Abstract

The article provides an overview of scientific works devoted to methods of correcting the development of children with autism spectrum disorders (ASD) based on EEG biofeedback (neurofeedback). According to the World Health Organization, one in 160 children are currently diagnosed with ASD. In 2018, about 0.1 % of the child population in Russia suffered from autism. Moreover, the incidence of the disease is increasing every year. Genetic disorders are the most likely cause of ASD. Dysfunctions of 69 genes are highly likely to cause ASD. Most of these genes are pleiotropic. They affect the proliferation, differentiation and migration of nerve cells, the growth of axons and synaptogenesis, the synthesis of neurotransmitters and the development of receptors for them. Several genes involved in the development of ASD undergo epigenetic modifications under the influence of the environment and pathogens. The key in the onset of ASD is probably a violation of the synaptic pruning process. Pruning is necessary to reduce redundant connections and improve the efficiency of the central nervous system. Based on this, the researchers put forward a hypothesis explaining the symptoms of ASD as a result of a violation of structural and functional brain connectivity. Such disturbances are likely to cause abnormalities in the functioning of the brain mirror system (BMS). Disorders of the synaptic organization of the brain correlate with indicators of cognitive, emotional and behavioral tests, EEG characteristics. The study of phase coherence in several EEG frequency ranges demonstrated the presence of global hypo- and local hyper-connectivity in patients with ASD. The absence of suppression or desynchronization of the mu rhythm may indicate a malfunction of the BMS. The child’s brain is highly plastic. Therefore, early corrective intervention can improve the developmental outcomes of a child with ASD. Modern research demonstrates the possibility of effective application of neurofeedback for the correction of the disease. One of the strategies is the use of neurofeedback trainings to reduce anxiety in children with ASD. Another strategy is aimed at regulating the coherence of EEG signals. Researchers consider the most promising strategy for learning mu rhythm modulation using neurofeedback. This neurofeedback protocol affects the functioning of the BMS. According to the research results, after the neurofeedback trainings, the normalization of the functional cerebral connectivity according to the mu rhythm was established. Further research in this direction can become the basis for the most effective methods of treating ASD.

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