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.