Addictions NeuroImaging Assessment (ANIA): Towards an integrative framework for alcohol use disorder

NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS

卷:113

Review

Voon, Valerie^1,2,3  Grodin, Erica⁴  Mandali, Alekhya¹  Morris, Laurel^2,5  Donamayor, Nuria¹  Weidacker, Kathrin¹  Kwako, Laura⁶  Goldman, David⁶  Koob, George F.⁶  Momenan, Reza⁴ 

[1] Univ Cambridge, Dept Psychiat, Cambridge, England

[2] Behav & Clin Neurosci Inst, Cambridge, England

[3] Cambridgeshire & Peterborough NHS Trust, Cambridge, England

[4] Natl Inst Hlth, Natl Inst Alcohol Abuse & Alcoholism, Clin NeuroImaging Res Core, London, England

[5] Univ Cambridge, Dept Psychol, Cambridge, England

[6] Natl Inst Hlth, Natl Inst Alcohol Abuse & Alcoholism, London, England

关键词: Alcohol use disorder;    Alcohol dependence;    Binge drinking;    MRI;    PET;   

DOI  :  10.1016/j.neubiorev.2020.04.004

来源: Elsevier

【 摘 要 】

Alcohol misuse and addiction are major international public health issues. Addiction can be characterized as a disorder of aberrant neurocircuitry interacting with environmental, genetic and social factors. Neuroimaging in alcohol misuse can thus provide a critical window into underlying neural mechanisms, highlighting possible treatment targets and acting as clinical biomarkers for predicting risk and treatment outcomes. This neuroimaging review on alcohol misuse in humans follows the Addictions Neuroclinical Assessment (ANA) that proposes incorporating three functional neuroscience domains integral to the neurocircuitry of addiction: incentive salience and habits, negative emotional states, and executive function within the context of the addiction cycle. Here we review and integrate multiple imaging modalities focusing on underlying cognitive processes such as reward anticipation, negative emotionality, cue reactivity, impulsivity, compulsivity and executive function. We highlight limitations in the literature and propose a model forward in the use of neuroimaging as a tool to understanding underlying mechanisms and potential clinical applicability for phenotyping of heterogeneity and predicting risk and treatment outcomes.

【 授权许可】

Free