Social Anxiety Disorder (SAD) is characterized by excessive concern or fear of negative evaluation in one or more social situations and ranks as one of the most common psychiatric disorders. SAD has also been characterized by significant deficits in social motivation and a lack of reactivity to pleasurable stimuli (i.e., positive affect; [PA]), particularly within social contexts. Recent neuroimaging work has shifted towards examining positively-valenced motivational systems in SAD focused on reward responses to social and nonsocial stimuli. These studies have revealed aberrant reward processing during social reward tasks in individuals with SAD. However, not all individuals with SAD exhibit reward circuitry dysfunction. Therefore, the current study aimed to examine if functional patterns of connectivity in the brain underlie heterogeneity in PA differences in individuals with SAD. Results revealed several functional connectivity strength differences between SAD and control groups within reward regions. Additionally, associations between regions of interest (ROIs)-couplings (i.e., OFC and insula, OFC and subgenual cingulate, insula and cingulate, and cingulate and subgenual cingulate) and diminished PA were present in individuals with SAD, but not controls. Lastly, results demonstrated that individuals with SAD had higher variability in their reward connectivity strength presentations and reports of PA as compared to controls. These results hold significance for the development of interventions for SAD that focus on the enhancement of PA to bolster social reward responsivity. / M.S. / Social Anxiety Disorder (SAD) is a common disorder where individuals experience persistent excessive fear of one or more social situations. Individuals with SAD also tend to show lower social motivation and a lack of reactivity to pleasurable activities/events (referred to broadly as positive affect; [PA]), particularly within social situations. Current work has focused on areas within the brain that are responsible for reward responses, and have indicated that individuals with SAD show different types of reward processing during social reward situations. However, not all individuals with SAD show these same patterns. Therefore, the current study aimed to examine if connections between reward regions in the brain underlie differences in PA differences in individuals with SAD. Results showed several differences between SAD and control groups within reward regions of the brain. Additionally, specific associations between brain regions of interest and low PA were present in individuals with SAD, but not controls. Lastly, results demonstrated that individuals with SAD had higher variability in their connections between reward regions and reports of PA as compared to controls. These results can help inform the development of treatments for SAD that focus on the improving PA in an attempt to increase responsiveness to social rewards.

Yes / Knowledge of the underlying mechanisms of effortful listening could help to reduce cases of social withdrawal and mitigate fatigue, especially in older adults. However, the relationship between transient effort and longer-term fatigue is likely to be more complex than originally thought. Here, we manipulated the presence/absence of monetary reward to examine the role of motivation and mood state in governing changes in perceived effort and fatigue from listening. In an online study, 185 participants were randomly assigned to either a ‘reward’ (n = 91) or ‘no-reward’ (n = 94) group and completed a dichotic listening task along with a series of questionnaires assessing changes over time in perceived effort, mood, and fatigue. Effort ratings were higher overall in the reward group, yet fatigue ratings in that group showed a shallower linear increase over time. Mediation analysis revealed an indirect effect of reward on fatigue ratings via perceived mood state; reward induced a more positive mood state which was associated with reduced fatigue. These results suggest that: (a) listening conditions rated as more ‘effortful’ may be less fatiguing if the effort is deemed worthwhile, and (b) alterations to one’s mood state represents a potential mechanism by which fatigue may be elicited during unrewarding listening situations.

This thesis discusses the use of Bayesian Inference in inferring over the human's objective for Human-Robot Interaction, more specifically, it focuses upon the adaptation of methods to better utilize the information for inferring upon the human's objective for Reward Learning and Communicative Shared Autonomy settings. To accomplish this, we first examine state-of-the-art methods for approaching Bayesian Inverse Reinforcement learning where we explore the strengths and weaknesses of current approaches. After which we explore alternative methods for approaching the problem, borrowing similar approaches to those of the statistics community to apply alternative methods to improve the sampling process over the human's belief. After this, I then move to a discussion on the setting of Shared Autonomy in the presence and absence of communication. These differences are then explored in our method for inferring upon an environment where the human is aware of the robot's intention and how this can be used to dramatically improve the robot's ability to cooperate and infer upon the human's objective. In total, I conclude that the use of these methods to better infer upon the human's objective significantly improves the performance and cohesion between the human and robot agents within these settings. / Master of Science / This thesis discusses the use of various methods to allow robots to better understand human actions so that they can learn and work with those humans. In this work we focus upon two areas of inferring the human's objective: The first is where we work with learning what things the human prioritizes when completing certain tasks to better utilize the information inherent in the environment to best learn those priorities such that a robot can replicate the given task. The second body of work surrounds Shared Autonomy where we work to have the robot better infer what task a human is going to do and thus better allow the robot to assist with this goal through using communicative interfaces to alter the information dynamic the robot uses to infer upon that human intent. Collectively, the work of the thesis works to push that the current inference methods for Human-Robot Interaction can be improved through the further progression of inference to best approximate the human's internal model in a given setting.

