Expectancy and pharmacology influence the subjective effects of nicotine in a balanced-placebo design.

Kelemen, William L.; Kaighobadi, Farnaz

doi:10.1037/1064-1297.15.1.93

Cited by 56 publications

(62 citation statements)

References 29 publications

(53 reference statements)

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“…Interestingly, one PET study found that negative drug prediction errors (i.e., alcohol expected but not delivered) decreased striatal DA concentrations while positive drug prediction errors (i.e., alcohol not expected but delivered) increased striatal DA levels in individuals with alcohol dependence (21), which is consistent with our finding of modifiable striatal responses by beliefs. Furthermore, our findings extend previous results showing the impact of beliefs on behavioral performances and subjective states related to nicotine intake (15)(16)(17)20) by detailing the specific neural and computational mechanisms underlying the impact of beliefs on drug effects. These selective effects demonstrate that belief can modulate model-based parameters important for learning and suggest that belief serves as an important cognitive mechanism in addiction.…”

Section: Discussionsupporting

confidence: 76%

“…Additionally, six parameters generated during motion correction were entered as covariates. In the first GLM, market value r t was entered as parametric regressors at the fifth regressor (market price reveal of rounds [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]; in the second GLM, reward prediction error TD t was entered as parametric regressors at the fifth regressor (market price reveal of rounds 2-19). Regressors were orthogonalized in a standard SPM8 fashion.…”

Section: Behavioral Data Analysismentioning

confidence: 99%

“…These treatment effects are putatively accomplished by neurobiological processes usually associated with pharmacological actions of active drugs, even though active drugs are not administered (10)(11)(12)(13)(14). Interestingly, beliefs also directly impact behavioral (15)(16)(17)(18)(19)(20) and neurophysiological (21-26) responses when addictive drugs are administered. Drug dependence is a learned process in which cognitive factors are critical (2,5,(27)(28)(29)(30).…”

mentioning

confidence: 99%

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Belief about nicotine selectively modulates value and reward prediction error signals in smokers

Lohrenz

Salas

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Little is known about how prior beliefs impact biophysically described processes in the presence of neuroactive drugs, which presents a profound challenge to the understanding of the mechanisms and treatments of addiction. We engineered smokers' prior beliefs about the presence of nicotine in a cigarette smoked before a functional magnetic resonance imaging session where subjects carried out a sequential choice task. Using a model-based approach, we show that smokers' beliefs about nicotine specifically modulated learning signals (value and reward prediction error) defined by a computational model of mesolimbic dopamine systems. Belief of "no nicotine in cigarette" (compared with "nicotine in cigarette") strongly diminished neural responses in the striatum to value and reward prediction errors and reduced the impact of both on smokers' choices. These effects of belief could not be explained by global changes in visual attention and were specific to value and reward prediction errors. Thus, by modulating the expression of computationally explicit signals important for valuation and choice, beliefs can override the physical presence of a potent neuroactive compound like nicotine. These selective effects of belief demonstrate that belief can modulate modelbased parameters important for learning. The implications of these findings may be far ranging because belief-dependent effects on learning signals could impact a host of other behaviors in addiction as well as in other mental health problems.O ne materialist view of mental function suggests that even the most abstract beliefs can be represented in terms of physiological states available to the brain (1). These mappings are critical in conditions like drug addiction, where our ignorance of how prior beliefs about drugs influence physiological processes related to drugs of abuse presents a profound challenge to the understanding of the mechanism and treatment of addiction (2, 3). Although extensive work has shown that addictive drugs act on the mesolimbic dopaminergic (DA) pathway (2, 4), it has become clear that these purely biochemical explanations are not sufficient to account for the huge heterogeneity among drug-dependent individuals and the low success rate of quitting and remaining drug-free (2, 5) and that cognitive factors such as beliefs and expectations have a profound impact on drug-related neurobiological effects (6, 7).Beliefs are known to contribute to the placebo effect. The placebo effect is a treatment effect not caused by the physical presence of an active drug, but rather by the meaning ascribed to it and the subjective expectation of receiving a treatment (8, 9). A subject's belief that he or she is receiving a treatment could lead to observable improvement even in the absence of active drugs. These treatment effects are putatively accomplished by neurobiological processes usually associated with pharmacological actions of active drugs, even though active drugs are not administered (10-14). Interestingly, beliefs also directly impact behavioral...

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Section: Discussionsupporting

confidence: 76%

Section: Behavioral Data Analysismentioning

confidence: 99%

mentioning

confidence: 99%

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Belief about nicotine selectively modulates value and reward prediction error signals in smokers

Lohrenz

Salas

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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“…Outcome expectancies reflect anticipated consequences of smoking (Brandon, 1994;Brandon et al, 1999;Cohen, McCarthy, Brown, & Myers, 2002;Cox & Klinger, 1988;Niaura, Goldstein, & Abrams, 1991) and include beliefs about positive reinforcement (e.g., "I enjoy the taste sensations while smoking"), negative reinforcement/negative affect reduction (e.g., "Smoking helps me calm down when I feel nervous"), negative consequences (e.g., "The more I smoke, the more I risk my health"), and appetite control (e.g., "Smoking helps me control my weight"; Brandon & Baker, 1991). Outcome expectancies are related to key aspects of smoking behavior (Kelemen & Kaighobadi, 2007). For instance, smokers who smoke at higher rates tend to endorse more positive expectancies about the effects of smoking (Ahijevych & Wewers, 1993;Copeland, Brandon, & Quinn, 1995;Downey & Kilbey, 1995), whereas expectancies for negative reinforcement/negative affect reduction predict greater rates of smoking cessation failure (Wetter, Smith et al, 1994).…”

