Deep learning identifies partially overlapping subnetworks in the human social brain

Communications Biology, vol. 4, pp. 65

Abstract

Complex social interplay is a defining property of the human species. In social neuroscience, many experiments have sought to first define and then locate 'perspective taking', 'empathy', and other psychological concepts to specific brain circuits. Seldom, bottom-up studies were conducted to first identify explanatory patterns of brain variation, which are then related to psychological concepts; perhaps due to a lack of large population datasets. In this spirit, we performed a systematic de-construction of social brain morphology into its elementary building blocks, involving ~10,000 UK Biobank participants. We explored coherent representations of structural co-variation at population scale within a recent social brain atlas, by translating autoencoder neural networks from deep learning. The learned subnetworks revealed essential patterns of structural relationships between social brain regions, with the nucleus accumbens, medial prefrontal cortex, and temporoparietal junction embedded at the core. Some of the uncovered subnetworks contributed to predicting examined social traits in general, while other subnetworks helped predict specific facets of social functioning, such as the experience of social isolation. As a consequence of our population-level evidence, spatially overlapping subsystems of the social brain probably relate to interindividual differences in everyday social life.

Authors 7

1. Hannah Kiesow Aachen Department of Psychiatry, Psychotherapy and Psychosomatics

   RWTH Aachen University

   Affiliation as printed

   Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen University, Aachen, Germany

2. R. Nathan Spreng

   McGill University · Montreal Neurological Institute and Hospital

   Affiliation as printed

   Department of Psychiatry and Psychology, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada

   Laboratory of Brain and Cognition, Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada

3. Avram J. Holmes

   Yale University

   Affiliation as printed

   Department of Psychology, Yale University, New Haven, CT, USA

4. M. Mallar Chakravarty

   McGill University · Douglas Mental Health University Institute

   Affiliation as printed

   Cerebral Imaging Centre, Douglas Research Centre, Montreal, QC, Canada

   Department of Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada

   Department of Psychiatry, McGill University, Montreal, QC, Canada

5. André F. Marquand

   King's College London · Radboud University Medical Center · Radboud University Nijmegen · Donders Institute for Brain, Cognition and Behaviour · Donders Centre for Cognitive Neuroimaging

   Affiliation as printed

   Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands

   Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, King's College London, De Crespigny Park, London, UK

   Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands

6. B.T. Thomas Yeo

   National University of Singapore

   Affiliation as printed

   Department of Electrical and Computer Engineering, Centre for Sleep and Cognition, Clinical Imaging Research Centre, N.1 Institute for Health and Institute for Digital Medicine, National University of Singapore, Singapore, 119077, Singapore

7. Danilo Bzdok corresponding

   McGill University · Montreal Neurological Institute and Hospital · Mila - Quebec Artificial Intelligence Institute

   Affiliation as printed

   Department of Biomedical Engineering, McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, School of Computer Science, McGill University, Montreal, Canada. danilo.bzdok@mcgill.ca

   Mila - Quebec Artificial Intelligence Institute, Montreal, Canada. danilo.bzdok@mcgill.ca

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