A robust brain network for sustained attention from adolescence to adulthood that predicts later substance use

Substance use, including cigarettes and cannabis, is associated with poorer sustained attention in late adolescence and early adulthood. Previous studies were predominantly cross-sectional or under-powered and could not indicate if impairment in sustained attention was a consequence of substance-use or a marker of the inclination to engage in such behaviour. This study explored the relationship between sustained attention and substance use across a longitudinal span from ages 14 to 23 in over 1,000 participants. Behaviours and brain connectivity associated with diminished sustained attention at age 14 predicted subsequent increases in cannabis and cigarette smoking, establishing sustained attention as a robust biomarker for vulnerability to substance use. Individual differences in network strength relevant to sustained attention were preserved across developmental stages and sustained attention networks generalized to participants in an external dataset. In summary, brain networks of sustained attention are robust, consistent, and able to predict aspects of later substance use. Teaser A robust brain network for sustained attention at age 14 predicts cigarette and cannabis use from ages 14 to 23.

[1]  T. Paus,et al.  Trajectories of cortical structures associated with stress across adolescence: a bivariate latent change score approach , 2023, Journal of child psychology and psychiatry, and allied disciplines.

[2]  A. Dale,et al.  Task fMRI paradigms may capture more behaviorally relevant information than resting-state functional connectivity , 2023, NeuroImage.

[3]  F. Volkmar,et al.  A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth , 2022, medRxiv.

[4]  Christopher L. Asplund,et al.  Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study , 2022, Nature Communications.

[5]  T. Paus,et al.  A Developmental Perspective on Facets of Impulsivity and Brain Activity Correlates From Adolescence to Adulthood , 2022, Biological psychiatry. Cognitive neuroscience and neuroimaging.

[6]  P. Faure,et al.  Chronic nicotine increases midbrain dopamine neuron activity and biases individual strategies towards reduced exploration in mice , 2021, Nature Communications.

[7]  Sachiko Hara,et al.  Influence of Alcohol and Acetaldehyde on Cognitive Function: Findings from An Alcohol Clamp Study in Healthy Young Adults. , 2021, Addiction.

[8]  Vasant Honavar,et al.  Feeding the machine: Challenges to reproducible predictive modeling in resting-state connectomics , 2021, Network Neuroscience.

[9]  C. Larson,et al.  Resting state functional connectivity in the default mode network: Relationships between cannabis use, gender, and cognition in adolescents and young adults , 2021, NeuroImage: Clinical.

[10]  L. Brose,et al.  Cannabis use and co-use in tobacco smokers and non-smokers: prevalence and associations with mental health in a cross-sectional, nationally representative sample of adults in Great Britain, 2020. , 2020, Addiction.

[11]  Martin R. West,et al.  Mindfulness training preserves sustained attention and resting state anticorrelation between default‐mode network and dorsolateral prefrontal cortex: A randomized controlled trial , 2020, Human brain mapping.

[12]  B. Biswal,et al.  Common and separable neural alterations in substance use disorders: A coordinate‐based meta‐analyses of functional neuroimaging studies in humans , 2020, Human brain mapping.

[13]  S. Ferguson,et al.  One Is Not Enough: Understanding and Modeling Polysubstance Use , 2020, Frontiers in Neuroscience.

[14]  Y. Hurd,et al.  Deconstructing the neurobiology of cannabis use disorder , 2020, Nature Neuroscience.

[15]  Abigail S. Greene,et al.  Functional connectivity predicts changes in attention observed across minutes, days, and months , 2020, Proceedings of the National Academy of Sciences.

[16]  R. Wise,et al.  Dopamine and Addiction. , 2020, Annual review of psychology.

[17]  J. Steele,et al.  Neurocognitive consequences of chronic cannabis use: a systematic review and meta-analysis , 2019, Neuroscience & Biobehavioral Reviews.

[18]  D. Scheinost,et al.  Dissociable neural substrates of opioid and cocaine use identified via connectome-based modelling , 2019, Molecular Psychiatry.

[19]  M. Esterman,et al.  Models of sustained attention. , 2019, Current opinion in psychology.

[20]  C. Sripada,et al.  Prediction of neurocognition in youth from resting state fMRI , 2019, Molecular Psychiatry.

