The neurobiology of addiction: the perspective from magnetic resonance imaging present and future.

BACKGROUND AND AIMS: Addiction is associated with severe economic and social consequences and personal tragedies, the scientific exploration of which draws upon investigations at the molecular, cellular and systems levels with a wide variety of technologies. Magnetic resonance imaging (MRI) has been key to mapping effects observed at the microscopic and mesoscopic scales. The range of measurements from this apparatus has opened new avenues linking neurobiology to behaviour. This review considers the role of MRI in addiction research, and what future technological improvements might offer. METHODS: A hermeneutic strategy supplemented by an expansive, systematic search of PubMed, Scopus and Web of Science databases, covering from database inception to October 2015, with a conjunction of search terms relevant to addiction and MRI. Formal meta-analyses were prioritized. RESULTS: Results from methods that probe brain structure and function suggest frontostriatal circuitry disturbances within specific cognitive domains, some of which predict drug relapse and treatment response. New methods of processing imaging data are opening opportunities for understanding the role of cerebral vasculature, a global view of brain communication and the complex topology of the cortical surface and drug action. Future technological advances include increases in MRI field strength, with concomitant improvements in image quality. CONCLUSIONS: The magnetic resonance imaging literature provides a limited but convergent picture of the neurobiology of addiction as global changes to brain structure and functional disturbances to frontostriatal circuitry, accompanied by changes in anterior white matter.The authors receive support from the Behavioural and Clinical Neuroscience Institute, jointly funded by the Medical Research Council and the Wellcome Trust, and the National Institute for Health Research Cambridge Biomedical Research Centre.This is the author accepted manuscript. The final version is available from Wiley via https://doi.org doi:10.1111/add.1347

Cannabis-dependent adolescents show differences in global reward-associated network topology: A functional connectomics approach.

Adolescence may be a period of increased vulnerability to the onset of drug misuse and addiction due to changes in developing brain networks that support cognitive and reward processing. Cannabis is a widely misused illicit drug in adolescence which can lead to dependence and alterations in reward-related neural functioning. Concerns exist that cannabis-related alterations in these reward networks in adolescence may sensitize behaviour towards all forms of reward that increase the risk of further drug use. Taking a functional connectomics approach, we compared an acutely abstinent adolescent cannabis-dependent (CAN) group with adolescent controls (CON) on global measures of network topology associated with anticipation on a monetary incentive delay task. In the presence of overall superior accuracy, the CAN group exhibited superior global connectivity (clustering coefficient, efficiency, characteristic path length) during monetary gain anticipation compared with the CON group. Additional analyses showed that the CAN group exhibited significantly greater connectivity strength during monetary gain anticipation across a subnetwork that included mesocorticolimbic nodes involving both interhemispheric and intrahemispheric connections. We discuss how these differences in reward-associated connectivity may allude to subtle functional alterations in network architecture in adolescent cannabis-dependence that could enhance the motivation for nondrug reward during acute abstinence

Differential effects of Down's syndrome and Alzheimer's neuropathology on default mode connectivity.

Down's syndrome is a chromosomal disorder that invariably results in both intellectual disability and Alzheimer's disease neuropathology. However, only a limited number of studies to date have investigated intrinsic brain network organisation in people with Down's syndrome, none of which addressed the links between functional connectivity and Alzheimer's disease. In this cross-sectional study, we employed 11 C-Pittsburgh Compound-B (PiB) positron emission tomography in order to group participants with Down's syndrome based on the presence of fibrillar beta-amyloid neuropathology. We also acquired resting state functional magnetic resonance imaging data to interrogate the connectivity of the default mode network; a large-scale system with demonstrated links to Alzheimer's disease. The results revealed widespread positive connectivity of the default mode network in people with Down's syndrome (n = 34, ages 30-55, median age = 43.5) and a stark lack of anti-correlation. However, in contrast to typically developing controls (n = 20, ages 30-55, median age = 43.5), the Down's syndrome group also showed significantly weaker connections in localised frontal and posterior brain regions. Notably, while a comparison of the PiB-negative Down's syndrome group (n = 19, ages 30-48, median age = 41.0) to controls suggested that alterations in default mode connectivity to frontal brain regions are related to atypical development, a comparison of the PiB-positive (n = 15, ages 39-55, median age = 48.0) and PiB-negative Down's syndrome groups indicated that aberrant connectivity in posterior cortices is associated with the presence of Alzheimer's disease neuropathology. Such distinct profiles of altered connectivity not only further our understanding of the brain physiology that underlies these two inherently linked conditions but may also potentially provide a biomarker for future studies of neurodegeneration in people with Down's syndrome

