Continuous or repetitive exposure to physical and psychological stressors can lead to a range of health problems caused by resulting malfunctional allostasis. The field of neuroarchitecture focuses on the relationship between architecture and neuroscience, and the specific neurological changes shown in biomarkers that can result from the built environment. In extreme environments, where exposure to stressors is heightened, the deliberate use of physical architecture and indoor environmental quality - for a positive influence on short and long-term stress response - is of even greater significance. Previous research investigated architecture as cause for stress, post-stress relaxation and for physical recovery. Still, architecture as acute countermeasure (reducing relative stress reaction) based on individual neuroendocrine response to prevent a shift to malfunctional allostasis is not well investigated. The thesis aims to help closing that gap by investigating the effectiveness of visual quality features as countermeasure to stressor exposure shown in biomarkers. It focuses on inter-individual reaction and the alignment of neuroarchitecture with functional requirements of architecture in extreme environments. The methodology for this is three-fold. A research framework was developed considering study design (including necessary infrastructure, stressor simulation, study conduction and data collection), and study outcomes (data analysis and data application). The framework was applied to a pilot study with human subjects focussing on colour correlated temperature (CCT) and heart rate variability (HRV). In addition to HRV, basic physical data, the participant’s stress over the last month, chronotype, perceived stress/workload during the experiment and test performance were recorded. The study data were processed through different computational models (including multi-criteria decision analyses and Bayesian linear effects models) analysing inter-individuality, the effect of confounding variables and the use of transient stressor simulation. The findings - while not generalizable due to the small data sample – indicate baseline-, stress-, and recovery-HRV were higher under warm CCT, but the HRV-change from stress to recovery was greater under blue CCT. Despite this, CCT did not show a significant counteracting effect reflected in the change from baseline-HRV to stress-HRV. The most relevant findings relate to the development and exploration of the methodology, providing directions to address inter-individuality of stress-response and cause-effect ambiguity in cross-sectional research on the effect of visual quality as countermeasure. The data were further used for the demonstration of a future application - using a microgravitational space station as case study - detailing Multi-Sensor Data Fusion and Bayesian Reinforcement Learning for a system that considers confounding influences, spatial limitations, functional requirements, accessibility, individual- and group-needs and long-term trends in biomarkers. The research framework can be extended and applied to future neuroarchitectural studies, the results of which could inform the development of adaptive systems in extreme environments. The aim of this thesis was the development of research methods and their preliminary validation that can contribute to future research on neuro-adaptive architecture as countermeasure to physiological stress response.