The Effect Of Abstinence From Smoking On Stress Reactivity

Subjective stress is a well-documented predictor of early smoking relapse, yet our understanding of stress and tobacco use is limited by the reliability of current available measures of stress. Functional magnetic reasoning imaging (fMRI) could provide a much-needed objective measure of stress reactivity. The goal of this dissertation is to contribute to the understanding of abstinence-induced changes in stress reactivity by examining neural, neuroendocrine (cortisol), and subjective measures of stress response during abstinence. In addition, this study investigated the influence of individual variation in nicotine metabolism rates on these measures of stress reactivity. Seventy-five treatment-seeking smokers underwent blood oxygen level dependent (BOLD) fMRI during the Montreal Imaging Stress Task (MIST) on two occasions: once during smoking satiety and once following biochemically confirmed 24-hour abstinence (order counter-balanced). The primary outcome measure was brain response during stress (vs. control) blocks of the MIST. Neural stress reactivity during abstinence (vs. satiety) was associated with significantly increased activation in the left inferior frontal gyrus (IFG), a brain region previously associated with inhibitory control. Greater abstinence-induced change in brain response to stress was associated with greater abstinence-induced change in subjective stress. However, there was no association with abstinence-induced change in cortisol response. In addition, higher rates of nicotine metabolism were associated with increased abstinence-induced change in self-reported stress, but not with brain or cortisol response. This study provides novel evidence that the brain response to stress is altered during the first 24 hours of a quit attempt compared to smoking satiety. These results underscore the importance of stress response during abstinence, and suggest that neuroimaging may provide a useful biomarker of stress response during the early smoking cessation, a period when smokers are most vulnerable to relapse

Imaginary relish and exquisite torture: The elaborated intrusion theory of desire

The authors argue that human desire involves conscious cognition that has strong affective connotation and is potentially involved in the determination of appetitive behavior rather than being epiphenomenal to it. Intrusive thoughts about appetitive targets are triggered automatically by external or physiological cues and by cognitive associates. When intrusions elicit significant pleasure or relief, cognitive elaboration usually ensues. Elaboration competes with concurrent cognitive tasks through retrieval of target-related information and its retention in working memory. Sensory images are especially important products of intrusion and elaboration because they simulate the sensory and emotional qualities of target acquisition. Desire images are momentarily rewarding but amplify awareness of somatic and emotional deficits. Effects of desires on behavior are moderated by competing incentives, target availability, and skills. The theory provides a coherent account of existing data and suggests new directions for research and treatment

Methods and Applications of Multivariate Pattern Analysis in Functional MRI Data Analysis.

In spite of the tremendous advances in science and technology, the human brain and its functions are still not completely understood. Functional magnetic resonance imaging (fMRI) is an imaging modality that allows for non-invasive study of brain function and physiology. Thus, fMRI has found many applications in various fields involved in the study of cognition, psychology, psychiatry, neuroscience, etc. Machine learning techniques have gained tremendous interest in recent times for fMRI data analysis. These methods involve learning from numerous examples and then making predictions for new unseen examples. This work addresses the use of machine learning techniques to find and study multivariate patterns in the fMRI brain data. The two main applications explored in this work include temporal brain-state prediction and subject categorization. The within-subject brain-state prediction setup has been used to compare and contrast three different acquisition techniques in a motor-visual activation study. It has also been implemented to highlight the differences in pain regulation networks in healthy controls and subjects with temporomandibular disorders. Lastly, regression has been used to predict graded fMRI activation on a continuous scale in a motor activation and craving study. The between-subject categorization setup has been used to distinguish between patients with Asperger's disorder and healthy controls. A major contribution of our work involves a novel multi-subject machine learning framework. This technique helps to learn a model which is based on information acquired from multiple other subjects' data in addition to the subject's own data. This has been used to classify the craving and non-craving brain states of nicotine-dependent subjects, allowing examination of both population-wide as well as subject-specific neural correlates of nicotine craving. A real-time neurofeedback setup was implemented to provide feedback to a subject using their own brain activation data. Subjects can then be trained to self-regulate their own brain activation.PhDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111357/1/ysshah_1.pd

Functional Organization of the Human Brain: How We See, Feel, and Decide.

