Browsing by Author "LaBar, Kevin S"

Emotions are pervasive in daily life, and a rich literature has documented how emotional stimuli and events disrupt ongoing processing and place heightened demands on control. Yet the executive control mechanisms that subsequently resolve that interference have not been well characterized. Although many failures of executive control have emotion at their core, numerous questions remain in the field regarding interactions between emotion and executive control. How do executive processes act on affective representations? Are emotional representations less amenable to control? Do distinct processes or neural networks govern their control? The present dissertation addresses these questions by investigating the neural systems and cognitive processes that support executive control in the face of interference from affective sources. Whereas previous research has emphasized the bottom-up impact of emotion on cognition, this dissertation will investigate how top-down executive control signals modulate affect's influence on cognition. Combining behavioral techniques with neuroimaging methodologies, this dissertation characterizes the interactive relationship between affective processes and top-down executive control and the ramifications of that interaction for promoting adaptive behavior.

Cognitive and behavioral phenomena related to affective interference resolution are explored in a series of research projects spanning attention and memory. Task-irrelevant affective representations may disrupt performance, but this interference appears to be dependent on top-down factors and can be resolved by executive mechanisms. Interference resolution mechanisms act on representations both of stimuli in the environment and information stored in memory. The findings reported here support emotion's capacity to disrupt executive processing but also highlight the role executive control plays in overcoming that interference in order to promote adaptive behavior.

Disgust features prominently in many facets of human life, from dining etiquette to spider phobia to genocide. For some applications, such as public health campaigns, it might be desirable to know how to increase disgust, whereas for things like legal and political decision-making it might be desirable to know how to suppress disgust. However, interventions in neither direction can take place until the basic structure of disgust is better understood. Disgust is notoriously difficult to model, largely due to the fact that it is a highly individually variable, multifactorial construct, with a great breadth of eliciting stimuli and contexts. As such, many of the theories which attempt to comprehensively describe disgust come into conflict with each other, impeding progress towards more efficient and effective ways of predicting disgust-related outcomes. The aim of this dissertation is to explore the possible contribution of data-driven methods to resolving theoretical questions, evaluating extant theories, and the generation of novel conceptual structures from bottom-up insights. Data were collected to sample subjective experience as well as psychophysiological reactivity. Through the use of techniques such as factor analysis and support vector machine classification, several insights about the approaching the study of disgust emerged. In one study, results indicated that the level of abstraction across subdivisions of disgust is not necessarily constant, in spite of a priori theoretical expectations: in other words, some domains of disgust are more general than others, and recognizing as much will improve the predictive validity of a model. Another study highlighted the importance of recognizing one particular category of disgust elicitors (mutilation) as a separate entity from the superordinate domains into which extant theories placed it. Finally, another study investigated the influence of concurrent emotions on variability in disgust physiology, and demonstrated the difference in the representations of the structure of disgust between the level of subjective experience and the level of autonomic activity. In total, the studies conducted as part of this dissertation suggest that for constructs as complex as disgust, data-driven approaches investigations can be a boon to scientists looking to evaluate the quality of the theoretical tools at their disposal.

Distancing is a type of emotion regulation that involves simulating a new perspective to alter the psychological distance and emotional impact of a stimulus. The effectiveness and versatility of distancing make it a promising skill for clinical applications. However, the specific neurocognitive mechanisms of this emotion regulation tactic are poorly defined relative to the broader strategy of reappraisal. More focused investigation of these mechanisms would promote further understanding of the processes underlying distancing and potentially improve its applications. Therefore, I first synthesized literature on the component processes of distancing to propose a preliminary neurocognitive model. I tested the neural architecture of this model through a meta-analysis of fMRI literature, and then further validated and refined it by comparing three forms of distancing in an fMRI study. Finally, I investigated self-projection and its relation to the left temporoparietal junction using transcranial magnetic stimulation. The results of this work supported the neural architecture of the proposed model and suggested subtle differences in the recruitment of parietal regions across forms of distancing. No conclusions could be drawn regarding the specific functional contribution of the left temporoparietal junction, but I found that distancing performance was facilitated by repeated use, reinforcing the utility of this tactic for applied contexts. This model contributes new insights into the neurocognitive mechanisms of distancing, informs the optimal use of this tactic, and provides a framework for future research and interventions.

Our perception of time is not veridical but rather is consistently modulating by changing dynamics in our environment. Anecdotal experiences suggest that emotions can be powerful modulators of time perception; nevertheless, the mechanisms underlying emotion-induced temporal distortions remain unclear. Widely accepted pacemaker-accumulator models of time perception suggest that changes in arousal and attention have unique influences on temporal judgments and contribute to emotional distortions of time perception. However, such models conflict with current views of arousal and attention and their interaction from the perspective of affective and cognitive science. The aim of this dissertation was to more clearly examine the role of arousal and attention in driving emotion-induced temporal distortions by explicitly manipulating and measuring these constructs using well-established timing procedures within the context of affective manipulations induced via classical conditioning and drug administration. Measures of physiological arousal and subjective measures of top-down attention to emotional stimuli were assessed both within and across subjects. The findings reported here suggest that current models of time perception do not adequately explain the variability in emotion-induced temporal distortions. Instead these findings provide support for a new theoretical model of emotion-induced temporal distortions proposed in the current manuscript that emphasizes both the unique and interactive influences of arousal and attention on time perception, dependent on temporal dynamics, event relationships, and individual differences. Collectively, these findings may point to plausible neurobiological mechanisms of emotion-induced temporal distortions and have important implications for our understanding of how emotions may modulate our perceptual experiences in service of adaptively responding to biologically relevant stimuli.

Emotions play a fundamental role in how we remember the past. Decades of neuroscience research have uncovered the neural mechanisms that help explain why we selectively remember emotional experiences, often at the expense of more neutral ones. What remains less understood, however, are the factors that govern biased access to certain emotional memories over others. Discerning such effects can provide insight to aberrant memory biases that perpetuate psychopathological symptoms in a wide range of clinical disorders. Here I present three different routes to emotional memory bias, stemming from factors at encoding, consolidation, or retrieval that selectively influence what we remember from the past and how we remember it. First, I tested the influence of spatial proximity during initial exposure to threatening stimuli, finding that threats encountered in near space activate a distinct neural fear circuit that predicts enhanced reinstatement the next day. Second, I tested the influence of mood during consolidation, finding that mood after encoding retroactively strengthens mood-congruent content into long-term memory. Third, I tested how memories can be modified at retrieval by manipulating conceptual and perceptual features of the remembered event, finding that these two forms of reconstruction recruit distinct neural profiles. Finally, I summarize how these studies inform memory biases in mood disorders, while also discussing related work on emotion representation and dispositional biases in retrieval tendencies.