The Interpretation of the Effective Connectivity Maps Obtained by Using Dynamic Bayesian Networks on EEG Data

Date

2016-01-01

Author

Erkuş, Ekin Can
Ulusoy, İlkay

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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The main aim of this study was to compare and discuss the effective brain connectivity maps of dyslexic and control groups in terms of differences and similarities. The differences and sismilarities that may be found in the study, could provide information for the related future studies. There were total of 58 subjects which were 27 control and 31 dyslexics data in this study. All the data according to the groups were averaged with respect to time and group data were generated. Then, effective connectivity maps for both dyslexic and control groups were constructed using the Dynamic Bayesian Networks algorithms. The symmetric connectivities which we call strong connections between electrode pairs were extracted and mainly used for discussion. It was observed that there are differences in effective connectivity maps of both groups in terms of connections' density and directions. The results should also be checked by brain anatomy experts anatomically and by comparing with literature of medicine, their validity and usabilities could be tested.

Subject Keywords

EEG, Dyslexia, Dynamic Bayesian Networks, DBN, Effective Connectivity, Brain connectivity

URI

https://hdl.handle.net/11511/53584

Collections

Graduate School of Natural and Applied Sciences, Conference / Seminar

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Citation Formats

E. C. Erkuş and İ. Ulusoy, “The Interpretation of the Effective Connectivity Maps Obtained by Using Dynamic Bayesian Networks on EEG Data,” 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53584.