NEUROGENERATIVE ARCHITECTURE: A Conceptual Framework for Spatial Production Based on Human Data

XX. Symposium on Digital Design in Architecture (MSTAS 2026)

TED University, Ankara · 21-23 June 2026

Authors: Betül Uçkan, Ayçin Atukeren, Bengü Özmutlu, Aykut Dağ, Tolga Aydoğdu, Umut Pektetik, Ahmet Gün, Ethem Gürer, Tülay Karakaş

Neurogenerative Architecture

For many years, architecture has predominantly approached space as a physical and static construct, while the human-space relationship has been evaluated primarily through functional and formal dimensions. Recent advances in neuroimaging technologies have enabled a more detailed investigation of the cognitive and emotional effects of architectural environments on humans, contributing significantly to the development of the field of neuroarchitecture. However, most existing neuroarchitectural research focuses on analyzing the relationship between humans and space, while holistic models that transform the resulting data directly into generative inputs for the design process remain limited. Similarly, generative design approaches are capable of producing design alternatives through algorithmic and parametric systems, yet they rarely incorporate human cognitive and emotional states directly into the design process. In response to this gap, this study proposes the concept of neurogenerative architecture, which brings together the analytical foundations of neuroarchitecture and the methodological approaches of generative design.

The research is structured as a conceptual and theoretical study and includes a comparative review of studies related to Brain-Computer Interfaces (BCI), EEG-based design, neuroadaptive design, neuroresponsive design, and generative design. Based on this review, a conceptual model is developed that considers human neurophysiological data as one of the active inputs of spatial production. The proposed model describes a process in which neurophysiological data are collected, processed, transformed into meaningful indicators of human states, translated into design parameters, and spatialized through generative systems within hybrid environments. Within this framework, data obtained from users are treated not merely as analytical outputs but as design inputs capable of influencing lighting conditions, soundscapes, audiovisual atmospheres, and spatial behaviors. Consequently, a continuous neurofeedback loop can be established between humans and space, allowing spatial environments to transform synchronously in response to user data.

As a result, the study proposes reconsidering space not as a fixed object but as a dynamic system that is informed by human data, evolves together with its users, and interacts with cognitive states. In this sense, neurogenerative architecture offers a conceptual framework that establishes a new relationship between human experience and computational design processes.

Keywords: Neurogenerative architecture, neuroarchitecture, generative design, Brain-Computer Interface (BCI), neurofeedback.