EEG-based Brain Connectivity Analysis of Working Memory and Attention

• Main Author: ., Mohammad Bashiri
• Format: Final Year Project
• Language: English
• Published: IRC 2015
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://utpedia.utp.edu.my/16001/1/Dissertation%20-%20Bashiri.pdf; http://utpedia.utp.edu.my/16001/

Recent research reveal that the Working Memory (WM) is more powerful than IQ as a predictor of academic success. WM is the type of memory in human brain which is responsible for manipulating the input (encoded) data and storing them in a limited manner. As it can be observed from the latter statement, “limited manner”, the limitation of WM is the number of items which it can hold, which essentially leave the performance of WM to depend on the type of information that is being held in it (i.e., some information take more space, some less). However, recent psychological advances show that not only WM performance is affected by the type of information, but also attention can influence WM performance. 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.