Green building research is shifting from a sole focus on physical performance to a human-centered, collaborative approach that integrates environmental sustainability with user well-being. However, a critical gap remains in understanding how built environments influence physiological, emotional, and cognitive processes. This review examines the integration of neuroscientific tools - including electroencephalography (EEG), functional magnetic resonance imaging (fMRI), event-related potentials (ERPs), eye-tracking (ET), and functional near-infrared spectroscopy (fNIRS) - into green building research. These technologies enable objective and fine-grained measurement of human responses to architectural spaces. We demonstrate how multimodal neurotechnologies facilitate real-time detection of human–environment interactions, supporting dynamic spatial optimization, health-oriented performance enhancement, and the subconscious reinforcement of sustainable behaviors. Beyond synthesizing empirical evidence, we propose an AI-augmented collaborative design framework that connects neural data with environmental parameters, bridging aesthetic, scientific, technical, and ethical rationalities. This framework provides a transformative pathway towards carbon neutrality while enhancing cognitive and emotional well-being, positioning neuroscience as a cornerstone of next generation green building research. • Integrates neuroscience (EEG, fMRI, ET, fNIRS) into green building to objectively measure user responses. • Proposes a collaborative design model bridging aesthetics, science, tech, and ethics for synergy. • Uses multimodal neural-environmental-behavioral data fusion for precise human-building interaction. • Shifts green building paradigm from human adaptation towards neuro-adaptive environments empowering users. • Uses neuro-responsive design to subconsciously drive sustainable behaviors and carbon goals.
Fu et al. (2026) studied this question.