Social anxiety disorder (SAD) is a debilitating disorder marked by persistent fear of one or more social or performance situations that is associated with poor daily functioning in various areas of life. Most empirically-supported interventions for SAD are based on cognitive behavioral models that focus largely on reducing negative emotions. However, these approaches produce only modest rates of remission, suggesting that core components of SAD may not be sufficiently targeted by current treatments. Recent theoretical models have suggested that diminished sensitivity to reward may be a specific factor related to low positive affect (PA) and by extension social anxiety, yet no research has systematically examined this relationship. Additionally, working memory has been found to activate dopamine synthesis related to reward, however this relation has not been demonstrated in social anxiety. Accordingly, research proposed here sought to characterize PA and working memory, and determine whether reward sensitivity is altered in a self-reported socially anxious sample of 59 young adults. We hypothesized that social anxiety symptomatology would be inversely correlated with the magnitude of reward sensitivity as measured using the Reward Bias Task (RBT). Results within the full sample did not support our hypothesis; however, an unexpected relationship between PA and working memory emerged. Once using conservative data quality procedures, results indicated that the online version of the reward bias task demonstrated promising relationships with depression and working memory. Additionally, after controlling for depression, the restricted sample demonstrated a relationship between reward bias mean and working memory, and SPIN and diminished PA. / M.S. / Social anxiety disorder is related to poor daily functioning in various areas of life, such as school, work, and social functioning, and also increases the risk for depression and substance abuse. Over half of patients with the disorder remain symptomatic after treatment. Low levels of positive emotionality, or positive affect (PA), has been associated with social anxiety. Additionally, individuals with social anxiety are thought to have less reward seeking behaviors, which may be related to their working memory abilities. Our study looked at PA, reward and working memory in a sample of 59 socially anxious young adults. Within our full sample, we found that PA and working memory were related, such that participants with higher levels of PA also had better working memory abilities. Within our restricted sample of 17 socially anxious adults we found that reward seeking behaviors were related to depression and working memory. Additionally, after accounting for depression, reward seeking and working memory were related, and social anxiety symptoms and PA were related.

