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Fractal Dimention EEG Dinamics in Solving Task Recognition of Bar Plots. / Gorbunov, Ivan; Morozova, Svetlana.

в: International Journal of Psychophysiology, Том 168, № S, S138-S139, 01.10.2021, стр. S138-S139.

Результаты исследований: Научные публикации в периодических изданияхтезисыРецензирование

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Gorbunov, I & Morozova, S 2021, 'Fractal Dimention EEG Dinamics in Solving Task Recognition of Bar Plots', International Journal of Psychophysiology, Том. 168, № S, S138-S139, стр. S138-S139. https://doi.org/10.1016/j.ijpsycho.2021.07.397

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Author

Gorbunov, Ivan ; Morozova, Svetlana. / Fractal Dimention EEG Dinamics in Solving Task Recognition of Bar Plots. в: International Journal of Psychophysiology. 2021 ; Том 168, № S. стр. S138-S139.

BibTeX

@article{617398c1418041baa5fd9402d3fa7743,
title = "Fractal Dimention EEG Dinamics in Solving Task Recognition of Bar Plots",
abstract = "Fractal dimenttion EEG dinamics in solving task recognition of bar plotsThe aim of our study was to find out the dynamics of changes in the functional state of the brain during the work of psychology students with graphs and tables.We designed an experiment in which subjects compared graphs and tables and find tables that are equivalent to a certain graph. The first study involved 25 people. It was attended by first-year undergraduates and employees of the Faculty of Psychology of St. Petersburg State University.The experiment involved the presentation of a series of stimuli contents a graph and three tables, one of which corresponded in numerical values to the graph. Factors: the number of cells (from 4 to 9 cells in the tables, and bars in the graph), the variability of the column names in the tables.According to the results of Repeated measures MANOVA, several significant effects were found. At the beginning of the solution, the fractal dimension averaged over all derivations was higher than at the end (F (1, 168) = 15.712, p =, 00011). A reliable interaction of factors of the decision stage and the predominance of one or another type of intelligence was found (F (1, 168) = 6.2569, p =, 01333). In subjects with a predominance of mathematical intelligence, the decrease in fractal dimension was significantly greater.In the process of solving the problem of recognizing histograms in the brain, the work of the neural network is reorganized with minimize complexity. It is reflected in an increase in the accuracy of identification and categorization of the graph, and manifested in a decrease in the fractal dimension of the EEG.",
author = "Ivan Gorbunov and Svetlana Morozova",
note = "Gorbunov I., Morozova S. Fractal Dimention EEG Dinamics in Solving Task Recognition of Bar Plots //International Journal of Psychophysiology. – 2021. – Т. 168. – С. S138-S139.; null ; Conference date: 07-09-2021 Through 11-09-2021",
year = "2021",
month = oct,
day = "1",
doi = "10.1016/j.ijpsycho.2021.07.397",
language = "English",
volume = "168",
pages = "S138--S139",
journal = "International Journal of Psychophysiology",
issn = "0167-8760",
publisher = "Elsevier",
number = "S",
url = "http://www.iop2021.com/index.html",

}

RIS

TY - JOUR

T1 - Fractal Dimention EEG Dinamics in Solving Task Recognition of Bar Plots

AU - Gorbunov, Ivan

AU - Morozova, Svetlana

N1 - Gorbunov I., Morozova S. Fractal Dimention EEG Dinamics in Solving Task Recognition of Bar Plots //International Journal of Psychophysiology. – 2021. – Т. 168. – С. S138-S139.

PY - 2021/10/1

Y1 - 2021/10/1

N2 - Fractal dimenttion EEG dinamics in solving task recognition of bar plotsThe aim of our study was to find out the dynamics of changes in the functional state of the brain during the work of psychology students with graphs and tables.We designed an experiment in which subjects compared graphs and tables and find tables that are equivalent to a certain graph. The first study involved 25 people. It was attended by first-year undergraduates and employees of the Faculty of Psychology of St. Petersburg State University.The experiment involved the presentation of a series of stimuli contents a graph and three tables, one of which corresponded in numerical values to the graph. Factors: the number of cells (from 4 to 9 cells in the tables, and bars in the graph), the variability of the column names in the tables.According to the results of Repeated measures MANOVA, several significant effects were found. At the beginning of the solution, the fractal dimension averaged over all derivations was higher than at the end (F (1, 168) = 15.712, p =, 00011). A reliable interaction of factors of the decision stage and the predominance of one or another type of intelligence was found (F (1, 168) = 6.2569, p =, 01333). In subjects with a predominance of mathematical intelligence, the decrease in fractal dimension was significantly greater.In the process of solving the problem of recognizing histograms in the brain, the work of the neural network is reorganized with minimize complexity. It is reflected in an increase in the accuracy of identification and categorization of the graph, and manifested in a decrease in the fractal dimension of the EEG.

AB - Fractal dimenttion EEG dinamics in solving task recognition of bar plotsThe aim of our study was to find out the dynamics of changes in the functional state of the brain during the work of psychology students with graphs and tables.We designed an experiment in which subjects compared graphs and tables and find tables that are equivalent to a certain graph. The first study involved 25 people. It was attended by first-year undergraduates and employees of the Faculty of Psychology of St. Petersburg State University.The experiment involved the presentation of a series of stimuli contents a graph and three tables, one of which corresponded in numerical values to the graph. Factors: the number of cells (from 4 to 9 cells in the tables, and bars in the graph), the variability of the column names in the tables.According to the results of Repeated measures MANOVA, several significant effects were found. At the beginning of the solution, the fractal dimension averaged over all derivations was higher than at the end (F (1, 168) = 15.712, p =, 00011). A reliable interaction of factors of the decision stage and the predominance of one or another type of intelligence was found (F (1, 168) = 6.2569, p =, 01333). In subjects with a predominance of mathematical intelligence, the decrease in fractal dimension was significantly greater.In the process of solving the problem of recognizing histograms in the brain, the work of the neural network is reorganized with minimize complexity. It is reflected in an increase in the accuracy of identification and categorization of the graph, and manifested in a decrease in the fractal dimension of the EEG.

UR - https://www.sciencedirect.com/science/article/pii/S0167876021006036?via%3Dihub

UR - https://www.mendeley.com/catalogue/50bdf3cd-9d4e-35a1-8f04-41a0de929980/

U2 - 10.1016/j.ijpsycho.2021.07.397

DO - 10.1016/j.ijpsycho.2021.07.397

M3 - Meeting Abstract

VL - 168

SP - S138-S139

JO - International Journal of Psychophysiology

JF - International Journal of Psychophysiology

SN - 0167-8760

IS - S

M1 - S138-S139

Y2 - 7 September 2021 through 11 September 2021

ER -

ID: 88540011