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Neurobehavioural characterisation and stratification of reinforcement-related behaviour

Nature Human Behaviour volume 4, pages 544–558 (2020)Cite this article

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Abstract

Reinforcement-related cognitive processes, such as reward processing, inhibitory control and social–emotional regulation are critical components of externalising and internalising behaviours. It is unclear to what extent the deficit in each of these processes contributes to individual behavioural symptoms, how their neural substrates give rise to distinct behavioural outcomes and whether neural activation profiles across different reinforcement-related processes might differentiate individual behaviours. We created a statistical framework that enabled us to directly compare functional brain activation during reward anticipation, motor inhibition and viewing emotional faces in the European IMAGEN cohort of 2,000 14-year-old adolescents. We observe significant correlations and modulation of reward anticipation and motor inhibition networks in hyperactivity, impulsivity, inattentive behaviour and conduct symptoms, and we describe neural signatures across cognitive tasks that differentiate these behaviours. We thus characterise shared and distinct functional brain activation patterns underling different externalising symptoms and identify neural stratification markers, while accounting for clinically observed comorbidity.

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Fig. 1: Workflow of the analyses.
Fig. 2: Activation maps of MID, SST, EFT and their overlay.
Fig. 3

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Data availability

IMAGEN data are available from a dedicated database: https://imagen2.cea.fr.

Code availability

Custom code that supports the findings of this study is available from the corresponding author upon request.

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Acknowledgements

This work received support from the following sources: the European Union-funded FP6 Integrated Project IMAGEN (reinforcement-related behaviour in normal brain function and psychopathology; LSHM-CT-2007-037286), the Horizon 2020-funded ERC Advanced Grant ‘STRATIFY’ (brain network-based stratification of reinforcement-related disorders; 695313), National Natural Science Foundation of China (81801773 and 81873909), the Shanghai Pujiang Project (18PJ1400900), ERANID (understanding the interplay between cultural, biological and subjective factors in drug use pathways; PR-ST-0416-10004), BRIDGET (JPND brain imaging, cognition, dementia and next generation GEnomics; MR/N027558/1), the Human Brain Project (SGA 2, 785907, and SGA 3, 945539), the FP7 project MATRICS (603016), the Medical Research Council Grant ‘c-VEDA’ (consortium on vulnerability to externalizing disorders and addictions; MR/N000390/1), the National Institute of Health (NIH) (R01DA049238, A decentralized macro and micro gene-by-environment interaction analysis of substance use behavior and its brain biomarkers), the National Institute for Health Research Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, the Bundesministerium für Bildung und Forschung (grants 01GS08152 and 01EV0711 and Forschungsnetz AERIAL 01EE1406A and 01EE1406B), the Deutsche Forschungsgemeinschaft (DFG grants SM 80/7-2, SFB 940, TRR 265 and NE 1383/14-1), the Medical Research Foundation and Medical Research Council (grants MR/R00465X/1 and MR/S020306/1), the National Institutes of Health (NIH)-funded ENIGMA (grants 5U54EB020403-05 and 1R56AG058854-01). Further support was provided by grants from: ANR ANR-12-SAMA-0004, AAPG2019 - GeBra), the Eranet Neuron (AF12-NEUR0008-01 - WM2NA and ANR-18-NEUR00002-01 - ADORe), the Fondation de France (00081242), the Fondation pour la Recherche Médicale (DPA20140629802), the Mission Interministérielle de Lutte Contre les Drogues et les Conduites Addictives (MILDECA), the Assistance-Publique – Hôpitaux de Paris and INSERM (interface grant), Paris Sud University IDEX 2012, the Fondation de l’Avenir (grant AP-RM-17-013), the Fédération pour la Recherche sur le Cerveau, the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797) and U.S.A. (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772-01A1), and by NIH Consortium grant U54 EB020403 (supported by a cross-NIH alliance that funds Big Data to Knowledge Centres of Excellence), the 111 Project (B18015), the National Key Research and Development Program of China (2018YFC0910503 and 2018YFC1312900), the NSFC (81930095 and 91630314), The Key Project of Shanghai Science and Technology Innovation Plan (16JC1420402), the Shanghai Municipal Science and Technology Major Project (2018SHZDZX01) and Zhangjiang Lab. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Authors and Affiliations

  1. Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China

    Tianye Jia, Qiang Luo, Jianfeng Feng, Gunter Schumann, Tianye Jia & Gunter Schumann

