Showing papers by "Nora D. Volkow published in 2005"

The Neural Basis of Addiction: A Pathology of Motivation and Choice

Abstract: Objective: A primary behavioral pathology in drug addiction is the overpowering motivational strength and decreased ability to control the desire to obtain drugs. In this review the authors explore how advances in neurobiology are approaching an understanding of the cellular and circuitry underpinnings of addiction, and they describe the novel pharmacotherapeutic targets emerging from this understanding. Method: Findings from neuroimaging of addicts are integrated with cellular studies in animal models of drug seeking.

How can drug addiction help us understand obesity

Abstract: To the degree that drugs and food activate common reward circuitry in the brain, drugs offer powerful tools for understanding the neural circuitry that mediates food-motivated habits and how this circuitry may be hijacked to cause appetitive behaviors to go awry.

The neuroscience of addiction.

Abstract: The burden of substance abuse and addiction to society is enormous, with an estimated annual economic impact in the United States of approximately half a trillion dollars arising from medical consequences, loss of productivity, accidents and crime1. The impact of drugs and alcohol on children is particularly problematic, as adolescents are significantly more vulnerable than adults to substance abuse and to addiction2. Also, because many of the molecular targets affected by drugs are involved with brain development, substance abuse during childhood and adolescence has the potential to be particularly deleterious. Indeed, it has been shown that children who begin using alcohol early in childhood (ages 14 or younger) are four times more vulnerable to becoming addicted to alcohol later in life than are those who begin drinking at 20 years of age or older3. Scientists are now able to portray addiction as a medical disease with physiological and molecular changes thanks to the scientific and technological advances that have occurred over the past decade. The articles in this issue highlight some of the remarkable progress that has revolutionized our understanding of the neurobiology of addiction and the way we treat it. Here we highlight some of the compelling neuroscientific questions about substance abuse, the answers for which will further improve prevention and treatment of addiction. In this editorial we use the term addiction rather than drug dependence, which is the clinical term favored by the Diagnostic and Statistical Manual of Mental Disorders (fourth edition; DSM-IV), to avoid confusion with physical dependence. Physical dependence refers to the adaptations that result in withdrawal symptoms when drugs such as alcohol and heroin are discontinued. Those are distinct from the adaptations that result in addiction, which refers to the loss of control over the intense urges to take the drug even at the expense of adverse consequences.

Activation of orbital and medial prefrontal cortex by methylphenidate in cocaine-addicted subjects but not in controls: relevance to addiction.

Abstract: Drugs of abuse are rewarding to addicted and nonaddicted subjects, but they trigger craving and compulsive intake only in addicted subjects. Here, we used positron emission tomography (PET) and [ 18 F]deoxyglucose to compare the brain metabolic responses (marker of brain function) of cocaine-addicted subjects ( n = 21) and controls ( n = 15) to identify brain regions that are uniquely activated in addicted subjects by intravenous methylphenidate (a drug that cocaine-addicted subjects report to be similar to cocaine). In parallel, we also measured the changes in dopamine (DA) induced by intravenous methylphenidate (using PET and [ 11 C]raclopride) in the striatum and in the thalamus. Metabolic responses between groups differed significantly only in the right medial orbital prefrontal cortex [Brodmann9s area (BA) 25 and medial BA 11], where methylphenidate increased metabolism in addicted subjects but decreased metabolism in controls. These changes were associated in all subjects with increased “desire for methylphenidate” and in the addicted subjects with “cocaine craving.” In addicted subjects, increases in BA 25 were also associated with mood elevation. Methylphenidate-induced increases in metabolism in the medial orbital prefrontal cortex were associated with its increase of DA in the thalamus but not in the striatum. These findings provide evidence that enhanced sensitivity of BA 25 (region involved with emotional reactivity) and BA 11 (region involved with salience attribution and motivation) in cocaine-addicted subjects may underlie the strong emotional response to the drug and the intense desire to procure it that results in craving and compulsive drug intake. It also suggests that the mesothalamic DA pathway may contribute to these processes.

