DocumentCode :
3761816
Title :
EEG-based brain connectivity analysis of working memory and attention
Author :
Mohammad Bashiri;Wajid Mumtaz;Aamir Saeed Malik;Kinza Waqar
Author_Institution :
Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia
fYear :
2015
Firstpage :
41
Lastpage :
45
Abstract :
Recent research reveal that the Working Memory (WM) is more powerful than IQ as a predictor of academic success. However, there are factors that may influence WM performance, such as Attention. Although the impact of attention is well documented using ERPs; yet, the underlying brain connectivity of the interaction of these two constructs is not sufficiently understood. In this study, a Delay-Response task and electroencephalography (EEG) data are used to investigate the brain connectivity during two stages of Working Memory: Encoding and Maintenance. We have presented distraction in both stages, and a secondary task in maintenance stage. Scalp EEG data of 19 participants were recorded. These results not only reveal the underlying brain connectivity of each task, but also highlights the differences between distraction and multitasking. The results show significant brain connectivity changes in the frontal and occipital areas of the brain depending on the WM stage where the distraction is presented.
Keywords :
"Electroencephalography","Maintenance engineering","Electrodes","Encoding","Coherence","Feature extraction","Biomedical engineering"
Publisher :
ieee
Conference_Titel :
Biomedical Engineering & Sciences (ISSBES), 2015 IEEE Student Symposium in
Type :
conf
DOI :
10.1109/ISSBES.2015.7435890
Filename :
7435890
Link To Document :
بازگشت