Stephens DN, Duka T, Crombag HS, Cunningham CL, Heilig M, Crabbe JC. Reward sensitivity: issues of measurement, and achieving consilience between human and animal phenotypes. Addict Biol 15: 145-168
ABSTRACT Reward is a concept fundamental to discussions of drug abuse and addiction. The idea that altered sensitivity to either drug-reward, or to rewards in general, contributes to, or results from, drug-taking is a common theme in several theories of addiction. However, the concept of reward is problematic in that it is used to refer to apparently different behavioural phenomena, and even to diverse neurobiological processes (reward pathways). Whether these different phenomena are different behavioural expressions of a common underlying process is not established, and much research suggests that there may be only loose relationships among different aspects of reward. Measures of rewarding effects of drugs in humans often depend upon subjective reports. In animal studies, such insights are not available, and behavioural measures must be relied upon to infer rewarding effects of drugs or other events. In such animal studies, but also in many human methods established to objectify measures of reward, many other factors contribute to the behaviour being studied. For that reason, studying the biological (including genetic) bases of performance of tasks that ostensibly measure reward cannot provide unequivocal answers. The current overview outlines the strengths and weaknesses of current approaches that hinder the conciliation of cross-species studies of the genetics of reward sensitivity and the dysregulation of reward processes by drugs of abuse. Some suggestions are made as to how human and animal studies may be made to address more closely homologous behaviours, even if those processes are only partly able to isolate 'reward' from other factors contributing to behavioural output.
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- "In other studies, discounting was assessed as a predictor of drug self-administration, and steeper discounting was associated with greater self-administration of alcohol, nicotine, and cocaine (Poulos et al., 1995; Perry et al., 2005; Diergaarde et al., 2008; Anker et al., 2009). The greater self-administration suggested that the more impulsive animals valued rewards more (although it is important to note that additional factors likely contribute to drug self-administration; Stephens et al., 2010). "
ABSTRACT: Evidence from both human and animal studies suggests that sensitivity to rewarding stimuli is positively associated with impulsive behaviors, including both impulsive decision making and inhibitory control. The current study examined associations between the hedonic value of a sweet taste and two forms of impulsivity (impulsive choice and impulsive action) in healthy young adults (N = 100). Participants completed a sweet taste test in which they rated their liking of various sweetness concentrations. Subjects also completed measures of impulsive choice (delay discounting), and impulsive action (go/no-go task). Subjects who discounted more steeply (i.e., greater impulsive choice) liked the high sweetness concentration solutions more. By contrast, sweet liking was not related to impulsive action. These findings indicate that impulsive choice may be associated with heightened sensitivity to the hedonic value of a rewarding stimulus, and that these constructs might share common underlying neurobiological mechanisms.Frontiers in Behavioral Neuroscience 06/2014; 8:228. DOI:10.3389/fnbeh.2014.00228 · 3.27 Impact Factor
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- "PR schedules are often used to measure the motivation to obtain reward. The classical procedure involves testing a single animal in a Skinner box in which the animal has access to two operants , . The animal has previously been trained to recognize that an instrumental response on one operant has no consequence, while a response on the other has been associated with a specific outcome. "
ABSTRACT: Here, we describe a new model of voluntary alcohol drinking by group-housed mice. The model employs sensor-equipped cages that track the behaviors of the individual animals via implanted radio chips. After the animals were allowed intermittent access to alcohol (three 24 h intervals every week) for 4 weeks, the proportions of licks directed toward bottles containing alcohol were 50.9% and 39.6% for the male and female mice, respectively. We used three approaches (i.e., quinine adulteration, a progressive ratio schedule and a schedule involving a risk of punishment) to test for symptoms of compulsive alcohol drinking. The addition of 0.01% quinine to the alcohol solution did not significantly affect intake, but 0.03% quinine induced a greater than 5-fold reduction in the number of licks on the alcohol bottles. When the animals were required to perform increasing numbers of instrumental responses to obtain access to the bottle with alcohol (i.e., a progressive ratio schedule), they frequently reached a maximum of 21 responses irrespective of the available reward. Although the mice rarely achieved higher response criteria, the number of attempts was ∼10 times greater in case of alcohol than water. We have developed an approach for mapping social interactions among animals that is based on analysis of the sequences of entries into the cage corners. This approach allowed us to identify the mice that followed other animals in non-random fashions. Approximately half of the mice displayed at least one interaction of this type. We have not yet found a clear correlation between imitative behavior and relative alcohol preference. In conclusion, the model we describe avoids the limitations associated with testing isolated animals and reliably leads to stable alcohol drinking. Therefore, this model may be well suited to screening for the effects of genetic mutations or pharmacological treatments on alcohol-induced behaviors.PLoS ONE 05/2014; 9(5):e96787. DOI:10.1371/journal.pone.0096787 · 3.23 Impact Factor
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- "Many animal and human laboratory paradigms are used to study different facets of alcohol dependence (O'Malley et al. 2002; Anton et al. 2004; Egli 2005; Mason et al. 2008; Koob, Lloyd & Mason 2009; Crabbe, Bell & Ehlers 2010; Heilig et al. 2010; Leeman et al. 2010; Stephens et al. 2010). These models also are used for evaluating medications with the ultimate aim of informing decisions to carry out clinical trials (Egli 2005; Koob et al. 2009). "
ABSTRACT: More than 76 million people world-wide are estimated to have diagnosable alcohol use disorders (AUDs) (alcohol abuse or dependence), making these disorders a major global health problem. Pharmacotherapy offers promising means for treating AUDs, and significant progress has been made in the past 20 years. The US Food and Drug Administration approved three of the four medications for alcoholism in the last two decades. Unfortunately, these medications do not work for everyone, prompting the need for a personalized approach to optimize clinical benefit or more efficacious medications that can treat a wider range of patients, or both. To promote global health, the potential reorganization of the National Institutes of Health (NIH) must continue to support the National Institute on Alcohol Abuse and Alcoholism's (NIAAA's) vision of ensuring the development and delivery of new and more efficacious medications to treat AUDs in the coming decade. To achieve this objective, the NIAAA Medications Development Team has identified three fundamental long-range goals: (1) to make the drug development process more efficient; (2) to identify more efficacious medications, personalize treatment approaches, or both; and (3) to facilitate the implementation and adaptation of medications in real-world treatment settings. These goals will be carried out through seven key objectives. This paper describes those objectives in terms of rationale and strategy. Successful implementation of these objectives will result in the development of more efficacious and safe medications, provide a greater selection of therapy options and ultimately lessen the impact of this devastating disorder.Addiction Biology 03/2012; 17(3):513-27. DOI:10.1111/j.1369-1600.2012.00454.x · 5.36 Impact Factor