмом в процессе проведения с ними психокоррекционных занятий. Материалы и методы. В исследовании приняли участие 48 детей с аутистическими расстройствами. Дети на протяжении 5 лет с периодичностью 1 раз в год выполняли диагностические пробы. Возраст детей в начале проведения исследования составил (5,75±2,61) года, в конце проведения исследования – (10,99±2,74) года. Для оценки дефицитарности (несформированности) функций II блока мозга были использованы методы нейропсихологической диагностики для детей дошкольного и школьного возраста. Результаты. Для детей с аутизмом наибольшая положительная динамика отмечается в таких областях, как зрительный гнозис ((1,91±0,45) балла), понимание обращенной речи ((1,82±0,43) балла) и понимание номинаций речи ((1,72±0,64) балла), показ частей тела ((1,98±0,55) балла). Наиболее проблемными областями являются понимание логико-грамматических конструкций ((0,97±0,53) балла), просодика ((1,01±0,48) балла), спонтанная речь ((1,03±0,73) балла), слухоречевая ((1,00±0,69) балла) и зрительная память ((1,04±1,06) балла). Заключение. Изучение изменения нейропсихологических особенностей функций II блока мозга у детей с аутизмом позволило выделить области, в которых отмечается наиболее и наименее выраженная динамика показателей. Purpose. Study of changes in neuropsychological indicators of functions of receiving, processing and storing information in autistic children in the course of their psychological correction sessions. Materials and methods. The study involved 48 children with autistic disorders, the children performed diagnostic tests once a year for five years. The age of children at the beginning of the study was (5.75 ± 2.61) years, at the end of the study – (10.99 ± 2.74) years. Methods of neuropsychological diagnostics for preschool and school-age children were used to assess the deficiency (lack of formation) of the brain block II functions. Results. For children with autism, the greatest positive dynamics was observed in such areas as visual gnosis ((1.91 ± 0.45) points), understanding of reversed speech ((1.82 ± 0.43) points) and understanding of speech nominations ((1.72 ± 0.64) points), showing body parts ((1.98 ± 0.55) points). The most problematic areas were logical and grammatical constructions understanding ((0.97 ± 0.53) points), prosodics ((1.01 ± 0.48) points), spontaneous speech ((1.03 ± 0.73) points), auditory speech ((1.00 ± 0.69) points) and visual memory ((1.04 ± 1.06) points). Conclusion. The study of changes in neuropsychological features of the brain block II functions in children with autism allowed identifying areas in which the most and least pronounced dynamics of indicators were observed.

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“…The main advantages of this paradigm are robustness, high-speed, and parallel computing. Thus, it has been used in many applications related to image processing, data encryption, and forecasting problems [1]- [7]. Image processing applications could be implemented effectively on CeNN platform because of its robust architecture and high-performance [1], [4], [8]- [11].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, it has been used in many applications related to image processing, data encryption, and forecasting problems [1]- [7]. Image processing applications could be implemented effectively on CeNN platform because of its robust architecture and high-performance [1], [4], [8]- [11]. One limitation of this platform is the challenge in building both of the cloning and feedback templates.…”

Section: Introductionmentioning

confidence: 99%

Cellular Neural Networks Templates Learning Approach Based on Mutual Information and Firefly Algorithm for X-Ray Images de-noising

Sharaf,

E. Abu El-Soud,

M. El-Henawy

2019

Mansoura Journal for Computer and Information Sciences

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The Cellular Neural Network is a 2D array of analog processors which forms a parallel computing framework. The main key factors in this model are the values of the neighborhood of each cell, which are called templates. These templates are usually set by a domain expert in this framework to determine the optimal values of the templates. In this paper, a novel approach was proposed to discover the templates of the cellular neural networks based on mutual information and firefly optimization. The mutual information discovers the hidden pattern in the templates by measuring the similarities among cells. The firefly algorithm navigates the search space to find the optimal values of the templates. The benchmarking and validation have been performed on the ChestX-ray8, which is a real-world X-ray images dataset. The proposed method achieved significant results when compared to other meta-heuristics algorithms such as Genetic Algorithm and Particle Swarm Optimization.

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Modeling the connections of brain regions in children with autism using cellular neural networks and electroencephalography analysis

Cited by 18 publications

References 39 publications

Comparative analysis on Hopf bifurcation of integer‐order and fractional‐order two‐neuron neural networks with delay

Comparative analysis on Hopf bifurcation of integer‐order and fractional‐order two‐neuron neural networks with delay

Dynamics of Neuropsychological Indicators of Block II Brain Functions Development in Autistic Children

Cellular Neural Networks Templates Learning Approach Based on Mutual Information and Firefly Algorithm for X-Ray Images de-noising

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