The reward system is a network of structures in the brain responsible for the feelings of pleasure, motivation, and decision making. It is comprised of the prefrontal cortex, orbitofrontal cortex (OFC), nucleus accumbens, ventral tegmental area, amygdala and the hippocampus, brain regions that come together to process rewarding stimuli, commonly referred to as rewards, to positively shape behavior. Rewards are well known to induce a range of molecular changes within the reward system that mediate reinforcing effects of rewards—neuroadaptations. These neuroadaptations can not only support adaptive behavior but also can mediate negative symptoms of psychiatric disorders such as anhedonia, withdrawal, or drug tolerance. Hence, aberrant functioning of the reward circuitry is present in patients with psychiatric disorders such as addiction, bipolar disorder, eating disorders, major depressive disorder, and schizophrenia. The molecular mechanisms underlying the function of the reward system are not fully understood and therefore elucidating the reward-induced neuroadaptations could inform future therapeutic approaches for symptoms caused by aberrant reward processing associated with psychiatric disorders. This thesis aims to characterize two types of neuroadaptations, circular RNA (circRNA) transcriptomic changes as well as N6-methyladenosine (m6A) epitranscriptomic adaptations, in the context of appetitive reward and opioids, respectively. First, we focused on describing circRNA related neuroadaptations within the OFC, and their functional implications, in the context of sucrose seeking behavior. We reported the first circRNA profile associated with appetitive reward and identified a regulation of 92 OFC circRNAs by sucrose self-administration. Among these changes we observed a downregulation of circNrxn3, a circRNA originating from neurexin 3 (Nrxn3), a gene involved in synaptogenesis, learning, and memory. Transcriptomic profiling via RNA sequencing and qPCR of the OFC following in vivo knock-down of circNrxn3 revealed differential regulation of genes associated with pathways important for learning and memory and altered splicing of Nrxn3. Furthermore, circNrxn3 knock-down enhanced sucrose self-administration and motivation for sucrose. Using RNA-immunoprecipitation, we reported binding of circNrxn3 to the known Nrxn3 splicing factor SAM68. circNrxn3 is the first reported circRNA capable of regulating reward behavior. In addition, circNrxn3-mediated interactions with SAM68 may impact subsequent downstream processing of RNAs such as the regulation of gene expression and splicing. We then went to characterize m6A epitranscriptomic adaptations induced by a commonly misused drug, the opioid morphine. m6A modifications have not been studied in opioid use disorder, despite being the most common RNA modification. We detected significant regulation of m6A-modifying enzymes in rat primary cortical cultures following morphine treatment, including AlkB Homolog 5 (Alkbh5). The m6a demethylase Alkbh5 functions as an m6A eraser, removing m6A modifications from mRNA. We hypothesized that chronic opioid exposure regulates m6A modifications through modulation of Alkbh5 and profiled m6A modifications in primary cortical cultures following chronic morphine exposure and Alkbh5 knock-down. We observed differential regulation of m6A modifications for 568 transcripts following morphine and 2865 following Alkbh5 knock-down. 103 transcripts were commonly regulated by both morphine and Alkbh5 knock-down, and the two treatments elicited concordant m6A epitranscriptomic profiles, suggesting that a subset of morphine-driven m6A modifications may be mediated through downregulation of Alkbh5 in cortical cultures. Together, this volume expands our understanding of molecular neuroadaptations induced by both appetitive reward and opioids. We have identified potential facilitators that could impact reward seeking, motivation and drug induced molecular adaptations that could inform future studies. / Biology

Feedback-based learning is a process in which decisions are made based on the previous feedback. This learning process is influenced by acute stress. However, different laboratory stressors elicit different physiological response patterns, which may influence feedback processing differently. Moreover, individual differences in stress reactivity may be associated with reward sensitivity. Therefore, the present study investigated the effects of psychosocial and physical stress on feedback-based learning. The relationship between stress reactivity and reward sensitivity was also examined. Ninety-two college-aged subjects were assigned into the mental arithmetic (MA) task or the cold pressor task (CPT) group. All subjects performed a feedback-based learning task prior to and after the stressor. Cardiovascular reactions, stress experiences, and learning outcomes were recorded during tasks. Trait differences in behavioral inhibition and activation (BIS/BAS) were also measured. Results indicated different patterns of cardiovascular reactions to the MA and CPT. Learning outcomes were differentially influenced by the MA and CPT. Moreover, subjective stress scores were negatively correlated with the learning rate in the pre-stress learning task. Additionally, BAS Drive subscale score was related to the processing of positive feedback. The results suggested that physical and psychosocial stress influence learning through distinct neural mechanisms and psychological processes. Motivational processes underlie the relationship between stress reactivity and reward sensitivity. This study extended research on stress and learning, and the findings have applied implications in various areas. / Ph. D. / People learn to make decisions based on their previous experiences. These processes are influenced by a wide range of non-learning factors, such as stress. Different types of stress may influence learning and decision-making differently. The present study examined the effects of physical and psychosocial stress on a feedback-based learning task. A cold pressor task and a mental arithmetic task were used to induce physical and psychosocial stress, respectively. The parameters that reflect learning processes and outcomes were calculated by using the standard action-value learning algorithm. Physiological measures, including electrocardiograph, respiration, and blood pressure, were recorded. Individual differences in motivation were measured by self-report questionnaires. The results showed that 1) physical and psychosocial stress induced different patterns of stress response; 2) the effects of the two types of stress on learning parameters and performance were different; 3) blood pressure was related to the effect of stress on learning; 4) individual differences in motivation was also related to feedback-based learning. Overall, the present results demonstrated the differences between the effects of the two types of stress, and contribute to the literature of learning and stress. These findings will guide future studies in this area and have applied implications in various areas.