Delineating the topography of amyloid-associated cortical atrophy in Down syndrome

Older adults with Down syndrome (DS) often have Alzheimer's disease (AD) neuropathologies. Although positron emission tomography imaging studies of amyloid deposition (beta amyloid, Aβ) have been associated with worse clinical prognosis and cognitive impairment, their relationships with cortical thickness remain unclear in people with DS. In a sample of 44 DS adults who underwent cognitive assessments, [C]-PiB positron emission tomography, and T1-weighted magnetization-prepared rapid gradient echo, we used mixed effect models to evaluate the spatial relationships between Aβ binding with patterns of cortical thickness. Partial Spearman correlations were used to delineate the topography of local Aβ-associated cortical thinning. [C]-PiB nondisplaceable binding potential was negatively associated with decreased cortical thickness. Locally, regional [C]-PiB retention was negatively correlated with cortical thickness in widespread cortices, predominantly in temporoparietal regions. Contrary to the prevailing evidence in established AD, we propose that our findings implicate Aβ in spatial patterns of atrophy that recapitulated the “cortical signature” of neurodegeneration in AD, conferring support to recent recommendations for earlier disease-interventions

Brain-predicted age in Down syndrome is associated with beta amyloid deposition and cognitive decline

Individuals with Down Syndrome (DS) are more likely to experience earlier onset of multiple facets of physiological ageing. This includes brain atrophy, β-amyloid deposition, cognitive decline and Alzheimer’s Disease; factors indicative of brain ageing. Here we employed a machine learning approach, using structural neuroimaging data to predict age (i.e., brain-predicted age) in people with DS (N = 46) and typically developing controls (N = 30). Chronological age was then subtracted from brain-predicted age to generate a brain-predicted age difference (brain-PAD) score. DS participants also underwent [11C]-PiB positron emission tomography (PET) scans to index levels of cerebral β-amyloid deposition, and cognitive assessment. Mean brain-PAD in DS participants’ was +2.49 years, significantly greater than controls (p<0.001). The variability in brain-PAD was associated with the presence and the magnitude of PIB-binding and levels of cognitive performance. Our study indicates that DS is associated with premature structural brain ageing, and that age-related alterations in brain structure are associated with individual differences in the rate of β-amyloid deposition and cognitive impairment

Longitudinal trajectories of amyloid deposition, cortical thickness, and tau in Down syndrome: A deep-phenotyping case report.

Introduction:Comorbid Alzheimer disease pathologies are frequently found in people with Down syndrome (DS). We report a deep phenotyping study undertaken over 7 years in a participant with DS who was nondemented at baseline but developed dementia after 5 years. Methods:Throughout the course of the study, the participant was seen 4 times (2010, 2013, 2015, and 2017). Multimodal neuroimaging, including three serial scans of [11C]-PiB-PET, four structural magnetic resonance imagings, as well as a [18F]-AV1451 scan, was interpreted alongside detailed neuropsychological assessments over the study period. Results:Amyloid beta accumulation preceded the onset of dementia and cognitive decline, which in turn corresponded to the predominant deposition of tau in temporoparietal cortices. Discussion:Until now, data on the longitudinal trajectories of amyloid accumulation, tau pathology, and brain atrophy over multiple time points remain scarce in DS. This case report highlights the potential for deep phenotyping imaging to elucidate the substrates of cognitive decline in DS, although further longitudinal studies are necessary to clarify the relative contributions of both amyloid and tau

Disturbances across whole brain networks during reward anticipation in an abstinent addiction population.

