Technology roadmap toward the completion of whole-brain architecture with BRA-driven development

The development of brain-morphic software holds significant promise for creating artificial general intelligence that exhibits high affinity and interpretability for humans and also offers substantial benefits for medical applications. To facilitate this, creating Brain Reference Architecture (BRA) data, serving as a design specification for brain-morphic software is imperative. BRA-driven development, which utilizes Brain Information Flow (BIF) diagrams based on mesoscale brain anatomy and Hypothetical Component Diagrams (HCD) for corresponding computational functionalities, has been proposed to address this need. This methodology formalizes identifying possible functional structures by leveraging existing, albeit insufficient, neuroscientific knowledge. However, applying this methodology across the entire brain, thereby creating a Whole Brain Reference Architecture (WBRA), represents a significant research and development challenge due to its scale and complexity. Technology roadmaps have been introduced as a strategic tool to guide discussion, management, and distribution of resources within such expansive research and development activities. These roadmaps proposed a manual, anatomically based approach to incrementally construct BIF and HCD, thereby systematically expanding brain organ coverage toward achieving a complete WBRA. Large Language Model (LLM) technologies have introduced a paradigm shift, substantially automating the BRA-driven development process. This is largely due to the BRA data being structured around the brain’s anatomy and described in natural language, which aligns well with the capabilities of LLMs for supporting and automating the construction and verification processes. In this paper, we propose a novel technology roadmap to largely automate the creation of WBRA, leveraging neuroscientific insights. This roadmap includes 12 activities for automating BIF construction, notably extracting anatomical structures from scholarly articles. Furthermore, it details 11 activities aimed at enhancing the integration of Hypothetical Component Diagrams (HCD) into the WBRA, focusing on automating checks for functional consistency. This roadmap aims to establish a cost-effective and efficient design process for WBRA, ensuring the availability of brain-morphic software design specifications that are continually validated against the latest neuroscientific knowledge.