Decreased brain connectivity in smoking contrasts with increased connectivity in drinking

  1. Wei Cheng  Is a corresponding author
  2. Edmund T Rolls  Is a corresponding author
  3. Trevor W Robbins
  4. Weikang Gong
  5. Zhaowen Liu
  6. Wujun Lv
  7. Jingnan Du
  8. Hongkai Wen
  9. Liang Ma
  10. Erin Burke Quinlan
  11. Hugh Garavan
  12. Eric Artiges
  13. Dimitri Papadopoulos Orfanos
  14. Michael N Smolka
  15. Gunter Schumann
  16. Keith Kendrick
  17. Jianfeng Feng  Is a corresponding author
  1. Fudan University, China
  2. University of Cambridge, United Kingdom
  3. Xidian University, China
  4. Shanghai University Finance and Economics, China
  5. University of Warwick, United Kingdom
  6. Beijing Institute of Genomics, Chinese Academy of Sciences, China
  7. King's College London, United Kingdom
  8. University of Vermont, United States
  9. University Paris Descartes, France
  10. Université Paris-Saclay, France
  11. Technische Universität Dresden, Germany
  12. University of Electronic Science and Technology of China, China

Abstract

In a group of 831 participants from the general population in the Human Connectome Project, smokers exhibited low overall functional connectivity, and more specifically of the lateral orbitofrontal cortex which is associated with non-reward mechanisms, the adjacent inferior frontal gyrus, and the precuneus. Participants who drank a high amount had overall increases in resting state functional connectivity, and specific increases in reward-related systems including the medial orbitofrontal cortex and the cingulate cortex. Increased impulsivity was found in smokers, associated with decreased functional connectivity of the non-reward-related lateral orbitofrontal cortex; and increased impulsivity was found in high amount drinkers, associated with increased functional connectivity of the reward-related medial orbitofrontal cortex. The main findings were cross-validated in an independent longitudinal dataset with 1176 participants, IMAGEN. Further, the functional connectivities in 14-year-old non-smokers (and also in female low-drinkers) were related to who would smoke or drink at age 19. An implication is that these differences in brain functional connectivities play a role in smoking and drinking, together with other factors.

Data availability

The dataset used in this study and custom code is available at Dryad.

The following data sets were generated

Article and author information

Author details

  1. Wei Cheng

    Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
    For correspondence
    chengwei06170323@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
  2. Edmund T Rolls

    Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
    For correspondence
    edmund.rolls@oxcns.org
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3025-1292
  3. Trevor W Robbins

    Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Weikang Gong

    Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  5. Zhaowen Liu

    School of Computer Science and Technology, Xidian University, Xi'an, China
    Competing interests
    The authors declare that no competing interests exist.
  6. Wujun Lv

    School of Mathematics, Shanghai University Finance and Economics, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  7. Jingnan Du

    Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  8. Hongkai Wen

    Department of Computer Science, University of Warwick, Coventry, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  9. Liang Ma

    Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  10. Erin Burke Quinlan

    Centre for Population Neuroscience and Stratified Medicine (PONS), King's College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  11. Hugh Garavan

    Department of Psychiatry, University of Vermont, Vermont, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Eric Artiges

    Institut National de la Santé et de la Recherche Médicale, University Paris Descartes, Orsay, France
    Competing interests
    The authors declare that no competing interests exist.
  13. Dimitri Papadopoulos Orfanos

    NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1242-8990
  14. Michael N Smolka

    Department of Psychiatry, Technische Universität Dresden, Dresden, Germany
    Competing interests
    The authors declare that no competing interests exist.
  15. Gunter Schumann

    Centre for Population Neuroscience and Stratified Medicine (PONS), King's College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  16. Keith Kendrick

    Key Laboratory for Neuroinformation of the Ministry of Education, School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0371-5904
  17. Jianfeng Feng

    Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
    For correspondence
    jianfeng64@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5987-2258

Funding

National Natural Science Foundation of China (71661167002)

  • Jianfeng Feng

The Key Project of Shanghai Science & Technology Innovation Plan (16JC1420402)

  • Jianfeng Feng

National Natural Science Foundation of China (81701773)

  • Wei Cheng

Shanghai Sailing Program (17YF1426200)

  • Wei Cheng

Natural Science Foundation of Shanghai (18ZR1404400)

