19 resultados para Emotion, emotion expression, emotion regulation, affect intensity, clarity, self-monitoring, ambivalence, acting, deception

em Duke University


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Individual differences in affect intensity are typically assessed with the Affect Intensity Measure (AIM). Previous factor analyses suggest that the AIM is comprised of four weakly correlated factors: Positive Affectivity, Negative Reactivity, Negative Intensity and Positive Intensity or Serenity. However, little data exist to show whether its four factors relate to other measures differently enough to preclude use of the total scale score. The present study replicated the four-factor solution and found that subscales derived from the four factors correlated differently with criterion variables that assess personality domains, affective dispositions, and cognitive patterns that are associated with emotional reactions. The results show that use of the total AIM score can obscure relationships between specific features of affect intensity and other variables and suggest that researchers should examine the individual AIM subscales.

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Empirical studies of education programs and systems, by nature, rely upon use of student outcomes that are measurable. Often, these come in the form of test scores. However, in light of growing evidence about the long-run importance of other student skills and behaviors, the time has come for a broader approach to evaluating education. This dissertation undertakes experimental, quasi-experimental, and descriptive analyses to examine social, behavioral, and health-related mechanisms of the educational process. My overarching research question is simply, which inside- and outside-the-classroom features of schools and educational interventions are most beneficial to students in the long term? Furthermore, how can we apply this evidence toward informing policy that could effectively reduce stark social, educational, and economic inequalities?

The first study of three assesses mechanisms by which the Fast Track project, a randomized intervention in the early 1990s for high-risk children in four communities (Durham, NC; Nashville, TN; rural PA; and Seattle, WA), reduced delinquency, arrests, and health and mental health service utilization in adolescence through young adulthood (ages 12-20). A decomposition of treatment effects indicates that about a third of Fast Track’s impact on later crime outcomes can be accounted for by improvements in social and self-regulation skills during childhood (ages 6-11), such as prosocial behavior, emotion regulation and problem solving. These skills proved less valuable for the prevention of mental and physical health problems.

The second study contributes new evidence on how non-instructional investments – such as increased spending on school social workers, guidance counselors, and health services – affect multiple aspects of student performance and well-being. Merging several administrative data sources spanning the 1996-2013 school years in North Carolina, I use an instrumental variables approach to estimate the extent to which local expenditure shifts affect students’ academic and behavioral outcomes. My findings indicate that exogenous increases in spending on non-instructional services not only reduce student absenteeism and disciplinary problems (important predictors of long-term outcomes) but also significantly raise student achievement, in similar magnitude to corresponding increases in instructional spending. Furthermore, subgroup analyses suggest that investments in student support personnel such as social workers, health services, and guidance counselors, in schools with concentrated low-income student populations could go a long way toward closing socioeconomic achievement gaps.

The third study examines individual pathways that lead to high school graduation or dropout. It employs a variety of machine learning techniques, including decision trees, random forests with bagging and boosting, and support vector machines, to predict student dropout using longitudinal administrative data from North Carolina. I consider a large set of predictor measures from grades three through eight including academic achievement, behavioral indicators, and background characteristics. My findings indicate that the most important predictors include eighth grade absences, math scores, and age-for-grade as well as early reading scores. Support vector classification (with a high cost parameter and low gamma parameter) predicts high school dropout with the highest overall validity in the testing dataset at 90.1 percent followed by decision trees with boosting and interaction terms at 89.5 percent.

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One hundred fifteen undergraduates rated 15 word-cued memories and their 3 most negatively stressful, 3 most positive, and 7 most important events and completed tests of personality and depression. Eighty-nine also recorded involuntary memories online for 1 week. In the first 3-way comparisons needed to test existing theories, comparisons were made of memories of stressful events versus control events and involuntary versus voluntary memories in people high versus low in posttraumatic stress disorder (PTSD) symptom severity. For all participants, stressful memories had more emotional intensity, more frequent voluntary and involuntary retrieval, but not more fragmentation. For all memories, participants with greater PTSD symptom severity showed the same differences. Involuntary memories had more emotional intensity and less centrality to the life story than voluntary memories. Meeting the diagnostic criteria for traumatic events had no effect, but the emotional responses to events did. In 533 undergraduates, correlations among measures were replicated and the Negative Intensity factor of the Affect Intensity Measure correlated with PTSD symptom severity. No special trauma mechanisms were needed to account for the results, which are summarized by the autobiographical memory theory of PTSD.