The selective dopamine D3 receptor antagonist SB-277011-A attenuates ethanol consumption in ethanol preferring (P) and non-preferring (NP) rats.

Abstract: The mesolimbic dopamine (DA) system plays an important role in mediating addiction to alcohol and other drugs of abuse. Recent evidence points toward the role of the DA D3 receptor (D3R) in drug-induced reward, drug-taking, as well as cue-, drug-, and stress-triggered relapse to drug-seeking behavior. Accordingly, the present study examined the effects of acute selective antagonism of the D3R on ethanol consumption in alcohol Preferring (P) and Non-Preferring (NP) rats. We employed the two-bottle choice paradigm to monitor ethanol consumption in these rats before and after treatment with 3, 10, and 30 mg/kg (i.p.) of the selective D3R antagonist SB-277011-A. Results indicated a significant attenuation in ethanol preference, intake and lick responses in P rats treated with 10 and 30 mg/kg SB-277011-A. A similar, though not as robust effect was observed in ethanol consumption in the NP rats when treated with 30 mg/kg SB-277011-A. Finally, the acute administration of SB-277011-A did not produce extrapyramidal side effects, as indicated by stable lick response-volume ratios and lick response time distributions. These results further support the notion that the D3R is important in mediating the addictive properties of alcohol and suggest that selective blockade of the D3R may constitute a new and useful target for prospective pharmacotherapeutic approaches to alcoholism.

Translational Neuroimaging: Positron Emission Tomography Studies of Monoamine Oxidase

Abstract: Positron emission tomography (PET) using radiotracers with high molecular specificity is an important scientific tool in studies of monoamine oxidase (MAO), an important enzyme in the regulation of the neurotransmitters dopamine, norepinephrine, and serotonin as well as the dietary amine, tyramine. MAO occurs in two different subtypes, MAO A and MAO B, which have different substrate and inhibitor specificity and which are different gene products. The highly variable subtype distribution with different species makes human studies of special value. MAO A and B can be imaged in the human brain and certain peripheral organs using PET and carbon-11 (half-life 20.4 minutes) labeled mechanism-based irreversible inhibitors, clorgyline and l-deprenyl, respectively. In this article we introduce MAO and describe the development of these radiotracers and their translation from preclinical studies to the investigation of variables affecting MAO in the human brain and peripheral organs.

Machine learning for clinical diagnosis from functional magnetic resonance imaging

Abstract: Functional magnetic resonance imaging (fMRI) has enabled scientists to look into the active human brain. FMRI provides a sequence of 3D brain images with intensities representing brain activations. Standard techniques for fMRI analysis traditionally focused on finding the area of most significant brain activation for different sensations or activities. In this paper, we explore a new application of machine learning methods to a more challenging problem: classifying subjects into groups based on the observed 3D brain images when the subjects are performing the same task. Here we address the separation of drug-addicted subjects from healthy non-drug-using controls. In this paper, we explore a number of classification approaches. We introduce a novel algorithm that integrates side information into the use of boosting. Our algorithm clearly outperformed well-established classifiers as documented in extensive experimental results. This is the first time that machine learning techniques based on 3D brain images are applied to a clinical diagnosis that currently is only performed through patient self-report. Our tools can therefore provide information not addressed by traditional analysis methods and substantially improve diagnosis.