The prevalent spatial distribution of abnormalities reported in cognitive fMRI studies in addiction suggests there are extensive disruptions across whole brain networks. Studies using resting state have reported disruptions in network connectivity in addiction, but these studies have not revealed characteristics of network functioning during critical psychological processes that are disrupted in addiction populations. Analytic methods that can capture key features of whole brain networks during psychological processes may be more sensitive in revealing additional and widespread neural disturbances in addiction, that are the provisions for relapse risk, and targets for medication development. The current study compared a substance addiction (ADD; n = 83) group in extended abstinence with a control (CON; n = 68) group on functional MRI (voxel-wise activation) and global network (connectivity) measures related to reward anticipation on a monetary incentive delay task. In the absence of group differences on MID performance, the ADD group showed reduced activation predominantly across temporal and visual regions, but not across the striatum. The ADD group also showed disruptions in global network connectivity (lower clustering coefficient and higher characteristic path length), and significantly less connectivity across a sub-network comprising frontal, temporal, limbic and striatal nodes. These results show that an addiction group in extended abstinence exhibit localised disruptions in brain activation, but more extensive disturbances in functional connectivity across whole brain networks. We propose that measures of global network functioning may be more sensitive in highlighting latent and more widespread neural disruptions during critical psychological processes in addiction and other psychiatric disorders

The ICCAM platform study: An experimental medicine platform for evaluating new drugs for relapse prevention in addiction. Part B: fMRI description.

OBJECTIVES: We aimed to set up a robust multi-centre clinical fMRI and neuropsychological platform to investigate the neuropharmacology of brain processes relevant to addiction - reward, impulsivity and emotional reactivity. Here we provide an overview of the fMRI battery, carried out across three centres, characterizing neuronal response to the tasks, along with exploring inter-centre differences in healthy participants. EXPERIMENTAL DESIGN: Three fMRI tasks were used: monetary incentive delay to probe reward sensitivity, go/no-go to probe impulsivity and an evocative images task to probe emotional reactivity. A coordinate-based activation likelihood estimation (ALE) meta-analysis was carried out for the reward and impulsivity tasks to help establish region of interest (ROI) placement. A group of healthy participants was recruited from across three centres (total n=43) to investigate inter-centre differences. Principle observations: The pattern of response observed for each of the three tasks was consistent with previous studies using similar paradigms. At the whole brain level, significant differences were not observed between centres for any task. CONCLUSIONS: In developing this platform we successfully integrated neuroimaging data from three centres, adapted validated tasks and applied whole brain and ROI approaches to explore and demonstrate their consistency across centres.Medical Research Council (Grant ID: G1000018), GlaxoSmithKlineThis is the author accepted manuscript. The final version is available from SAGE Publications via http://dx.doi.org/10.1177/026988111666859

Impulsivity in abstinent alcohol and polydrug dependence: a multidimensional approach.

RATIONALE: Dependence on drugs and alcohol is associated with impaired impulse control, but deficits are rarely compared across individuals dependent on different substances using several measures within a single study. OBJECTIVES: We investigated impulsivity in abstinent substance-dependent individuals (AbD) using three complementary techniques: self-report, neuropsychological and neuroimaging. We hypothesised that AbDs would show increased impulsivity across modalities, and that this would depend on length of abstinence. METHODS: Data were collected from the ICCAM study: 57 control and 86 AbDs, comprising a group with a history of dependence on alcohol only (n = 27) and a group with history of dependence on multiple substances ("polydrug", n = 59). All participants completed self-report measures of impulsivity: Barratt Impulsiveness Scale, UPPS Impulsive Behaviour Scale, Behaviour Inhibition/Activation System and Obsessive-Compulsive Inventory. They also performed three behavioural tasks: Stop Signal, Intra-Extra Dimensional Set-Shift and Kirby Delay Discounting; and completed a Go/NoGo task during fMRI. RESULTS: AbDs scored significantly higher than controls on self-report measures, but alcohol and polydrug dependent groups did not differ significantly from each other. Polydrug participants had significantly higher discounting scores than both controls and alcohol participants. There were no group differences on the other behavioural measures or on the fMRI measure. CONCLUSIONS: The results suggest that the current set of self-report measures of impulsivity is more sensitive in abstinent individuals than the behavioural or fMRI measures of neuronal activity. This highlights the importance of developing behavioural measures to assess different, more relevant, aspects of impulsivity alongside corresponding cognitive challenges for fMRI.This article presents independent research funded by the Medical Research Council as part of their addiction initiative (grant number G1000018). GSK kindly funded the functional and structural MRI scans that took place at Imperial College. The research was carried out at the NIHR/Wellcome Trust Imperial Clinical Research Facility, the NIHR/Wellcome Trust Cambridge Research Facility and Clinical Trials Unit at Salford Royal NHS Foundation Trust, and is supported by the North West London, Eastern and Greater Manchester NIHR Clinical Research Networks.This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s00213-016-4245-

