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Predicting nonverbal intelligence level from resting-state connectivity: a neural networks approachстатья
Информация о цитировании статьи получена из
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 17 августа 2021 г.
- Авторы: Ivanov S.A., Zakharov I.M., Feklicheva I.V., Ismatullina V.I., Chipeeva N.A., Alkapov R.R., Bessonov V.V., Buraya A.A., Starkov A.E., Malykh S.M.
- Журнал: Journal of Physics: Conference Series
- Номер: 1727
- Год издания: 2021
- Издательство: IOP Publishing
- Местоположение издательства: [Bristol, UK], England
- Номер статьи: 012010
- DOI: 10.1088/1742-6596/1727/1/012010
- Аннотация: This article is devoted to the development of a model of an artificial neural network for predicting the level of nonverbal intelligence according to the EEG of the brain. Cognitive functioning relies on the synchronization between different brain structures. However, it is still unclear how individual differences in intelligence are related to the global characteristics of information transmission in brain networks. Resting -state functional connectivity studies show the association of patterns of interactions between brain regions from people and different levels of nonverbal intelligence. In this study, we present a process of development of a neural network model used to predict the level of nonverbal intelligence based on EEG data of the brain. We have developed a fully-connected neural network to predict the level of nonverbal intelligence
- Добавил в систему: Малых Сергей Борисович