Stress and streets: How the network structure of streets is associated with stress-related brain activation

Abstract

Previous research has examined the relation between urban design factors and mental health, but the impact of street networks is underrepresented. This exploratory, cross-sectional study examines the association between street network variables based on the Space Syntax theory and whole-brain activation during a social stress paradigm. Forty-two individuals who lived in Berlin participated in an fMRI study during which acute social stress was induced. Saliva cortisol concentrations, subjective stress ratings, and mean heart rate were assessed as proxies for a successful stress induction. Space Syntax was used as a tool to objectively measure street network characteristics including global integration (‘proximity’ of a street to all the other streets in a network), local integration (‘proximity’ of a street to a certain number of streets within a walkable area), connectivity (‘direct street connections’ a street has), and normalized angular choice (NACH) (‘straightest and shortest’ route for a street in a street network). They were analyzed within a 1500 m radius of participants' address (i.e., neighborhood) as well as for the street closest to their address (i.e., point address). Higher mean neighborhood global and local integration, which equate to better integrated streets in the network, were associated with less activation during stress provocation in several brain regions, including dorsal anterior cingulate cortex, insula, and thalamus, which play a role in the detection of salient stimuli and threats. No association was found between brain activity and global and local integration for the point address. There was also no association between brain activity and connectivity or NACH for any conditions. The study indicates that Space Syntax is a useful tool for measuring macro-scale urban space (e.g., street networks) in neuro-urbanistic studies. The results underline the need to explore the potential of optimizing street networks to better understand pathways to urban mental health.