Magnesium Pincer Complexes for Pyridine Hydrogenation

Abstract

This thesis investigates why EEG-based neurophysiological research in architecture remains primarily confined to the design guideline phase, despite its potential for direct integration into design development. Through historical, philosophical, and empirical analysis, the study argues that neuroarchitecture possesses a sufficiently mature theoretical foundation for application across all design phases. A systematic review analysis demonstrates that research complexity increases substantially in design development, requiring advanced computational methods such as machine learning and real-time brain-computer interfaces. The findings suggest that the limited adoption of neuroscience during the act of designing is not due to theoretical shortcomings, but rather to the absence of accessible computational tools, pipelines, and shared datasets. The thesis concludes that broader integration of neuroscience in architecture depends on the development of practical and accessible infrastructures for designers.