TY - GEN
T1 - Assessing small-worldness of dynamic functional brain connectivity during complex tasks
AU - Ren, Shen
AU - Taya, Fumihiko
AU - Sun, Yu
AU - Desouza, Joshua
AU - Thakor, Nitish V.
AU - Bezerianos, Anastasios
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/4
Y1 - 2015/11/4
N2 - The development of network theory has introduced new approaches to understand the brain as a complex system. Currently the time-variant functional connectivity of brain networks under complex tasks is still being investigated. To explore connectivity during complex cognitive and motor tasks, this study focused on the relevance of small-worldness to human workloads using EEG signals from a dynamic analytic approach. Experiments were designed to investigate the small-worldness under two types of flight simulation tasks at two levels of difficulty - easy and hard. The results demonstrated a consistent small-world architecture of brain connectivity with time-based variance during complex tasks. We noticed an increased small-world effect especially at the alpha band when performing hard tasks compared to easy tasks, which relate to high and low workload respectively. Our results show the potential of dynamic brain network analysis in exploring time-variant and task-dependent brain connectivity during complex tasks.
AB - The development of network theory has introduced new approaches to understand the brain as a complex system. Currently the time-variant functional connectivity of brain networks under complex tasks is still being investigated. To explore connectivity during complex cognitive and motor tasks, this study focused on the relevance of small-worldness to human workloads using EEG signals from a dynamic analytic approach. Experiments were designed to investigate the small-worldness under two types of flight simulation tasks at two levels of difficulty - easy and hard. The results demonstrated a consistent small-world architecture of brain connectivity with time-based variance during complex tasks. We noticed an increased small-world effect especially at the alpha band when performing hard tasks compared to easy tasks, which relate to high and low workload respectively. Our results show the potential of dynamic brain network analysis in exploring time-variant and task-dependent brain connectivity during complex tasks.
UR - http://www.scopus.com/inward/record.url?scp=84953265668&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84953265668&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2015.7318999
DO - 10.1109/EMBC.2015.7318999
M3 - Conference contribution
C2 - 26736899
AN - SCOPUS:84953265668
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 2904
EP - 2907
BT - 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Y2 - 25 August 2015 through 29 August 2015
ER -