Analysis of Existing Datasets 

Cumulative evidence suggests that our environment influences several aspects of human behavior and mental health. Expanding our understanding of such associations requires large datasets, which are costly in terms of scientific effort and financial resources. In response, neuroscientists have embraced data sharing as an effective way to maximize the scientific yield from individual studies. At the Center for Environmental Neuroscience (CEN), we leverage several large-scale, openly accessible datasets to explore how environmental factors intersect with brain structure, behavior, and mental health.

1. IMAGEN: The IMAGEN project (https://www.imagen-project.org/) contains neuroimaging, genetic, environmental, and psychiatric data from 2000 adolescents. Given its longitudinal nature, the IMAGEN dataset is ideal for capturing environmental and individual changes over adolescence, a critical developmental period with numerous milestones at the social and neural levels. Contributing to growing evidence of brain-environment associations during childhood and pre-adolescence, we aim to trace these associations from adolescence to early adulthood and to ascertain whether environmental aspects shape brain developmental outcomes, for instance, in terms of brain volume and brain connectivity. Our goal is to identify macro-environmental features at the neighborhood level or beyond (e.g., urban fabric density, green spaces) that play a role in brain development. 
2. UK Biobank: The UK Biobank (https://www.ukbiobank.ac.uk/) is one of the largest biomedical databases in the world. It contains genetic, biological, lifestyle, and health information from over 500,000 middle-aged and older adults. Importantly, it includes neuroimaging data for approximately 100,000 participants, providing a unique opportunity to investigate the links between environmental exposures and brain structure later in life.
   At CEN, we use this dataset to explore how physical surroundings relate to brain health and mental well-being. For instance, we examine associations between urban environments and the prevalence of psychotic experiences, building on evidence that individuals in urban areas face up to twice the risk of developing psychotic disorders (Vassos et al., 2012). These insights are essential for identifying environmental risk factors and informing urban design that supports mental health.
3. Other available datasets include: 1) The German National Cohort study (NAKO; https://nako.de/en/study/), the largest long-term population study in Germany. It contains lifestyle, environmental, and genetic data from approximately 200,000 participants between the ages of 20 and 69; 2) The Berlin Aging Study II (BASE-II; https://www.base2.mpg.de/en), an extension of the Berlin Aging Study (BASE), which was carried out between 1990 and 1993 and contains longitudinal medical, behavioral, psychological, and genetic data from 2200 residents of  Berlin aged between 70 and over 100; and 3) The Lothian Birth Cohort 1936 (LBC1936; https://lothian-birth-cohorts.ed.ac.uk/), which contains psychological, sociological, and medical (including MRI) data across five acquisition waves of approximately 500-1000  participants (mean age = 70–79).

Literature 

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Vassos, E., Pedersen, C. B., Murray, R. M., Collier, D. A., & Lewis, C. M. (2012). Meta-analysis of the association of urbanicity with schizophrenia. Schizophrenia bulletin, 38(6), 1118–1123.