 This paper proposes extending current digital cognitive architectures to create more robust human digital twins, HDTs, suitable for realistic metaverse cybersecurity simulations. The study identified the top 10 psychology constructs for HDTs based on 20-time tested theories and applied network science centrality algorithms to rank them by influence. The results suggest specific extensions such as implementing refined structures of long-term memory and perception, focusing on non-cognitive yet influential constructs like arousal, and creating new capabilities for simulating, reasoning about, and selecting circumstances. Early usability tests demonstrate the usefulness of Saibanto for immediate uses such as manual analysis of hackers' behaviors and automatic analysis of behavioral cybersecurity knowledge texts. This article was authored by Tam Nguyen.