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The intensity and valence of 30 emotion terms, 30 events typical of those emotions, and 30 autobiographical memories cued by those emotions were each rated by different groups of 40 undergraduates. A vector model gave a consistently better account of the data than a circumplex model, both overall and in the absence of high-intensity, neutral valence stimuli. The Positive Activation - Negative Activation (PANA) model could be tested at high levels of activation, where it is identical to the vector model. The results replicated when ratings of arousal were used instead of ratings of intensity for the events and autobiographical memories. A reanalysis of word norms gave further support for the vector and PANA models by demonstrating that neutral valence, high-arousal ratings resulted from the averaging of individual positive and negative valence ratings. Thus, compared to a circumplex model, vector and PANA models provided overall better fits.

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Autobiographical memories may be recalled from two different perspectives: Field memories in which the person seems to remember the scene from his/her original point of view and observer memories in which the rememberer sees him/herself in the memory image. Here, 122 undergraduates participated in an experiment examining the relation between field vs. observer perspective in memory for 10 different emotional states, including both positive and negative emotions and emotions associated with high vs. low intensity. Observer perspective was associated with reduced sensory and emotional reliving across all emotions. This effect was observed for naturally occurring memory perspective and when participants were instructed to change their perspective from field to observer, but not when participants were instructed to change perspective from observer to field.

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Emotional and attentional functions are known to be distributed along ventral and dorsal networks in the brain, respectively. However, the interactions between these systems remain to be specified. The present study used event-related functional magnetic resonance imaging (fMRI) to investigate how attentional focus can modulate the neural activity elicited by scenes that vary in emotional content. In a visual oddball task, aversive and neutral scenes were presented intermittently among circles and squares. The squares were frequent standard events, whereas the other novel stimulus categories occurred rarely. One experimental group [N=10] was instructed to count the circles, whereas another group [N=12] counted the emotional scenes. A main effect of emotion was found in the amygdala (AMG) and ventral frontotemporal cortices. In these regions, activation was significantly greater for emotional than neutral stimuli but was invariant to attentional focus. A main effect of attentional focus was found in dorsal frontoparietal cortices, whose activity signaled task-relevant target events irrespective of emotional content. The only brain region that was sensitive to both emotion and attentional focus was the anterior cingulate gyrus (ACG). When circles were task-relevant, the ACG responded equally to circle targets and distracting emotional scenes. The ACG response to emotional scenes increased when they were task-relevant, and the response to circles concomitantly decreased. These findings support and extend prominent network theories of emotion-attention interactions that highlight the integrative role played by the anterior cingulate.

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We sought to map the time course of autobiographical memory retrieval, including brain regions that mediate phenomenological experiences of reliving and emotional intensity. Participants recalled personal memories to auditory word cues during event-related functional magnetic resonance imaging (fMRI). Participants pressed a button when a memory was accessed, maintained and elaborated the memory, and then gave subjective ratings of emotion and reliving. A novel fMRI approach based on timing differences capitalized on the protracted reconstructive process of autobiographical memory to segregate brain areas contributing to initial access and later elaboration and maintenance of episodic memories. The initial period engaged hippocampal, retrosplenial, and medial and right prefrontal activity, whereas the later period recruited visual, precuneus, and left prefrontal activity. Emotional intensity ratings were correlated with activity in several regions, including the amygdala and the hippocampus during the initial period. Reliving ratings were correlated with activity in visual cortex and ventromedial and inferior prefrontal regions during the later period. Frontopolar cortex was the only brain region sensitive to emotional intensity across both periods. Results were confirmed by time-locked averages of the fMRI signal. The findings indicate dynamic recruitment of emotion-, memory-, and sensory-related brain regions during remembering and their dissociable contributions to phenomenological features of the memories.

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Very long-term memory for popular music was investigated. Older and younger adults listened to 20-sec excerpts of popular songs drawn from across the 20th century. The subjects gave emotionality and preference ratings and tried to name the title, artist, and year of popularity for each excerpt. They also performed a cued memory test for the lyrics. The older adults' emotionality ratings were highest for songs from their youth; they remembered more about these songs, as well. However, the stimuli failed to cue many autobiographical memories of specific events. Further analyses revealed that the older adults were less likely than the younger adults to retrieve multiple attributes of a song together (i.e., title and artist) and that there was a significant positive correlation between emotion and memory, especially for the older adults. These results have implications for research on long-term memory, as well as on the relationship between emotion and memory.