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confidence: 99%

Linkages between cigarette smoking outcome expectancies and negative emotional vulnerability

Johnson¹,

Zvolensky²,

Marshall³

et al. 2008

Addictive Behaviors

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The present investigation examined whether smoking outcome expectancies, as measured by the Smoking Consequences Questionnaire (SCQ; Brandon & Baker, 1991), were incrementally related to emotional vulnerability factors among an adult sample of 202 daily cigarette smokers (44.6% women; M age = 23.78 years, SD = 9.69 years). After controlling for cigarettes smoked per day, past 30-day marijuana use, current alcohol consumption, and coping style, negative reinforcement/ negative affect reduction outcome expectancies were significantly associated with greater levels of negative affectivity, emotional dysregulation, and anxiety sensitivity. The observed effects for negative reinforcement/negative affect reduction also were independent of shared variance with other outcome expectancies. Negative personal consequences outcome expectancies were significantly and incrementally related to anxiety sensitivity, but not negative affectivity or emotional dysregulation. Findings are discussed in terms of the role of negative reinforcement/negative affect reduction smoking outcome expectancies and clinically-relevant negative emotional vulnerability for better understanding cigarette smoking-negative mood problems.Correspondence concerning this article should be addressed to Michael J. Zvolensky, Ph.D., Dr. Zvolensky can be contacted at The University of Vermont, Department of Psychology, 2, Colchester Avenue, John Dewey Hall, Burlington,. Electronic mail may be sent to Michael.Zvolensky@uvm.edu. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. 2 Although not a primary aim of the current study, exploratory analyses focused on positive affectivity were completed for comparative purposes. These analyses were completed in an identical fashion to those reported in the paper except positive affectivity was employed as the dependent variable. Here, predictor variables accounted for 22.1% of the overall variance for positive affectivity [F(9, 198) = 5.95, p < .001]. Level one of the model accounted for 17.1% of the variance, with significant contributions by the emotional processing and emotional expression subscales (β = .30, p < .001 and β = .16, p < .05, respectively). Level two of the model accounted for an additional 5% of the variance, with the appetite control subscale being the only significant predictor (β = −.16, p < .05). There is a recent and increasingly well-documented association between cigarette smoking and depressive and anxiety symptoms and disorders (Morrell & Cohen, 2006;Morissette, Tull, Gulliver, Kamholz, & Zimering, 2007;Patton, Carlin, Coffey, Wolfe, Hibbert, & ...

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“…Whether an individual's expectancy for alcohol translates to similar expectancies for cigarette smoking is unclear. However, smoking expectancies are predictive of smoking behavior (Kelemen & Kaighobadi, 2007), and, specifically, negative reinforcement expectancies have been found to predict greater rates of smoking-cessation failure (Wetter et al, 1994). If alcoholic typologies that favor relief drinking (e.g., Type B alcoholics) also favor relief smoking, this may have predictive value in smoking-cessation outcomes with or without concurrent medication treatment.…”

mentioning

confidence: 99%

Type A/Type B Alcoholism Predicts Differential Response to Topiramate in a Smoking Cessation Trial in Dually Diagnosed Men

Isgro

Doran

Heffner

et al. 2017

J. Stud. Alcohol Drugs

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ABSTRACT. Objective:Babor's A/B typology characterizes alcoholdependence subtypes, which differ across multiple defining variables; however, differences in cigarette smoking and cessation between these subtypes have not been previously investigated. Topiramate reduces heavy drinking and has separately been found to help non-alcoholdependent individuals quit smoking. This study tested the hypothesis that topiramate's effects on smoking would be moderated by alcohol-dependence subtype, and explored craving as a mediator of this response. Method: One hundred twenty-nine abstinent alcohol-dependent outpatient male smokers participated in this 12-week, randomized controlled trial comparing topiramate (maximum dosage 200 mg/day) with placebo, both with brief counseling, for smoking cessation. Participants were followed for 24 weeks following end of treatment. Results: Of the 125 participants with sufficient subtyping data, k-means cluster analysis categorized 52 (42%) as Type A alcoholics and 73 (58%) as Type B. Types A and B did not differ on baseline smoking characteristics, urges to smoke, or smoking consequence scores. Longitudinal mixed-effects regression indicated that the effect of treatment on smoking was moderated by the Type × Time interaction. Specifically, during the nontreatment follow-up phase, Type B's treated with topiramate had relative suppressed levels of smoking compared with placebo-treated Type B's. This moderating effect of the Type × Time interaction was mediated by intention to smoke and craving related to relief of negative affect. Conclusions: Type B alcoholics demonstrated suppressed levels of smoking in response to topiramate treatment as compared with placebo, but only during the nontreatment follow-up phase. This effect was mediated, in part, through intention to smoke and craving to smoke to relieve negative affect. Our findings extend other studies demonstrating a differential medication response by alcoholism subtype. (J. Stud. Alcohol Drugs, 78, 232-240, 2017)

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Expectancy and pharmacology influence the subjective effects of nicotine in a balanced-placebo design.

Cited by 56 publications

References 29 publications

Belief about nicotine selectively modulates value and reward prediction error signals in smokers

Belief about nicotine selectively modulates value and reward prediction error signals in smokers

Linkages between cigarette smoking outcome expectancies and negative emotional vulnerability

Type A/Type B Alcoholism Predicts Differential Response to Topiramate in a Smoking Cessation Trial in Dually Diagnosed Men

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