DocumentCode
586396
Title
Towards a graph theoretical approach to study gender lateralization effect in mathematical thinking
Author
Klados, Manousos A. ; Lithari, C. ; Antoniou, I. ; Semertzidou, A. ; Bratsas, C. ; Micheloyannis, Sifis ; Bamidis, Panagiotis D.
Author_Institution
Lab. of Med. Inf., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece
fYear
2012
fDate
11-13 Nov. 2012
Firstpage
666
Lastpage
670
Abstract
Gender differences in mathematical thinking is a common concern of scientists from different research fields. Both parents and teachers report that males seem to perform better in complex mathematics compared to females. This study comes to shed light in the different organization of the underlying functional networks, in order to investigate the aforementioned observation, without supporting or rejecting this statement. In this sense, it is generally accepted that females use their both hemispheres to accomplish a certain task, while males use mostly the hemisphere which is properly suited. For the purposes of the current analysis, electroencephalographic recordings were collected from 11 males and 11 females, during a difficult mathematical task. Then a previously proposed model was used in order to pass from the sensor level to the cortical one, in order to examine the networks formed among the cortical dipoles. Mutual information was employed to form the graphs represeting the functional connectivity among the different dipoles, while the density, the global and the local efficiencies were further examined. The results suggest that females use their both hemisphere to solve the complex mathematical task while males use mostly their left hemisphere which is the responsible one for the mathematical thinking.
Keywords
biological techniques; electroencephalography; graph theory; neurophysiology; complex mathematics; cortical dipoles; electroencephalographic recordings; functional connectivity; functional networks; gender lateralization effect; graph theoretical approach; mathematical task; mathematical thinking; mutual information; Brain modeling; Educational institutions; Electroencephalography; Mathematics; Mutual information; Organizations; Scalp; Graph Theory; Inverse Problem; Mathematical Cognition; Mathematics; Mutual Information;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics & Bioengineering (BIBE), 2012 IEEE 12th International Conference on
Conference_Location
Larnaca
Print_ISBN
978-1-4673-4357-2
Type
conf
DOI
10.1109/BIBE.2012.6399746
Filename
6399746
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