Pattern learning reveals brain asymmetry to be linked to socioeconomic status

Author:

Poeppl Timm B12ORCID,Dimas Emile3,Sakreida Katrin1ORCID,Kernbach Julius M4,Markello Ross D5,Schöffski Oliver2,Dagher Alain6,Koellinger Philipp78,Nave Gideon9,Farah Martha J10,Mišić Bratislav5ORCID,Bzdok Danilo311ORCID

Affiliation:

1. Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen University , Aachen , Germany

2. Department of Health Management, School of Business, Economics and Society, Friedrich-Alexander-Universität Erlangen-Nürnberg , Nürnberg , Germany

3. Department of Biomedical Engineering, McConnell Brain Imaging Center (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, School of Computer Science, McGill University, Montreal , Quebec , Canada

4. Department of Neurosurgery, Faculty of Medicine, RWTH Aachen University , Aachen , Germany

5. McConnell Brain Imaging Center (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal , Quebec , Canada

6. Montreal Neurological Institute (MNI), McGill University , Montreal, Quebec , Canada

7. Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam , Amsterdam , The Netherlands

8. La Follette School of Public Affairs, University of Wisconsin-Madison , Madison, WI , USA

9. Marketing Department, The Wharton School, University of Pennsylvania , Philadelphia, PA , USA

10. Center for Neuroscience and Society, University of Pennsylvania , Philadelphia, PA , USA

11. Mila – Quebec Artificial Intelligence Institute , Montreal, Quebec , Canada

Abstract

Abstract Socioeconomic status (SES) anchors individuals in their social network layers. Our embedding in the societal fabric resonates with habitus, world view, opportunity, and health disparity. It remains obscure how distinct facets of SES are reflected in the architecture of the central nervous system. Here, we capitalized on multivariate multi-output learning algorithms to explore possible imprints of SES in gray and white matter structure in the wider population (n ≈ 10,000 UK Biobank participants). Individuals with higher SES, compared with those with lower SES, showed a pattern of increased region volumes in the left brain and decreased region volumes in the right brain. The analogous lateralization pattern emerged for the fiber structure of anatomical white matter tracts. Our multimodal findings suggest hemispheric asymmetry as an SES-related brain signature, which was consistent across six different indicators of SES: degree, education, income, job, neighborhood and vehicle count. Hence, hemispheric specialization may have evolved in human primates in a way that reveals crucial links to SES.

Funder

Brain Canada Foundation

Canada Brain Research Fund

National Institutes of Health

Canadian Institute of Health Research

Healthy Brains Healthy Lives Initiative

Canada Institute for Advanced Research

Publisher

Oxford University Press (OUP)

Subject

General Medicine

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