Psychopharmacology Unit, School of Medical Sciences, University of Bristol, UK.
British Medical Bulletin (Impact Factor: 3.66). 02/2003; 65:209-22. DOI: 10.1093/bmb/65.1.209
Source: PubMed


Alcohol and psycho-active substance misuse has far-reaching social, psychological and physical consequences. Advances in neuroimaging technology have allowed neurobiological theories of addiction to become better characterized. We describe the neurobiology of dependence, withdrawal, abstinence and craving states in alcohol, stimulant and opiate misuse. Structural neuroimaging techniques such as CT and MRI with new analytical approaches such as voxel-based morphometry have shown wide-spread changes in stimulant and opiate abuse and atrophy, particularly in the frontal lobes, in alcoholism. Functional neuroimaging techniques such as PET, SPECT and fMRI reveal altered regional cerebral activity by all drugs of abuse. The neurochemistry of addiction, particularly involving dopamine, serotonin, opiate and GABA, has been studied with PET and SPECT and similarities between all drugs of abuse have been found such as reduced dopaminergic markers. The evidence derived from these advances in neuroimaging is likely to herald the emergence of new biological treatments in this important field.

Download full-text


Available from: Simon Davies, Nov 06, 2015
1 Follower
1 Read
  • [Show abstract] [Hide abstract]
    ABSTRACT: Neurochemical imaging studies can identify molecular targets of abused drugs and link them to the underlying pathology associated with behaviors such as drug dependence, addiction and withdrawal. positron emission tomography (PET) is opening new avenues for the investigation of the neurochemical disturbances underlying drug abuse and addiction and the in vivo mechanisms by which medications might ameliorate these conditions. PET can identify vulnerable human populations, treatment strategies and monitor treatment efficacy. Thus, with this tool and the knowledge it provides, the potential for developing novel drugs and treatment strategies for drug addiction is now close at hand.
    Drug Discovery Today 05/2005; 10(8):547-62. DOI:10.1016/S1359-6446(05)03412-4 · 6.69 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The segmentation of T1-weighted images into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) is a fundamental processing step in neuroimaging, the results of which affect many other structural imaging analyses. Variability in the segmentation process can decrease the power of a study to detect anatomical differences, and minimizing such variability can lead to more robust results. This paper outlines a straightforward strategy that can be used (1) to select more optimal data acquisition and processing protocols and (2) to quantify the impact of such optimization. Using this approach with multiple scans of a single subject, we found that the choice of a segmentation algorithm had the largest impact on variability, while the choice of a pulse sequence had the second largest impact. The data indicate that the classification of GM is the most variable, and that the optimal protocol may differ across tissue types. Therefore, the intended use of segmentation data should play a role in optimization. Examples are provided to demonstrate that the minimization of variability is not sufficient for optimization; the overall accuracy of the approach must also be considered. Simple volumetric computations are included to illustrate the potential gain of optimization; these results show that volume estimates from optimal pathways were on average three times less variable than estimates from suboptimal pathways. Therefore, the simple strategy illustrated here can be applied to many studies to optimize tissue segmentation, which should lead to a net increase in the power of structural neuroimaging studies.
    NeuroImage 02/2006; 29(1):185-202. DOI:10.1016/j.neuroimage.2005.07.035 · 6.36 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The ability to characterise psychopathologies on the basis of their underlying neurobiology is critical in improving our understanding of disorder etiology and making more effective diagnostic and treatment decisions. Given the well-documented relationship between temperament (i.e. core personality traits) and psychopathology, research investigating the neurobiological substrates that underlie temperament is potentially key to our understanding of the biological basis of mental disorder. We present evidence that specific areas of the prefrontal cortex (including the dorsolateral prefrontal, anterior cingulate, and orbitofrontal cortices) and limbic structures (including the amygdala, hippocampus and nucleus accumbens) are key regions associated with three fundamental dimensions of temperament: Negative Affect, Positive Affect, and Constraint. Proposed relationships are based on two types of research: (a) research into the neurobiological correlates of affective and cognitive processes underlying these dimensions; and (b) research into the neurobiology of various psychopathologies, which have been correlated with these dimensions. A model is proposed detailing how these structures might comprise neural networks whose functioning underlies the three temperaments. Recommendations are made for future research into the neurobiology of temperament, including the need to focus on neural networks rather than individual structures, and the importance of prospective, longitudinal, multi-modal imaging studies in at-risk youth.
    Neuroscience & Biobehavioral Reviews 02/2006; 30(4):511-25. DOI:10.1016/j.neubiorev.2005.09.003 · 8.80 Impact Factor
Show more