  • Wei Cheng

The Key Project of Shanghai Science & Technology Innovation Plan (15JC1400101)

  • Jianfeng Feng

The Shanghai AI Platform for Diagnosis and Treatment of Brain Diseases (2016-17)

  • Jianfeng Feng

Base for Introducing Talents of Discipline to Universities (B18015)

  • Jianfeng Feng

National Natural Science Foundation of China (91630314)

  • Jianfeng Feng

National Natural Science Foundation of China (11771010)

  • Wei Cheng

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: The WU-Minn HCP Consortium obtained full informed consent from all participants, and research procedures and ethical guidelines were followed in accordance with the Washington University Institutional Review Boards (IRB #201204036; Title: 'Mapping the Human Connectome: Structure, Function, and Heritability').

Copyright

© 2019, Cheng et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 5,585
    views
  • 643
    downloads
  • 45
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Wei Cheng
  2. Edmund T Rolls
  3. Trevor W Robbins
  4. Weikang Gong
  5. Zhaowen Liu
  6. Wujun Lv
  7. Jingnan Du
  8. Hongkai Wen
  9. Liang Ma
  10. Erin Burke Quinlan
  11. Hugh Garavan
  12. Eric Artiges
  13. Dimitri Papadopoulos Orfanos
  14. Michael N Smolka
  15. Gunter Schumann
  16. Keith Kendrick
  17. Jianfeng Feng
(2019)
Decreased brain connectivity in smoking contrasts with increased connectivity in drinking
eLife 8:e40765.
https://doi.org/10.7554/eLife.40765

Share this article

https://doi.org/10.7554/eLife.40765

Further reading

    1. Neuroscience
    Franziska Auer, Katherine Nardone ... David Schoppik
    Research Article

    Cerebellar dysfunction leads to postural instability. Recent work in freely moving rodents has transformed investigations of cerebellar contributions to posture. However, the combined complexity of terrestrial locomotion and the rodent cerebellum motivate new approaches to perturb cerebellar function in simpler vertebrates. Here, we adapted a validated chemogenetic tool (TRPV1/capsaicin) to describe the role of Purkinje cells — the output neurons of the cerebellar cortex — as larval zebrafish swam freely in depth. We achieved both bidirectional control (activation and ablation) of Purkinje cells while performing quantitative high-throughput assessment of posture and locomotion. Activation modified postural control in the pitch (nose-up/nose-down) axis. Similarly, ablations disrupted pitch-axis posture and fin-body coordination responsible for climbs. Postural disruption was more widespread in older larvae, offering a window into emergent roles for the developing cerebellum in the control of posture. Finally, we found that activity in Purkinje cells could individually and collectively encode tilt direction, a key feature of postural control neurons. Our findings delineate an expected role for the cerebellum in postural control and vestibular sensation in larval zebrafish, establishing the validity of TRPV1/capsaicin-mediated perturbations in a simple, genetically tractable vertebrate. Moreover, by comparing the contributions of Purkinje cell ablations to posture in time, we uncover signatures of emerging cerebellar control of posture across early development. This work takes a major step towards understanding an ancestral role of the cerebellum in regulating postural maturation.

    1. Neuroscience
    Gáspár Oláh, Rajmund Lákovics ... Gábor Tamás
    Research Article

    Human-specific cognitive abilities depend on information processing in the cerebral cortex, where the neurons are significantly larger and their processes longer and sparser compared to rodents. We found that, in synaptically connected layer 2/3 pyramidal cells (L2/3 PCs), the delay in signal propagation from soma to soma is similar in humans and rodents. To compensate for the longer processes of neurons, membrane potential changes in human axons and/or dendrites must propagate faster. Axonal and dendritic recordings show that the propagation speed of action potentials (APs) is similar in human and rat axons, but the forward propagation of excitatory postsynaptic potentials (EPSPs) and the backward propagation of APs are 26 and 47% faster in human dendrites, respectively. Experimentally-based detailed biophysical models have shown that the key factor responsible for the accelerated EPSP propagation in human cortical dendrites is the large conductance load imposed at the soma by the large basal dendritic tree. Additionally, larger dendritic diameters and differences in cable and ion channel properties in humans contribute to enhanced signal propagation. Our integrative experimental and modeling study provides new insights into the scaling rules that help maintain information processing speed albeit the large and sparse neurons in the human cortex.