[21]  B. Waterhouse,et al.  Selective activation of Dopamine D3 receptors and norepinephrine transporter blockade enhances sustained attention , 2019, Neuropharmacology.

[22]  Hans Colonius,et al.  A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task , 2019, eLife.

[23]  Dustin Scheinost,et al.  Connectome-Based Prediction of Cocaine Abstinence. , 2019, The American journal of psychiatry.

[24]  N. Wade,et al.  Effects of Cannabis Use and Subclinical ADHD Symptomology on Attention Based Tasks in Adolescents and Young Adults. , 2018, Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists.

[25]  B. Franke,et al.  Genome-wide association study reveals novel genetic locus associated with intra-individual variability in response time , 2018, Translational Psychiatry.

[26]  M. Zvolensky,et al.  Trends in cannabis use disorder by cigarette smoking status in the United States, 2002-2016. , 2018, Drug and alcohol dependence.

[27]  Dustin Scheinost,et al.  Task-induced brain state manipulation improves prediction of individual traits , 2018, Nature Communications.

[28]  Xin Di,et al.  Toward Task Connectomics: Examining Whole-Brain Task Modulated Connectivity in Different Task Domains , 2018, Cerebral cortex.

[29]  Vincent Frouin,et al.  Neural circuitry underlying sustained attention in healthy adolescents and in ADHD symptomatology , 2018, NeuroImage.

[30]  Dustin Scheinost,et al.  Connectome-based predictive modeling of attention: Comparing different functional connectivity features and prediction methods across datasets , 2018, NeuroImage.

[31]  Dustin Scheinost,et al.  Connectome-based Models Predict Separable Components of Attention in Novel Individuals , 2018, Journal of Cognitive Neuroscience.

[32]  S. Kelly,et al.  The Effects of Methylphenidate on the Neural Signatures of Sustained Attention , 2017, Biological Psychiatry.

[33]  M. Chun,et al.  Using connectome-based predictive modeling to predict individual behavior from brain connectivity , 2017, Nature Protocols.

[34]  J. Ferris,et al.  No Smoke without Tobacco: A Global Overview of Cannabis and Tobacco Routes of Administration and Their Association with Intention to Quit , 2016, Front. Psychiatry.

[35]  M. Yücel,et al.  Acute and Chronic Effects of Cannabinoids on Human Cognition—A Systematic Review , 2016, Biological Psychiatry.

[36]  G. Willemsen,et al.  Smoking During Adolescence as a Risk Factor for Attention Problems , 2015, Biological Psychiatry.

[37]  M. Chun,et al.  A neuromarker of sustained attention from whole-brain functional connectivity , 2015, Nature Neuroscience.

[38]  Francesca C. Fortenbaugh,et al.  Sustained Attention Across the Life Span in a Sample of 10,000 , 2015, Psychological science.

[39]  A. Childress,et al.  Cannabis, Cigarettes, and Their Co-Occurring Use: Disentangling Differences in Gray Matter Volume , 2015, The international journal of neuropsychopharmacology.

[40]  A. Awad,et al.  Revisiting the ‘self-medication’ hypothesis in light of the new data linking low striatal dopamine to comorbid addictive behavior , 2015, Therapeutic advances in psychopharmacology.

[41]  M. Rietschel,et al.  Neuropsychosocial profiles of current and future adolescent alcohol misusers , 2014, Nature.

[42]  Mariya V. Cherkasova,et al.  Reduced Dopamine Response to Amphetamine in Subjects at Ultra-High Risk for Addiction , 2014, Biological Psychiatry.

[43]  D. Martínez,et al.  Blunted Dopamine Release as a Biomarker for Vulnerability for Substance Use Disorders , 2014, Biological Psychiatry.

[44]  Brenda Happell,et al.  On exploratory factor analysis: a review of recent evidence, an assessment of current practice, and recommendations for future use. , 2014, International journal of nursing studies.

[45]  Xenophon Papademetris,et al.  Groupwise whole-brain parcellation from resting-state fMRI data for network node identification , 2013, NeuroImage.

[46]  L. Dwoskin,et al.  Angiotensin AT1 and AT2 receptor antagonists modulate nicotine-evoked [³H]dopamine and [³H]norepinephrine release. , 2013, Biochemical pharmacology.

