Addiction Research Consortium: Losing and regaining control over drug intake (ReCoDe)-From trajectories to mechanisms and interventions.

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
  • Additional Information
    • Source:
      Publisher: Wiley-Blackwell Country of Publication: United States NLM ID: 9604935 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1369-1600 (Electronic) Linking ISSN: 13556215 NLM ISO Abbreviation: Addict Biol Subsets: MEDLINE
    • Publication Information:
      Publication: Hoboken, NJ : Wiley-Blackwell
      Original Publication: Abingdon, Oxfordshire, UK ; Cambridge, MA : Carfax, c1996-
    • Subject Terms:
    • Abstract:
      One of the major risk factors for global death and disability is alcohol, tobacco, and illicit drug use. While there is increasing knowledge with respect to individual factors promoting the initiation and maintenance of substance use disorders (SUDs), disease trajectories involved in losing and regaining control over drug intake (ReCoDe) are still not well described. Our newly formed German Collaborative Research Centre (CRC) on ReCoDe has an interdisciplinary approach funded by the German Research Foundation (DFG) with a 12-year perspective. The main goals of our research consortium are (i) to identify triggers and modifying factors that longitudinally modulate the trajectories of losing and regaining control over drug consumption in real life, (ii) to study underlying behavioral, cognitive, and neurobiological mechanisms, and (iii) to implicate mechanism-based interventions. These goals will be achieved by: (i) using mobile health (m-health) tools to longitudinally monitor the effects of triggers (drug cues, stressors, and priming doses) and modify factors (eg, age, gender, physical activity, and cognitive control) on drug consumption patterns in real-life conditions and in animal models of addiction; (ii) the identification and computational modeling of key mechanisms mediating the effects of such triggers and modifying factors on goal-directed, habitual, and compulsive aspects of behavior from human studies and animal models; and (iii) developing and testing interventions that specifically target the underlying mechanisms for regaining control over drug intake.
      (© 2019 The Authors. Addiction Biology published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.)
    • References:
      Helzer JE, Robins LN, Taylor JR, et al. The extent of long-term moderate drinking among alcoholics discharged from medical and psychiatric treatment facilities. N Engl J Med. 1985;312(26):1678-1682.
      Imber S, Schultz E, Funderburk F, Allen R, Flamer R. The fate of the untreated alcoholic. Toward a natural history of the disorder. J Nerv Ment Dis. 1976;162(4):238-247.
      Sobell LC, Ellingstad TP, Sobell MB. Natural recovery from alcohol and drug problems: methodological review of the research with suggestions for future directions. Addiction. 2000;95(5):749-764.
      Swift W, Coffey C, Degenhardt L, Carlin JB, Romaniuk H, Patton GC. Cannabis and progression to other substance use in young adults: findings from a 13-year prospective population-based study. J Epidemiol Community Health. 2012;66(7):e26.
      Mann K, Schafer DR, Langle G, Ackermann K, Croissant B. The long-term course of alcoholism, 5, 10 and 16 years after treatment. Addiction. 2005;100(6):797-805.
      Gladwin TE, Wiers CE, Wiers RW. Cognitive neuroscience of cognitive retraining for addiction medicine: from mediating mechanisms to questions of efficacy. Prog Brain Res. 2016;224:323-344.
      Rezapour T, DeVito EE, Sofuoglu M, Ekhtiari H. Perspectives on neurocognitive rehabilitation as an adjunct treatment for addictive disorders: from cognitive improvement to relapse prevention. Prog Brain Res. 2016;224:345-369.
      Heinz A, Beck A, Halil MG, Pilhatsch M, Smolka MN, Liu S. Addiction as learned behavior patterns. J Clin Med. 2019;8:1086-1095.
      Rapp MA, Schnaider-Beeri M, Wysocki M, et al. Cognitive decline in patients with dementia as a function of depression. Am J Geriatr Psychiatry. 2011;19(4):357-363.
      Serre F, Fatseas M, Swendsen J, Auriacombe M. Ecological momentary assessment in the investigation of craving and substance use in daily life: a systematic review. Drug Alcohol Depend. 2015;148:1-20.
      Brown HR, Zeidman P, Smittenaar P, et al. Crowdsourcing for cognitive science-the utility of smartphones. PLoS One. 2014;9:e100662.
      Foo JC, Noori HR, Yamaguchi I, et al. Dynamical state transitions into addictive behaviour and their early-warning signals. Proc Biol Sci. 2017;284.
      Durstewitz D, Koppe G, Meyer-Lindenberg A. Deep neural networks in psychiatry. Mol Psychiatry. 2019;24(11):1583-1598.
      Meinhardt MW, Sommer WH. Postdependent state in rats as a model for medication development in alcoholism. Addict Biol. 2015;20(1):1-21.
      Spanagel R. Animal models of addiction. Dialogues Clin Neurosci. 2017;19(3):247-258.
      Goldman D, Oroszi G, Ducci F. The genetics of addictions: uncovering the genes. Nat Rev Genet. 2005;6:521-532.
      Kirsch M, Gruber I, Ruf M, Kiefer F, Kirsch P. Real-time functional magnetic resonance imaging neurofeedback can reduce striatal cue-reactivity to alcohol stimuli. Addict Biol. 2016;21(4):982-992.
    • Grant Information:
      TRR265 International Deutsche Forschungsgemeinschaft; International German Research Foundation
    • Contributed Indexing:
      Keywords: addiction; alternative rewards; animal and computational models; cognitive-behavioral control; craving and relapse; habit formation
    • Publication Date:
      Date Created: 20191221 Date Completed: 20210216 Latest Revision: 20210317
    • Publication Date:
      20240105
    • Accession Number:
      10.1111/adb.12866
    • Accession Number:
      31859437