A design-integrated framework for neuroarchitectural research

Area of Science:

• Neuroaesthetics
• Neuroarchitecture
• Architectural Design
• Empirical Psychology

Background:

• Current neuroaesthetics and neuroarchitecture studies often lack situated experience and embodied engagement.
• Bridging the gap between empirical rigor and architectural meaning requires new methodological approaches.
• Dominant assumptions in neuroarchitectural research need systematic reassessment to enhance ecological validity.

Purpose of the Study:

• To present a multi-stage framework integrating architectural design logic with empirical testing across representational scales.
• To bridge disciplinary divides between empirical rigor and situated experience, visual abstraction and embodied engagement, and neuroscientific measurement and architectural meaning.
• To systematically reassess dominant methodological assumptions in neuroaesthetics and neuroarchitectural studies using curvature as a test case.

Main Methods:

• Developed a three-phase experimental approach: image-based evaluation (Phase 1), object-based interaction (Phase 2), and full-scale immersive experience (Phase 3).
• Utilized a stimulus-generation pipeline rooted in spatial logic and architectural composition.
• Positioned the architectural environment as a generator of perceptual, affective, and behavioral data within an iterative research process.

Main Results:

• Phase 1 findings illustrate the framework's capacity to generate perceptually distinct stimuli.
• Recurring evaluative patterns were revealed, including foreground-sensitive preferences for curvature under controlled figure-ground manipulations.
• Methodological calibration and design logic for subsequent phases were informed by Phase 1 results.

Conclusions:

• The proposed framework offers a scalable and adaptable approach for advancing neuroarchitectural research.
• It supports collaborative investigations across multiple contexts, progressively increasing ecological validity.
• The framework positions the architectural environment as an active participant in generating research data, moving beyond passive evaluation.