Comparison of Monoamine Oxidase A in Peripheral Organs in Nonsmokers and Smokers

Abstract: Smokers have reduced levels of brain monoamine oxidase A (MAO A) leading to speculation that MAO A inhibition by tobacco smoke may underlie some of the neurophysiologic effects of smoking. Because smoking exposes peripheral organs as well as the brain to MAO A–inhibitory compounds, we determined whether smokers would also have reduced MAO A in peripheral organs. Methods: We measured MAO A in peripheral organs in a group of 9 smokers and compared it with a group of nonsmokers studied previously. MAO A was measured using PET and serial scans with the MAO A–specific radiotracers 11C-clorgyline and deuterium-substituted 11C-clorgyline (11C-clorgyline-D2) using the deuterium isotope effect to assess binding specificity. The time course of radiotracer in the arterial plasma was also measured and data from the tissue time–activity curves and the arterial input function were analyzed using a 3-compartment model to estimate k3, which represents the rate-limiting step for the irreversible binding of labeled clorgyline to MAO A. Results: Tracer uptake at plateau was reduced with deuterium substitution for the heart, lungs, and kidneys, indicating specificity for MAO. There was no difference in organ uptake at plateau between nonsmokers and smokers though, for the smokers, the efflux of tracer from peak uptake to plateau was slower for the lungs. The area under the time–activity curve for the arterial plasma was also significantly reduced for smokers versus nonsmokers and the reduction occurred in the first few minutes after radiotracer injection. Smokers had an ∼50% reduction in k3 when compared with nonsmokers; however, k3 did not differ for nonsmokers and smokers for the heart and the kidneys. Conclusion: Because MAO A breaks down serotonin, norepinephrine, dopamine, and tyramine, and because the lung is a major metabolic organ in degrading some of these substances, reduced lung MAO A may contribute to some of the physiologic effects of smoking. This study also revealed that the concentration of the radiotracers in the arterial plasma is significantly lower for the smoker versus the nonsmoker and that this appears to be caused in part by retention of the radiotracer in lungs. If this is generally true for other substances that are administered intravenously, then this needs to be considered as a variable that may contribute to different short-term behavioral responses to intravenously administered drugs for nonsmokers versus smokers.

PET imaging in clinical drug abuse research.

Abstract: Over the last two decades, SPECT (single photon emission computed tomography) and especially PET (positron emission tomography) have proven increasingly effective imaging modalities in the study of human psychopharmacology. Abusing populations can be studied at multiple times after abstinence begins, to give information about neurochemical and physiological adaptations of the brain during recovery from addiction. Individual human subjects can be studied using multiple positron labeled radiotracers, so as to probe more than one facet of brain function. PET and SPECT have been used to help our understanding of many aspects of the pharmacokinetics and pharmacodynamics of abused drugs, and have made valuable contributions in terms of drug mechanisms, drug interactions (e.g. cocaine and alcohol) and drug toxicities. They have also been employed to study the acute effects of drugs on populations of active drug abusers and of normal controls, and to evaluate the neurochemical consequences of candidate therapies for drug abuse. A particularly productive strategy has been the use of PET in conjunction with neuropsychological testing of subjects, to allow correlation of imaging data with uniquely human aspects of the effects of drugs, such as euphoria and craving.

Anger and depression in cocaine addiction: association with the orbitofrontal cortex.

Abstract: The high prevalence of anger, impulsivity and violence in cocaine addiction implicates chronic cocaine use in the compromise of higher-order inhibitory control neurocognitive processes. We used the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) anger content scale as a personality measure of inhibitory control and examined its association with glucose metabolism in the lateral orbitofrontal gyrus (LOFG) at rest as measured by positron emission tomography with 2-deoxy-2[(18)F]fluoro-D-glucose (PET (18)FDG) in 17 recently abstinent cocaine-dependent subjects and 16 comparison subjects. Three additional variables--the MMPI-2 depression content scale, metabolism in the medial orbitofrontal gyrus (MOFG) and the anterior cingulate (AC) gyrus--were inspected. When level of education was statistically controlled for, the LOFG was significantly associated with anger within the cocaine group. No other region was associated with anger within the cocaine-dependent group, and the LOFG did not correlate with depression within any of the study groups. The present study confirms earlier reports in demonstrating a positive association between relative metabolism at rest in the LOFG and cognitive-behavioral and personality measures of inhibitory control in drug addiction: the higher the metabolism, the better the inhibitory control.