The human brain is responsible for constructing how we perceive, think, and act in the world around us. The organization of these functions is intricately distributed throughout the brain. Here, I discuss how functional magnetic resonance imaging (fMRI) was employed to understand three broad questions: how do we see, feel, and decide? First, high-resolution fMRI was used to measure the polar angle representation of saccadic eye movements in the superior colliculus. We found that eye movements along the superior-inferior visual field are mapped across the medial-lateral anatomy of a subcortical midbrain structure, the superior colliculus (SC). This result is consistent with the topography in monkey SC. Second, we measured the empathic responses of the brain as people watched a hand get painfully stabbed with a needle. We found that if the hand was labeled as belonging to the same religion as the observer, the empathic neural response was heightened, creating a strong ingroup bias that could not be readily manipulated. Third, we measured brain activity in individuals as they made free decisions (i.e., choosing randomly which of two buttons to press) and found the activity within fronto-thalamic networks to be significantly decreased compared to being instructed (forced) to press a particular button. I also summarize findings from several other projects ranging from addiction therapies to decoding visual imagination to how corporations are represented as people. Together, these approaches illustrate how functional neuroimaging can be used to understand the organization of the human brain

PROCESSING OF SMOKING AND MONETARY REWARDS AMONG CHRONIC SMOKERS: CHARACTERIZATION OF NEURAL RESPONSE, MODERATION BY ABSTINENCE, AND ASSOCIATION WITH SMOKING OUTCOMES

Theoretical models suggest that chronic smoking may be associated with both hypersensitivity to smoking and related cues and hyposensitivity to alternative reinforcers, and that these effects may be more pronounced during deprivation from smoking. However, neural responses to smoking and non-smoking rewards are rarely evaluated within the same paradigm, and current neuroimaging evidence on the effects of deprivation on reward processing is limited. Bias toward smoking reward in lieu of alternative rewards during abstinence could represent a fundamental mechanism contributing to relapse during a quit attempt. In this dissertation, I present a series of analyses to address three primary aims: 1) to characterize the neural response to smoking and non-smoking rewards among chronic smokers within the same paradigm, 2) to determine the impact of deprivation upon the neural response to both reward types, and 3) to evaluate the association between neural responses to both reward types and the choice to smoke in lieu of alternative reinforcement. Smokers each participated in two separate fMRI scans, one after smoking ad libitum and one following 24 hours of abstinence. A rewarded guessing task was conducted during each scan to evaluate BOLD response during anticipation and delivery of both smoking and monetary rewards. Following completion of both scans, smokers engaged in a quit attempt supported by contingency management, during which abstinence from smoking was reinforced with monetary iii reward. Results indicated that smoking and monetary rewards both activated the same reward-related circuitry, including ventral and dorsal striatum, anterior cingulate cortex, medial prefrontal cortex, and bilateral insula. Abstinence from smoking was associated with an increase in anticipatory activation to smoking reward and a parallel decrease in anticipatory activation to monetary reward in the same reward-related regions. Furthermore, preliminary analyses suggested that larger decreases in anticipatory activation to monetary reward in the right caudate were associated with higher likelihood of lapse during contingency management. Collectively, these results suggest that reward processing may be biased toward smoking reward at the expense of alternative rewards during abstinence—a bias which may directly impact smoking behavior during a quit attempt

Are Machine Learning Methods the Future for Smoking Cessation Apps?