A social-ecological approach to identify and quantify biodiversity tipping points in South America’s seasonal dry ecosystems

ropical dry forests and savannas harbour unique biodiversity and provide critical ES, yet they are under severe pressure globally. We need to improve our understanding of how and when this pressure provokes tipping points in biodiversity and the associated social-ecological systems. We propose an approach to investigate how drivers leading to natural vegetation decline trigger biodiversity tipping and illustrate it using the example of the Dry Diagonal in South America, an understudied deforestation frontier. The Dry Diagonal represents the largest continuous area of dry forests and savannas in South America, extending over three million km² across Argentina, Bolivia, Brazil, and Paraguay. Natural vegetation in the Dry Diagonal has been undergoing large-scale transformations for the past 30 years due to massive agricultural expansion and intensification. Many signs indicate that natural vegetation decline has reached critical levels. Major research gaps prevail, however, in our understanding of how these transformations affect the unique and rich biodiversity of the Dry Diagonal, and how this affects the ecological integrity and the provisioning of ES that are critical both for local livelihoods and commercial agriculture.Fil: Thonicke, Kirsten. Institute for Climate Impact Research ; AlemaniaFil: Langerwisch, Fanny. Institute for Climate Impact Research ; Alemania. Czech University of Life Sciences Prague; República ChecaFil: Baumann, Matthias. Humboldt Universität zu Berlin; Alemania. Technische Universitat Carolo Wilhelmina Zu Braunschweig.; AlemaniaFil: Leitão, Pedro J.. Humboldt Universität zu Berlin; Alemania. Technische Universitat Carolo Wilhelmina Zu Braunschweig.; AlemaniaFil: Václavík, Tomáš. Helmholtz Centre for Environmental Research; Alemania. Palacký University Olomouc; República ChecaFil: Alencar, Anne. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; BrasilFil: Simões, Margareth. Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA); BrasilFil: Scheiter, Simon. Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA); Brasil. Universidade Federal do Rio de Janeiro; BrasilFil: Langan, Liam. Senckenberg Biodiversity and Climate Research Centre; AlemaniaFil: Bustamante, Mercedes. Universidade do Brasília; BrasilFil: Gasparri, Nestor Ignacio. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Ecología Regional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; ArgentinaFil: Hirota, Marina. Universidade Federal de Santa Catarina; Brasil. Universidade Estadual de Campinas; BrasilFil: Börner, Jan. Universitat Bonn; AlemaniaFil: Rajao, Raoni. Universidade Federal de Minas Gerais; BrasilFil: Soares Filho, Britaldo. Universidade Federal de Minas Gerais; BrasilFil: Yanosky, Alberto. Consejo Nacional de Ciencia y Tecnología; ParaguayFil: Ochoa Quinteiro, José Manuel. Instituto de Investigación de Recursos Biológicos Alexander von Humboldt; ColombiaFil: Seghezzo, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones en Energía no Convencional. Universidad Nacional de Salta. Facultad de Ciencias Exactas. Departamento de Física. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Conti, Georgina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: de la Vega Leiner, Anne Cristina. Universität Greifswald; Alemani