Publication:
The architecture of neural networks for enhanced autobiographical memory access: A functional MRI study

Дата
2020
Авторы
Zhigulina, P.
Malakhov, D.
Orlov, V.
Novikov, K.
Ushakov, V.
Kartashov, S.
Journal Title
Journal ISSN
Volume Title
Издатель
Научные группы
Организационные подразделения
Организационная единица
Институт интеллектуальных кибернетических систем
Цель ИИКС и стратегия развития - это подготовка кадров, способных противостоять современным угрозам и вызовам, обладающих знаниями и компетенциями в области кибернетики, информационной и финансовой безопасности для решения задач разработки базового программного обеспечения, повышения защищенности критически важных информационных систем и противодействия отмыванию денег, полученных преступным путем, и финансированию терроризма.
Выпуск журнала
Аннотация
© 2020 The Authors. Published by Elsevier B.V.The paper reports results of the first neuroimaging study of a peculiar phenomenon of autobiographical human memory (AM)- A state of enhanced memory access . The objective of this work was to determine the AM network and the AM gate, i.e. the brain structures responsible for access to the entire memory network. In the framework of the experiment, fMRI images of the volunteers' brains were obtained during normal and enhanced autobiographical memory retrieval, then pre-processing and processing of these data were performed, the areas involved in actualization of the AM on the individual and group levels were identified, after that the connections between these areas were exposed and visualized, and a meta-analysis of the data received at individual level were performed. The areas that were identified in the state of enhanced memory retrieval significantly overlap with the already known AM network, but activations were also detected in areas not mentioned earlier in the papers on AM. Also we report evidence, that achievement of the enhanced memory access has individual threshold for each subject.
Описание
Ключевые слова
Цитирование
The architecture of neural networks for enhanced autobiographical memory access: A functional MRI study / Zhigulina, P. [et al.] // Procedia Computer Science. - 2020. - 169. - P. 787-794. - 10.1016/j.procs.2020.02.164
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