Modeling Neuronal Interactivity using Dynamic Bayesian Networks

Abstract: Functional Magnetic Resonance Imaging (fMRI) has enabled scientists to look into the active brain. However, interactivity between functional brain regions, is still little studied. In this paper, we contribute a novel framework for modeling the interactions between multiple active brain regions, using Dynamic Bayesian Networks (DBNs) as generative models for brain activation patterns. This framework is applied to modeling of neuronal circuits associated with reward. The novelty of our framework from a Machine Learning perspective lies in the use of DBNs to reveal the brain connectivity and interactivity. Such interactivity models which are derived from fMRI data are then validated through a group classification task. We employ and compare four different types of DBNs: Parallel Hidden Markov Models, Coupled Hidden Markov Models, Fully-linked Hidden Markov Models and Dynamically Multi-Linked HMMs (DML-HMM). Moreover, we propose and compare two schemes of learning DML-HMMs. Experimental results show that by using DBNs, group classification can be performed even if the DBNs are constructed from as few as 5 brain regions. We also demonstrate that, by using the proposed learning algorithms, different DBN structures characterize drug addicted subjects vs. control subjects. This finding provides an independent test for the effect of psychopathology on brain function. In general, we demonstrate that incorporation of computer science principles into functional neuroimaging clinical studies provides a novel approach for probing human brain function.

Maternal and Fetal 11C-Cocaine Uptake and Kinetics Measured In Vivo by Combined PET and MRI in Pregnant Nonhuman Primates

Abstract: Cocaine use during pregnancy has been shown to be deleterious to the infant. This may reflect reduction of flow to placenta or effects on the fetal brain. Methods to assess pharmacokinetics of drugs of abuse in vivo would be useful to investigate the mechanisms underlying the fetal adverse effects. We recently reported that combined MRI and PET technology allows the measurement of radioisotope distribution in maternal and fetal organs in pregnant Macaca radiata. Here, we evaluate the utility of PET to measure the uptake and distribution of 11C-cocaine in the third-trimester fetus. Methods: Six pregnant M. radiata weighing 3.8–9.0 kg were anesthetized and MR images were acquired on a 4-T MRI instrument. In all 6 animals, dynamic PET scans were subsequently acquired using 148–259 MBq of 11C-cocaine. Time-activity curves for both maternal and fetal organs were obtained simultaneously with the pregnant animal positioned transverse in the PET scanner. Distribution volume ratios for maternal and fetal brain for 11C-cocaine were calculated. Results: Coregistration of PET and MR images allowed identification of fetal organs and brain regions and demonstrated that 11C-cocaine or its labeled metabolites readily cross the placenta and accumulate mainly in fetal liver and to a lesser extent in the brain. Time to reach peak 11C uptake in brain was shorter for the mother than for the fetus. The distribution volume ratios of the maternal striatum were higher than those of the fetus. Placenta was clearly visible on the early time frames and showed more rapid uptake and clearance than other fetal tissues. Conclusion: The pregnant M. radiata model allows the noninvasive measurement of radioisotope pharmacokinetics in maternal and fetal brain and other organs simultaneously. Although the uptake of radioactivity into the fetal brain after the injection of 11C-cocaine is lower and slower than in the maternal brain, a measurable quantity of 11C-cocaine (or its labeled metabolites) accumulates in the fetal brain at early times after injection. The highest accumulation of 11C occurs in the fetal liver. Rapid radioisotope accumulation and clearance in the placenta offer potential as an input function for kinetic modeling for future studies of binding site availability.

Obesity on the brain.