After the remarkable expansion, and rapid growth of institutions of higher education (IHEs) between 1950 and 1970, campuses started to show signs of financial stress. By 1970, a number of institutions were faced with financial difficulties due to declining resources and steady increases in enrollment (Hansen & Stampen, 1981). The support that American society and government provided for IHEs earlier this century has decreased, in part due to criticism surrounding management techniques. The general public and state legislators are calling for increased accountability, assessment, graduation rates, and faculty productivity in the three traditional missions of higher education: teaching, research and service. These external demands have influenced the way work is conducted in all domains of the academy, including the faculty domain. There is little doubt that calls for improved undergraduate education, increased use of technology, a greater focus on applied (versus pure) research, and expanded outreach among others, have affected faculty teaching, research, and service activities. Yet research examining how this activities have shifted in recent years is very limited. In parallel vein, the recognition and reward system of IHEs (e.g., merit salary increases, teaching load, equipment and facilities) encourage faculty to engage in certain activities that are more valued than other activities. Traditional reward structures at many institutions have recognized research endeavors at the expense of teaching and service activities. It is reasonable to suggest, therefore, that if IHEs wish to shift attention among teaching, research and service endeavors of faculty, they need to design reward structures to recognize and value the activities they want faculty to undertake. There is very little evidence to suggest that IHEs have adapted their reward structures to promote such changes on the part of faculty. Therefore, the present study elicits information about faculty perceptions of the way their teaching, research, and service activities have shifted in recent years and how reward structures have or have not been adapted to support these shifts. The methodology used in this research is semi-structured interviews. Four departments at one university were selected for inclusion in the sample. From each department, ten faculty were randomly selected to participate in the study. The interviews were taped and transcribed to facilitate the analysis of the data. Conclusions drawn from the study suggest that changes in teaching, research, and service have taken place in recent years. The majority of changes related to the use of technology, followed by changes in class size, teaching style, curriculum reform and the use of teamwork. Faculty perceived that teaching, research, and service activities have changed in recent years in response to internal and external demands, however, the recognition and reward systems have not changed to reflect those changes. The results of this study suggest that both administrators and faculty may use these data to create new measures of faculty productivity that better reflect changes among the three university missions. The data may also provide other government and private agencies with different ways to assess institutional productivity. / Ph. D.

Reward-based learning is the ability to alter our future behavior following a novel reward. Dysregulation in this system has been linked to different forms of adult and pediatric psychopathologies such as mood disorders, for which it has proved to be an important treatment target given its link to broader health outcomes for these disorders. However, more research is needed to better understand its underlying mechanisms in the pediatric population. The current study examined how probabilistic reward learning, feedback-related negativity (FRN; an event-related potential from EEG), and dimensional ADHD symptom severity relate in adolescents with prominent mood symptoms. The final sample included 36 adolescents (72.2% female; aged 13 to 17) who completed a Probabilistic Reward Task (PRT) during EEG recording. Results revealed an inverse relationship between FRN mean amplitude and the reward learning score, independent of mood and ADHD symptoms. We also found that teens with increased overall ADHD symptom severity showed a larger (i.e., more negative voltage) FRN amplitude and a lower reward learning score. Exploratory analyses also showed that as ADHD inattentive symptom severity increased, FRN mean amplitude became more negative and reward learning score decreased. No significant relationship was found with ADHD hyperactive/impulsive symptom severity. In conclusion, our results showed that a poor modulation of behavior based on prior reward contingencies was related to an increase in dimensional ADHD symptom severity in a sample of adolescents with prominent mood difficulties. This behavioral dysfunction was also reflected by a blunted neural habituation to reward feedback as evidenced by a larger FRN mean amplitude. Additionally, exploratory analyses highlighted how the relationship between overall ADHD symptom severity and FRN may be driven especially by symptoms of inattention vs. hyperactivity/impulsivity. Results suggest deficits in reward learning that could impact response to behavioral therapies in youth with mood disorders and comorbid inattentive ADHD.

