Building Bridges Between Brain and Building: AI’s Supportive Role in Neuroarchitecture

Abstract This chapter investigates the intersection of artificial intelligence (AI) and neuroarchitecture, focusing on how AI can enhance architectural design by integrating neuroscientific insights. This chapter highlights, utilizing a theoretical research approach, the importance of understanding how the human brain and nervous system process and interact with the built environment, impacting each other. Additionally, it discusses the significance and challenges facing the field of neuroarchitecture and presents AI applications that can advance and streamline various aspects of this field. This chapter’s main objective is to develop a conceptual framework for a knowledge-based system (KBS) that incorporates AI to facilitate the application of neuroscience principles in design. The AI tool as a research and decision-support system aims to help architects and students make informed decisions that optimize user experience and well-being. The KBS consists of three main components: inputs, system functions, and outputs, while considering critical criteria within its scope, including the use of the architectural space, the occupants’ age groups, and their functional abilities. The system inference engine uses designers’ inputs to derive conclusions, generating design recommendations based on neuroscience principles as outputs, categorized into space distribution and context, light and shadows, shapes and forms, colors and materiality, height, width, and enclosure. In conclusion, this chapter acknowledges and outlines the framework’s limitations and suggests future improvements, such as integrating user-friendly interfaces and expanding the framework’s scope to include additional factors like gender within the input categories to yield more detailed results. Future research could focus on designing the tool and testing its effectiveness.