Abstract: 552 VOLUME 8 | NUMBER 5 | MAY 2005 NATURE NEUROSCIENCE The articles in this issue highlight some of the remarkable progress in our understanding of the molecular basis of obesity and provide a glimpse into the extraordinary complexity of the regulation of energy metabolism by the brain. Obesity is at once the prototypical model of a complex genetic disease and a product of lifestyle choice. This apparent paradox has led to the development of two distinct fields of obesity research, one biological and one psychological. A goal of human behavioral research is to understand and modify the factors that motivate individuals to overconsume or adopt sedentary behaviors. Biological research has a goal of understanding the processes controlling food intake, energy storage and energy expenditure in order to develop targeted therapeutic strategies. Since the discovery of leptin in 1994, these distinct research fields have begun to converge on a unified understanding of the molecular substrates of human motivation and of how motivated behaviors are impacted by endocrine and metabolic signals arising from organs involved in energy storage or utilization. Ongoing clinical trials investigating the potential of cannabinoid receptor antagonists as obesity therapeutics illustrate this convergence. We can anticipate the emergence of truly novel approaches to treat or prevent obesity through the development of new tools to integrate human perception and behavior into the neurobiology of obesity. The neuroscience of obesity is one of the broad areas highlighted for new initiative development by the US National Institutes of Health Obesity Research Task Force. The NIH Director established the Task Force to advance progress in obesity research by enhancing and synergizing the efforts of the numerous NIH components that support obesity-related research. Reflecting the complexity of signals that converge in the brain to impact energy balance, the research missions of the NIH components represented on the Task Force range from obesity’s well-known comorbidities of diabetes and cardiovascular disease to neuroscience and many other areas. In our positions as Directors of several of the NIH institutes represented on the Task Force—and, for two of us, as its Co-chairs—we seek to bring knowledge and insights from diverse disciplines to bear on obesity research planning across the NIH. The Strategic Plan for NIH Obesity Research (http://www.obesityresearch.nih.gov) was published in August 2004. Developed by the NIH Obesity Research Task Force with critical input from external scientists and the public, the Strategic Plan presents a multidimensional research agenda and is based on the identification of areas of greatest scientific opportunity and challenge. Among these areas is the intersection of neurobiology, behavior and obesity. Tremendous progress has been made since the discovery of leptin in defining the brain pathways that regulate hunger, satiety and energy metabolism. Despite the enormous advances in this field, major gaps remain. The connection between integrative centers in the hypothalamus and efferent endocrine and autonomic pathways that control diverse functions associated with energy homeostasis, such as activity, metabolic rate, food seeking behavior, gut motility, nutrient partitioning and hormone secretion, still remains undiscovered. The complex interactions between cognition, behavior and environment that are critical to our understanding of the pathobiology and prevention of obesity are difficult to study in animal models. To characterize the influences of genetics, environment and social and societal cues on human behavior and energy regulation in particular will require multidimensional analysis with an array of sophisticated techniques, some of which are still under development. Scientists with expertise in human investigation must be coupled with experts in endocrinology, animal behavior, imaging and genetics. Highlighted below are a number of initiatives developed by the Task Force that focus on the interface between these disciplines, a product of the diversity of perspectives, interest and expertise represented on the Task Force. Neurobiology of obesity, including motivational factors and food preference development. This initiative is focused on enhancing knowledge of the biological basis of human eating behavior by bridging the gap between the understanding at the molecular/genetic level of neural pathways involved in food intake and the understanding of behavioral influences on human obesity. Research is needed to link brainstem, hypothalamic and cortical afferent and efferent pathways that control food intake or energy expenditure and to develop models to integrate endocrine and nutrient signals into their function. Comparative studies connecting molecular substrates and human behavior will help bridge this gap. This initiative will emphasize the need for interaction between researchers working in addiction and reward systems and those working on control of food intake. Brain imaging studies of obesity. Brain imaging of obese individuals represents both physical and technological challenges. NIH is committed to stimulating the development of brain imaging technology in the areas of magnetic resonance imaging and positron emission tomography to investigate brain mechanisms of obesity. These necessary technological advancements will allow for investigations of brain-behavior interactions in the study of obesity. The development of imaging technologies will enable comparisons between animal models, where molecular mechanisms can be investigated, and humans, where Obesity on the brain