  2. MoE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Shanghai, China

    Tianye Jia, Qiang Luo, Jianfeng Feng & Tianye Jia

  3. Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King’s College London, London, UK

    Tianye Jia, Alex Ing, Erin Burke Quinlan, Nicole Tay, Qiang Luo, Sylvane Desrivières, Jianfeng Feng, Gunter Schumann, Tianye Jia, Alex Ing, Erin Burke Quinlan, Sylvane Desrivières & Gunter Schumann

  4. MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China

    Tianye Jia, Qiang Luo & Tianye Jia

  5. State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China

    Qiang Luo, Biondo Francesca & Biondo Francesca

  6. Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany

    Tobias Banaschewski, Frauke Nees, Tobias Banaschewski & Frauke Nees

  7. Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK

    Gareth J. Barker & Gareth J. Barker

  8. Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland

    Arun L. W. Bokde & Arun L. W. Bokde

  9. University Medical Centre Hamburg-Eppendorf, Hamburg, Germany

    Uli Bromberg, Christian Büchel, Uli Bromberg & Christian Büchel

  10. Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, P.R. China

    Jianfeng Feng

  11. Department of Computer Science, University of Warwick, Coventry, UK

    Jianfeng Feng

  12. Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, PR China

    Jianfeng Feng

  13. Shanghai Center for Mathematical Sciences, Shanghai, PR China

    Jianfeng Feng

  14. Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany

    Herta Flor, Frauke Nees, Herta Flor & Frauke Nees

  15. Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany

    Herta Flor & Herta Flor

  16. NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France

    Antoine Grigis, Dimitri Papadopoulos Orfanos & Dimitri Papadopoulos Orfanos

  17. Departments of Psychiatry and Psychology, University of Vermont, Burlington, Vermont, USA

    Hugh Garavan & Hugh Garavan

  18. Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK

    Penny Gowland & Penny Gowland

  19. Department of Psychiatry and Psychotherapy CCM, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany

    Andreas Heinz, Henrik Walter, Andreas Heinz & Henrik Walter

  20. Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Brunswick, Germany

    Bernd Ittermann & Bernd Ittermann

  21. Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 “Neuroimaging & Psychiatry”, University Paris Saclay, University Paris Descartes; DIgiteo-Labs, Gif-sur-Yvette, France

    Jean-Luc Martinot, Marie-Laure Paillère Martinot & Jean-Luc Martinot

  22. Maison de Solenn, Paris, France

    Jean-Luc Martinot & Jean-Luc Martinot

  23. AP-HP.Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France

    Marie-Laure Paillère Martinot

  24. Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital and Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, Canada

    Tomáš Paus & Tomáš Paus

  25. Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany

    Luise Poustka & Luise Poustka

  26. Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany

    Juliane H. Fröhner, Michael N. Smolka, Juliane H. Fröhner & Michael N. Smolka

  27. School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland

    Robert Whelan & Robert Whelan

  28. PONS Research Group, Dept of Psychiatry and Psychotherapy, Campus Charite Mitte, Humboldt University, Berlin, Germany

    Gunter Schumann & Gunter Schumann

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  1. Tianye Jia
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  2. Alex Ing
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  3. Erin Burke Quinlan
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  4. Nicole Tay
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  5. Qiang Luo
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  6. Biondo Francesca
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  7. Tobias Banaschewski
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  8. Gareth J. Barker
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  9. Arun L. W. Bokde
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  10. Uli Bromberg
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  11. Christian Büchel
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  12. Sylvane Desrivières
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  13. Jianfeng Feng
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  14. Herta Flor
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  15. Antoine Grigis
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  16. Hugh Garavan
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  17. Penny Gowland
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  18. Andreas Heinz
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  19. Bernd Ittermann
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  20. Jean-Luc Martinot
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  21. Marie-Laure Paillère Martinot
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  22. Frauke Nees
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  23. Dimitri Papadopoulos Orfanos
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  24. Tomáš Paus
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  25. Luise Poustka
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  26. Juliane H. Fröhner
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  27. Michael N. Smolka
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  28. Henrik Walter
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  29. Robert Whelan
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  30. Gunter Schumann
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Consortia

