This paper examines, conceptually, the relationship between stress-inducing architectural features and allostatic overload by drawing on literature from neuroimmunology and neuroarchitecture. The studies reviewed from the field of neuroimmunology indicate that chronic or repeated exposure to stress-inducing events may overwhelm the body’s regulatory system, resulting in a process termed allostatic overload. While there is evidence from the field of neuroarchitecture that short-term exposure to particular architectural features produce acute stress responses, there is yet to be a study on the relationship between stress-inducing architectural features and allostatic load. This paper considers how to design such a study by reviewing the two primary methods used to measure allostatic overload: biomarkers and clinimetrics. Of particular interest is the observation that the clinical biomarkers used to measure stress in neuroarchitectural studies differ substantially from those used to measure allostatic load. Therefore, the paper concludes that while the observed stress responses to particular architectural forms may indicate allostatic activity, further research is needed to determine whether these stress responses are leading to allostatic overload. Consequently, a discrete longitudinal public health study is advised, one which engages the clinical biomarkers indicative of allostatic activity and incorporates contextual data using a clinimetric approach.

Recent research in architectural neuroscience has found that visual exposure to biophilic design may help reduce occupant physiological stress responses. However, there are still significant gaps in our understanding of the complex ways in which biophilic design impacts on building occupant neurophysiology. The relationship between visual exposure to biophilic design and neurophysiological responses such as neuroinflammation have yet to be directly investigated. This paper examines the results of a pilot study that was established to investigate the relationship between visual exposure to biophilic design and neuroinflammation, as mediated by physiological stress responses. The pilot study utilised a 32-channel quantitative electroencephalograph (qEEG) to assess the relative changes in neuroinflammatory markers (relative alpha and relative delta power band activity) of 10 participants while they were exposed to 2D digital images of buildings that visually expressed varying degrees of biophilic design. Participants exhibited a decrease in relative delta power when exposed to higher levels of biophilic design. No statistically significant changes in relative alpha power were observed. These findings suggest that exposure to buildings with higher degrees of biophilia may result in decreased neuroinflammatory activity. In doing so, this research works to further develop our understanding of the complex ways in which the built environment impacts on occupant neuroinflammation and physiological stress.

Virtual architecture has been increasingly relied on to evaluate the health impacts of physical architecture. In this health research, exposure to virtual architecture has been used as a proxy for exposure to physical architecture. Despite the growing body of research on the health implications of physical architecture, there is a paucity of research examining the long-term health impacts of prolonged exposure to virtual architecture. In response, this paper considers: what can proxy studies, which use virtual architecture to assess the physiological response to physical architecture, tell us about the impact of extended exposure to virtual architecture on human health? The paper goes on to suggest that the applicability of these findings to virtual architecture may be limited by certain confounding variables when virtual architecture is experienced for a prolonged period of time. This paper explores the potential impact of two of these confounding variables: multisensory integration and gravitational perception. This paper advises that these confounding variables are unique to extended virtual architecture exposure and may not be captured by proxy studies that aim to capture the impact of physical architecture on human health through acute exposure to virtual architecture. While proxy studies may be suitable for measuring some aspects of the impact of both physical and virtual architecture on human health, this paper argues that they may be insufficient to fully capture the unintended consequences of extended exposure to virtual architecture on human health. Therefore, in the face of the increasing use of virtual architectural environments, the author calls for the establishment of a subfield of neuroarchitectural health research that empirically examines the physiological impacts of extended exposure to virtual architecture in its own right.

The built environment is increasingly recognized as a critical determinant of human health, profoundly influencing neurophysiological and psychological well-being. Previous studies show that specific visual patterns can elicit cortical hyperexcitation and visual discomfort, particularly in individuals with a predisposition to cortical hyperexcitability. However, traditional approaches to examining visual stress have yet to capture the complexity of ways in which the built environment may contribute to visual discomfort. This study presents a novel, integrated analytical methodology that merges generative artificial intelligence (using Midjourney v6.1) with advanced Fourier-based computational analysis to quantify the impact of architectural façades on visual stress. By systematically varying contrast ratios, pattern periodicity, spatial frequency distribution, stylistic elements, and geometric curvature across nine façade designs, the research generated a diverse array of stimuli that were then analyzed using the Visual Stress Analysis Tool (ViStA). This tool employs Fourier spatial frequency decomposition to extract key metrics that are proxy indicators of potential cortical stress responses. The results revealed that façades with regularly spaced elements at approximately three cycles per degree exhibited the highest stress metrics, particularly when combined with high contrast ratios and consistent repetition. Vertical wooden slats and vertical metal screening elements produced the most pronounced indicators of visual stress, while more varied geometric compositions demonstrated substantially lower stress metrics. This methodology offers a scalable, reproducible approach for the evaluation of visual stress. The framework lays the groundwork for developing a more robust evidence base to support architectural design decision-making that proactively addresses the health impacts of the built environment.

The global rise in mental health-related disorders represents a significant health and wellbeing challenge, imposing a substantial social and economic burden on individuals, communities, and healthcare systems. According to the World Health Organization, one in four people globally will be affected by mental or neurological disorders at some point in their lives, highlighting a significant global health concern that warrants carefully considered and innovative responses. While mental health challenges arise from complex, multifaceted factors, emerging research indicates that the built environment—the architecture of our homes, workplaces, and public spaces—may exert a critical but underappreciated influence on mental health outcomes. This paper outlines a novel theoretical framework for how visual stressors in the built environment might trigger neurophysiological stress responses via the HPA and SAM axes, potentially contributing over time to allostatic load. In this paper, it is proposed that chronic physiological strain can alter neuroplastic processes and neurogenesis in key brain regions—such as the hippocampus, prefrontal cortex (PFC), anterior cingulate cortex (ACC), and amygdala—thereby affecting cognitive health, emotional regulation, and overall mental wellbeing. Drawing on the principle of neurosustainability, this paper suggests that long-term exposure to stress-inducing environments may create feedback loops, particularly involving the amygdala, that have downstream effects on other brain areas and may be linked to adverse mental health outcomes such as depression. By presenting this framework, this paper aims to inspire further inquiry and applied experimental research into the intersection of neurophysiology, mental health, and the built environment, with a particular emphasis on rigorous testing and validation of the proposed mechanisms, that may then be translated into practical architectural design strategies for supporting health and wellbeing. In doing so, it is hoped that this work may contribute to a more holistic approach to improving mental health that integrates the creation of nurturing, resilient spaces into the broader public health agenda.

Generative AI is increasingly applied in architectural research, from automated ideation and reshaping design workflows to design education. Despite the increasing realism of synthetic imagery, several research gaps remain including alignment, plausibility, explainability, and control. This study focuses on alignment with human perceptions, specifically examining how synthetic architectural façade imagery aligns with geographical, objective, and affective text descriptors. We propose a pipeline that applies a Latent Diffusion Model to generate façade images and then evaluate this alignment through both AI-based and human-based evaluations. The results reveal that while images generated with geographical prompts are notably aligned, they also show clear biases. The results also reveal that images synthesised from objective descriptors (e.g., angular/curvy) are more aligned with human perceptions than affective descriptors (e.g., utopian/dystopian). These initial results highlight the opportunities and limits of current generative AI models, hinting at data biases and the potential lack of embodied understanding to grasp the complexity in experiencing architecture. Limitations of the study remain. Future work can expand on exploring cultural biases and semantic overlaps, and in testing more advanced embodied AI models and methods.