Exploiting temporal information in functional magnetic resonance imaging brain data

Abstract: Functional Magnetic Resonance Imaging(fMRI) has enabled scientists to look into the active human brain, leading to a flood of new data, thus encouraging the development of new data analysis methods. In this paper, we contribute a comprehensive framework for spatial and temporal exploration of fMRI data, and apply it to a challenging case study: separating drug addicted subjects from healthy non-drug-using controls. To our knowledge, this is the first time that learning on fMRI data is performed explicitly on temporal information for classification in such applications. Experimental results demonstrate that, by selecting discriminative features, group classification can be successfully performed on our case study although training data are exceptionally high dimensional, sparse and noisy fMRI sequences. The classification performance can be significantly improved by incorporating temporal information into machine learning. Both statistical and neuroscientific validation of the method’s generalization ability are provided. We demonstrate that incorporation of computer science principles into functional neuroimaging clinical studies, facilitates deduction about the behavioral probes from the brain activation data, thus providing a valid tool that incorporates objective brain imaging data into clinical classification of psychopathologies and identification of genetic vulnerabilities.

Dopamine and Glutamate in Attention Deficit Hyperactivity Disorder

Abstract: Attention deficit hyperactivity disorder (ADHD) is a complex condition, thought to have multiple subtypes lurking within a broad, behaviorally defined phenotype, making it difficult to identify specific biological causes of this syndrome. However, the evidence from studies conducted over the past decade suggests that dopamine (DA) plays a prominent role in the etiology and treatment of ADHD. Here we will start with consensus views that have emerged about ADHD at the behavioral, biological, and genetic levels of analysis. Then, we will summarize the evidence that links DA to ADHD.

A note from NIDA's Director.

Abstract: In this issue of Science & Practice Perspectives, a dialogue between researcher Dr. Linda Chang and clinical psychiatrist Dr. Paul Linde provides a prime example of how bringing together a researcher’s conceptual framework and a skillful clinician’s understanding of clinical nuance stimulates and enriches both. Together, Chang and Linde consider whether the results to date from non-invasive brain imaging studies might support his use of certain medications with methamphetamine abusers. Ultimately, they conclude that the findings appear consistent with Linde’s use of some of the medications, raise concerns about others, and can’t strictly endorse any. Along the way, the colloquy identifies two good opportunities for research studies and appropriate messages to give patients based on imaging studies. If Chang and Linde’s discussion exemplifies the depth of integration now occurring between research and clinical practice in drug abuse, the overall contents of the journal indicate its breadth. Topics range from clinical interventions to the challenges of making organizational changes and of laying a foundation for systemic change. The research-practice engagement evident in Perspectives reflects a broad maturity of collaborative solution-seeking in the treatment of drug abuse. To cite some examples: NIDA’s Clinical Trials Network has now published the results of studies of motivational interviewing, contingency management, and opiate detoxification with the medication combination of buprenorphine and naloxone. Although these studies proved their hypotheses, an equally important outcome was that researchers and community clinicians jointly planned and accomplished projects that served both of their learning agendas. The Blending Initiative—a collaboration between NIDA, the Substance Abuse and Mental Health Services Administration, and the Addiction Treatment Technology Centers—has released four evidence-based, validated tools for staff training. They cover the use of buprenorphine for opiate withdrawal and for longer term treatment, and offer guidance on administering and interpreting the Addiction Severity Index. There always will be some degree of divergence between research and clinical practice in the treatment of substance abuse, because the two enterprises have different natures. Communication across this gap is critical to achieve the common goal of reducing drug abuse and addiction, and their health and social consequences. The growing maturity of that communication, evident in this journal, increases hope for patients, their families, and the Nation.