Smoking cessation apps provide efficient, low-cost and accessible support to smokers who are trying to quit smoking. This article focuses on how up-to-date machine learning algorithms, combined with the improvement of mobile phone technology, can enhance our understanding of smoking behaviour and support the development of advanced smoking cessation apps. In particular, we focus on the pros and cons of existing approaches that have been used in the design of smoking cessation apps to date, highlighting the need to improve the performance of these apps by minimizing reliance on self-reporting of environmental conditions (e.g., location), craving status and/or smoking events as a method of data collection. Lastly, we propose that making use of more advanced machine learning methods while enabling the processing of information about the user’s circumstances in real time is likely to result in dramatic improvement in our understanding of smoking behaviour, while also increasing the effectiveness and ease-of-use of smoking cessation apps, by enabling the provision of timely, targeted and personalised intervention

AN FMRI STUDY OF THE IMPACT OF OLFACTORY CUES ON CIGARETTE CRAVING

Cigarette smoking remains the number one preventable cause of death in the United States. Cigarette craving during a quit attempt has been linked to relapse, suggesting it is a clinically significant construct. This study investigated an understudied method of craving reduction, involving the administration of olfactory cues after craving induction. Olfactory cues may work to combat craving because they strongly engage attentional and emotional processing, can induce vivid autobiographical memory (AM) recall, and because olfactory processing brain regions overlap with regions involved in craving. Using both general linear model (GLM) and multivoxel pattern analysis (MVPA) approaches, this study collected fMRI and behavioral data to build upon a set of behavioral studies that have found odors to be an effective craving reduction tool. The neural response during a strong craving state was assessed in 39 adult daily smokers across a variety of craving, olfactory, and AM regions before and after an odor exposure paradigm, during which half of the participants smelled a pleasant odor cue and half smelled a neutral odor. Results indicate that exposure to a pleasant odor cue (compared to a neutral odor cue) changed the neural response in craving related regions. Odor characteristics, namely specific memory association for an odor, and individual differences in attention to odors were found to influence this odor-induced craving change. In addition, this study found that MVPA techniques are compatible with the unique study design requirements of craving research. Study limitations, implications, and possible future directions are discussed in light of these findings

CORTICOLIMBIC FUNCTIONING, NICOTINE DEPENDENCE CHARACTERISTICS, AND SMOKING LAPSE HISTORY: AN FMRI STUDY

Nicotine dependence is a prevalent and costly disorder characterized by notoriously high relapse rates. Extant research implicates stress as a key mechanism driving smoking across the stages of addiction, and neurobiological models of stress and addiction emphasize the role of overlapping corticolimbic circuits in both emotion dysregulation and compulsive drug seeking. However, neuroimaging research examining the neural correlates of stress processing in human smokers is limited and lacking in some areas, leaving key questions unanswered. Specifically, it is unclear how neural responses to stress may explain individual differences in nicotine dependence severity and cessation attempt outcomes. Moreover, more recent theoretical and empirical work has highlighted the importance of looking beyond functioning in discreet neural regions and has emphasized the importance of examining how brain functioning at a network level, through the use of resting state functional connectivity, might explain addictive behavior. However, research examining the relationship between functional connectivity and clinically-relevant smoking measures is also limited. As a first step toward addressing these gaps in the literature, the current study utilized a novel fMRI-compatible psychological stress induction task to examine the relationships between stress-induced neural activation, as well as resting state functional connectivity within stress-related corticolimbic circuits, and clinically-relevant smoking characteristics among a sample of adult cigarette smokers. Analysis of the fMRI data collected during administration of the novel stress induction task revealed significant stress-induced activation in the right insula, a region previously implicated in the interoceptive experience of negative affective states, as well as visceral symptoms of nicotine withdrawal and craving. Contrary to expectations, there were no significant relationships identified between stress-induced neural functioning, or functional connectivity within stress-related circuits, and the clinically-relevant smoking measures that were assessed. Findings are discussed in light of several study limitations and directions for future research are enumerated

Exploring Environmental Tobacco Smoke (ETS) exposure: A pathway to youth smoking addiction?

Contains fulltext : 284938.pdf (Publisher’s version ) (Open Access)Radboud University, 02 december 2022Promotores : Otten, R., Kleinjan, M. Co-promotor : Luijten, M.198 p