IMAGEN Consortium

  • Tianye Jia
  • , Alex Ing
  • , Erin Burke Quinlan
  • , Biondo Francesca
  • , Tobias Banaschewski
  • , Gareth J. Barker
  • , Arun L. W. Bokde
  • , Uli Bromberg
  • , Christian Büchel
  • , Sylvane Desrivières
  • , Herta Flor
  • , Hugh Garavan
  • , Penny Gowland
  • , Andreas Heinz
  • , Bernd Ittermann
  • , Jean-Luc Martinot
  • , Frauke Nees
  • , Dimitri Papadopoulos Orfanos
  • , Tomáš Paus
  • , Luise Poustka
  • , Juliane H. Fröhner
  • , Michael N. Smolka
  • , Henrik Walter
  • , Robert Whelan
  •  & Gunter Schumann

Contributions

G.S. and T.J. designed the study. T.J. and G.S. wrote the manuscript. A.I., E.B.Q., N.T., Q.L. and B.F. edited the first draft. All authors critically reviewed the manuscript. T.B., G.J.B., A.L.W.B., U.B., C.B., S.D., J.F., H.F., A.G., H.G., P.G., A.H., B.I., J.-L.M., M.-L.P.M., F.N., T.P., L.P., J.H.F., M.N.S., H.W., R.W. and G.S. were the principal investigators. E.B.Q., T.B., G.J.B., A.L.W.B., U.B., C.B., H.F., A.G., H.G., P.G., A.H., B.I., J.-L.M., M.-L.P.M., F.N., D.P.O., T.P., L.P., J.H.F., M.N.S., H.W., R.W. and G.S. acquired the data. T.J. and A.I. analysed the data.

Corresponding authors

Correspondence to Tianye Jia or Gunter Schumann.

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Competing interests

T.B. served in an advisory or consultancy role for Lundbeck, Medice, Neurim Pharmaceuticals, Oberberg and Shire. He received conference support or speaker’s fees from Lilly, Medice, Novartis and Shire. He has been involved in clinical trials conducted by Shire and Vifor Pharma. He received royalties from Hogrefe, Kohlhammer, CIP Medien and Oxford University Press. The present work is unrelated to the above grants and relationships. G.J.B. has received honoraria from General Electric Healthcare for teaching on scanner programming courses. The other authors declare no competing interests.

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Editor recognition statement: Primary Handling Editor: Marike Schiffer.

Extended data

Extended Data Fig. 1 Dendrograms of heirachical clustering for WVCNA nodes.

Dendrogram trees and static cut at 90% quantile of height of branches for (A) MID, (B) SST and (C) EFT nodes from WVCNA.

Extended Data Fig. 2 Overlapped functional brain regions.

Overlapped Functional Brain Regions (Cohen’s D > 0.30) Identified across All Three Tasks.

Extended Data Fig. 3 Extended RCCA results between fMRI and externalizing behaviours.

RCCA results between fMRI and externalising behaviours based on 1000 Permutation with predefined Regulation Parameters: A. The Effect Size (η2) and Confidence Intervals; B. P-values.

Extended Data Fig. 4 Extended RCCA results between fMRI and internalizing behaviours.

RCCA results between fMRI and internalising behaviours based on 1000 Permutation with predefined regulation parameters.

Extended Data Fig. 5 The design of monetary incentive delay (MID) task.

The figure of experimental paradigm was adapted from a previous publication6.

Extended Data Fig. 6 The design of emotional face task (EFT).

The figure of experimental paradigm was adapted from a previous publication22.

Extended Data Fig. 7 The design of stop signal task (SST).

The figure of experimental paradigm was adapted from a previous publication52.

Extended Data Fig. 8 Plot of soft-threshold for MID (A), EFT (B) and SST (C).

The soft-thresholds were picked as 7 for MID, 8 for EFT and 7 for SST.

Supplementary information

Supplementary Information

Supplementary Tables 2–4 and the full list of consortium members.

Reporting Summary

Supplementary Table 1

a, Functional brain regions identified through WVCNA for the MID task and the following hierarchical clustering results at the height of the top 90%. b, Functional brain regions identified through WVCNA for the SST task and the following hierarchical clustering results at the height of the top 90%. c, Functional brain regions identified through WVCNA for the EFT task and the following hierarchical clustering results at the height of the top 90%

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Jia, T., Ing, A., Quinlan, E.B. et al. Neurobehavioural characterisation and stratification of reinforcement-related behaviour. Nat Hum Behav 4, 544–558 (2020). https://doi.org/10.1038/s41562-020-0846-5

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