Chronic nicotine use has been linked to increased sensitivity to nondrug rewards as well as improvement in mood among individuals with depression, and these effects have been hypothesized to be mediated through alternations in striatal dopamine activity. Similarly, chronic nicotine use is hypothesized to influence the mechanisms by which healthy and depressed individuals learn about rewards in their environment. However, the specific behavioral and neural mechanisms by which nicotine influences the learning process is poorly understood. Here, we use a probabilistic learning task, functional magnetic resonance imaging and neurocomputational analyses, to show that chronic smoking is associated with higher reward sensitivity, along with lower learning rate and striatal prediction error signal. Further, we show that these effects do not differ between individuals with and without major depressive disorder (MDD). In addition, a negative correlation between reward sensitivity and striatal prediction error signal was found among smokers, consistent with the suggestion that enhanced tonic dopamine associated with increased reward sensitivity leads to an attenuation of phasic dopamine activity necessary for updating of reward value during learning. / Master of Science / Nicotine use has been associated with increased sensitivity to nondrug rewards and improvement in mood among individuals with depression, and these effects maybe attributed to neural activity in the striatum, a brain region related to reward perception and learning. Chronic nicotine may also influence reward learning in healthy and depressed individuals but this influence is poorly understood. Therefore, we use a computerized learning task to measure participants’ behavioral performance, functional magnetic resonance imaging to collect their brain activity data and neurocomputational analyses to examine their learning process. We showthat, compared to nonsmokers, chronic smokers perceive rewards as more rewarding (higher reward sensitivity), they learn the value of a reward slower (lower learningrate) and the neural activity in their striatum is weaker in the learning process. Moreover, we show that these effects do not differ between individuals with and without depression.

The study’s objective was to assess whether resting-state regional functional connectivity and current source density (CSD) measured during smoking abstinence predict smoking progression across 18 months, depressive traits, and nicotine-enhanced reward sensitivity (NERS) in young light-nicotine (NIC) smokers using low-resolution brain electromagnetic tomography analysis (LORETA). A secondary goal was to assess whether depressive traits moderate the ability of connectivity and regional CSD to predict NERS. Brain regions of interest (ROIs) hypothesized to predict smoking progression, NERS, and depressive traits include structures with high-density nicotinic acetylcholine receptors (nAChRs) and reward-related areas. A total of N=108, 14-hour NIC-deprived young (age 18-24) light (5-35 NIC uses/week) smokers underwent electroencephalogram (EEG) recording while at rest (i.e., viewed a white crosshair on a black background) for 8 minutes then completed the PRT, an assessment of reward sensitivity, after smoking a placebo (0.05 mg NIC) and NIC (0.8 mg NIC) cigarette using a within-subjects design allowing for the assessment of NIC-induced changes in reward sensitivity. All EEG power and LORETA activity bands underwent regression analysis to discover if EEG-assessed brain activity can predict smoking progression, depressive traits, NERS, and their potential interaction. Localized brain regions include 1) reward-related structures, 2) depressive trait-related structures, and 3) large-scale neural (e.g., salience network (SN), default mode network (DMN), executive control network (ECN)) and substance use disorder networks (e.g., orbital frontal cortex (OFC), insula, dorsal lateral prefrontal cortex (dlPFC) anterior cingulate cortex (ACC)). Weaker resting-state connectivity (rsC) between the insula and ACC (i.e., SN) predicted greater smoking progression at 18 months (theta1 and theta2) and greater depressive traits (delta and theta1), while greater rsC within the SN predicted greater NERS (alpha2 and beta 2/3[23.19 – 25.14 Hz]). Greater NERS was also predicted by greater alpha2 connectivity between the 1) ACC and posterior cingulate cortex (PCC) and 2) ACC and left dlPFC. Greater depressive traits were also predicted by 1) weaker delta and theta2 connectivity between the bilateral insula, 2) weaker delta, theta1, and theta2 between the insula and dlPFC, 3) weaker delta and theta1 between the insula and subgenual cortex, 4) greater theta2 in the right vs. left default mode, and 5) greater delta (2.44 – 3.41 Hz) in the left vs. right default mode network. Both greater depressive traits and greater NERS were predicted by weaker 1) theta2/alpha1 (6.59 – 9.52 Hz) between the insula and dlPFC and 2) alpha1 (7.5 – 9.5 Hz) between the left orbital frontal cortex and right dlPFC. These findings provide the first evidence that differences in EEG-assessed brain connectivity in young light smokers are associated with nicotine-enhanced reward sensitivity, depressive traits, and smoking progression. Notably, weaker low-frequency rsC within the salience network predicted depressive traits and smoking progression, while greater high-frequency rsC predicted greater nicotine-enhanced reward sensitivity. These findings suggest that salience network rsC and drug-enhanced reward sensitivity may be useful tools and potential endophenotypes for reward sensitivity and drug-dependence research.