Why do we need big brain data?
Human brains are in constant interaction with the social world. They guide our decisions in the social sphere but are also consistently being influenced by our proximal and distal environment, such as our family relations and living conditions. Understanding this complex interplay between brain and its dynamic social surroundings is imperative for pinpointing the social and environmental factors contributing to healthy and pathological development of the brain’s cognitive and affective systems. The AIVO project addresses this question by connecting i) human molecular and structural brain scans, ii) measures of psychological and somatic well-being, and iii) indicators of intergenerational socioeconomic well-being into a a new large-scale register-based database (>50,000 adults). By combining the unique Finnish register data with the existing medical register data on molecular (positron emission tomography) and structural (magnetic resonance imaging) neuroimaging we can characterize the interactions between social environment and brain with unparalleled accuracy and detail.
Data analysis techniques
Using both advanced multilevel latent class models and unsupervised machine learning, we quantify the reciprocal links between socioeconomic protective and risk factors, social attachment behaviour, and neurotransmission, brain structure and function through the lifespan.This unique large-scale analysis of existing brain imaging data combined with detailed register indices of well-being, cognition and affective functioning will provide new model for detecting brain-based diseases as well as brain-environment relationships, and allows establishing functional and molecular ‘fingerprints’ of risk factors for negative neurological, psychiatric as well as socioeconomic outcomes.
PET and MRI data are automatically retrieved from hospital Picture Archiving and Communication System (PACS) and processed with the MAGIA pipeline. Imaging data are linked with longitudinal register indices of psychological functioning, socioeconomic well-being, and somatic well-being in the AIVO database
Data frame
The project’s data frame involves unique combination of neural, medical, psychological and social and socioeconomic “fingerprints” from the individuals. These time-series data are organised into a multilayer network where we can analyse the interactions of the various protective and risk factors on multiple indicators of brain structure and function.