[47]  D. Dougherty,et al.  Impulsivity, attention, memory, and decision-making among adolescent marijuana users , 2013, Psychopharmacology.

[48]  P. Fitzgerald Elevated Norepinephrine may be a Unifying Etiological Factor in the Abuse of a Broad Range of Substances: Alcohol, Nicotine, Marijuana, Heroin, Cocaine, and Caffeine , 2013, Substance abuse : research and treatment.

[49]  J. Ormel,et al.  The association between neurocognitive functioning and smoking in adolescence: the TRAILS study. , 2012, Neuropsychology.

[50]  L. Schreiber,et al.  Association between tobacco smoking and cognitive functioning in young adults. , 2012, The American journal on addictions.

[51]  A. Agrawal,et al.  The co-occurring use and misuse of cannabis and tobacco: a review. , 2012, Addiction.

[52]  M. Rietschel,et al.  Adolescent impulsivity phenotypes characterized by distinct brain networks , 2012, Nature Neuroscience.

[53]  G. Fink,et al.  Spatial and sustained attention in relation to smoking status: behavioural performance and brain activation patterns , 2011, Journal of psychopharmacology.

[54]  D. Dougherty,et al.  Cognitive Impairments in Adolescent Cannabis Users are Related to THC Levels , 2010 .

[55]  L. Eaves,et al.  Mechanisms underlying the lifetime co-occurrence of tobacco and cannabis use in adolescent and young adult twins. , 2010, Drug and alcohol dependence.

[56]  M. Gill,et al.  Noradrenergic genotype predicts lapses in sustained attention , 2009, Neuropsychologia.

[57]  Matthijs G. Bossong,et al.  Delta 9-tetrahydrocannabinol induces dopamine release in the human striatum , 2008, NeuroImage.

[58]  K. Kanyas,et al.  Why do young women smoke? III. Attention and impulsivity as neurocognitive predisposing factors , 2007, European Neuropsychopharmacology.

[59]  Young T. Hong,et al.  Nucleus Accumbens D2/3 Receptors Predict Trait Impulsivity and Cocaine Reinforcement , 2007, Science.

[60]  Frank Telang,et al.  High levels of dopamine D2 receptors in unaffected members of alcoholic families: possible protective factors. , 2006, Archives of general psychiatry.

[61]  Robert H Mach,et al.  PET imaging of dopamine D2 receptors during chronic cocaine self-administration in monkeys , 2006, Nature Neuroscience.

[62]  T. Paus Mapping brain maturation and cognitive development during adolescence , 2005, Trends in Cognitive Sciences.

[63]  M. Nader,et al.  Social dominance in monkeys: dopamine D2 receptors and cocaine self-administration , 2002, Nature Neuroscience.

[64]  G. Yamey Abstinence , 2000, BMJ : British Medical Journal.

[65]  M. Sarter,et al.  Sustained Visual Attention Performance-Associated Prefrontal Neuronal Activity: Evidence for Cholinergic Modulation , 2000, The Journal of Neuroscience.

[66]  Trevor W. Robbins,et al.  Enhanced and Impaired Attentional Performance After Infusion of D1 Dopaminergic Receptor Agents into Rat Prefrontal Cortex , 2000, The Journal of Neuroscience.

[67]  L. Sobell,et al.  The reliability of the Alcohol Timeline Followback when administered by telephone and by computer. , 1996, Drug and alcohol dependence.

[68]  T. Robbins,et al.  Neuorpsychiatyric applications of CANTAB , 1996 .

[69]  A. Petersen,et al.  A self-report measure of pubertal status: Reliability, validity, and initial norms , 1988, Journal of youth and adolescence.

[70]  Sustained Attention , 2021, Encyclopedia of Evolutionary Psychological Science.

[71]  D. Martínez,et al.  Blunted Dopamine Transmission in Addiction: Potential Mechanisms and Implications for Behavior. , 2017, Seminars in nuclear medicine.

[72]  J. Binder,et al.  Across the Life Span , 2013 .

[73]  E. Strauss,et al.  Inconsistency in reaction time across the life span. , 2005, Neuropsychology.

[74]  L. Role,et al.  Physiological diversity of nicotinic acetylcholine receptors expressed by vertebrate neurons. , 1995, Annual review of physiology.

[75]  J. Galloway A Review of the , 1901 .