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Phenomenologically, humans effectively label and report feeling distinct emotions, yet the extent to which emotions are represented categorically in nervous system activity is controversial. Theoretical accounts differ in this regard, some positing distinct emotional experiences emerge from a dimensional representation (e.g., along axes of valence and arousal) whereas others propose emotions are natural categories, with dedicated neural bases and associated response profiles. This dissertation aims to empirically assess these theoretical accounts by examining how emotions are represented (either as disjoint categories or as points along continuous dimensions) in autonomic and central nervous system activity by integrating psychophysiological recording and functional neuroimaging with machine-learning based analytical methods. Results demonstrate that experientially, emotional events are well-characterized both along dimensional and categorical frameworks. Measures of central and peripheral responding discriminate among emotion categories, but are largely independent of valence and arousal. These findings suggest dimensional and categorical aspects of emotional experience are driven by separable neural substrates and demonstrate that emotional states can be objectively quantified on the basis of nervous system activity.

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To investigate the neural systems that contribute to the formation of complex, self-relevant emotional memories, dedicated fans of rival college basketball teams watched a competitive game while undergoing functional magnetic resonance imaging (fMRI). During a subsequent recognition memory task, participants were shown video clips depicting plays of the game, stemming either from previously-viewed game segments (targets) or from non-viewed portions of the same game (foils). After an old-new judgment, participants provided emotional valence and intensity ratings of the clips. A data driven approach was first used to decompose the fMRI signal acquired during free viewing of the game into spatially independent components. Correlations were then calculated between the identified components and post-scanning emotion ratings for successfully encoded targets. Two components were correlated with intensity ratings, including temporal lobe regions implicated in memory and emotional functions, such as the hippocampus and amygdala, as well as a midline fronto-cingulo-parietal network implicated in social cognition and self-relevant processing. These data were supported by a general linear model analysis, which revealed additional valence effects in fronto-striatal-insular regions when plays were divided into positive and negative events according to the fan's perspective. Overall, these findings contribute to our understanding of how emotional factors impact distributed neural systems to successfully encode dynamic, personally-relevant event sequences.

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College students generated autobiographical memories from distinct emotional categories that varied in valence (positive vs. negative) and intensity (high vs. low). They then rated various perceptual, cognitive, and emotional properties for each memory. The distribution of these emotional memories favored a vector model over a circumplex model. For memories of all specific emotions, intensity accounted for significantly more variance in autobiographical memory characteristics than did valence or age of the memory. In two additional experiments, we examined multiple memories of emotions of high intensity and positive or negative valence and of positive valence and high or low intensity. Intensity was a more consistent predictor of autobiographical memory properties than was valence or the age of the memory in these experiments as well. The general effects of emotion on autobiographical memory properties are due primarily to intensity differences in emotional experience, not to benefits or detriments associated with a specific valence.

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Understanding how genes affect behavior is critical to develop precise therapies for human behavioral disorders. The ability to investigate the relationship between genes and behavior has been greatly advanced over the last few decades due to progress in gene-targeting technology. Recently, the Tet gene family was discovered and implicated in epigenetic modification of DNA methylation by converting 5-methylcytosine to 5-hydroxymethylcytosine (5hmC). 5hmC and its catalysts, the TET proteins, are highly abundant in the postnatal brain but with unclear functions. To investigate their neural functions, we generated new lines of Tet1 and Tet3 mutant mice using a gene targeting approach. We designed both mutations to cause a frameshift by deleting the largest coding exon of Tet1 (Tet1Δe4) and the catalytic domain of Tet3 (Tet3Δe7-9). As Tet1 is also highly expressed in embryonic stem cells (ESCs), we generated Tet1 homozygous deleted ESCs through sequential targeting to compare the function of Tet1 in the brain to its role in ESCs. To test our hypothesis that TET proteins epigenetically regulate transcription of key neural genes important for normal brain function, we examined transcriptional and epigenetic differences in the Tet1Δe4 mouse brain. The oxytocin receptor (OXTR), a neural gene implicated in social behaviors, is suggested to be epigenetically regulated by an unknown mechanism. Interestingly, several human studies have found associations between OXTR DNA hypermethylation and a wide spectrum of behavioral traits and neuropsychiatric disorders including autism spectrum disorders. Here we report the first evidence for an epigenetic mechanism of Oxtr transcription as expression of Oxtr is reduced in the brains of Tet1Δe4-/- mice. Likewise, the CpG island overlapping the promoter of Oxtr is hypermethylated during early embryonic development and persists into adulthood. We also discovered altered histone modifications at the hypermethylated regions, indicating the loss of TET1 has broad effects on the chromatin structure at Oxtr. Unexpectedly, we discovered an array of novel mRNA isoforms of Oxtr that are selectively reduced in Tet1Δe4-/- mice. Additionally, Tet1Δe4-/- mice display increased agonistic behaviors and impaired maternal care and short-term memory. Our findings support a novel role for TET1 in regulating Oxtr expression by preventing DNA hypermethylation and implicate TET1 in social behaviors, offering novel insight into Oxtr epigenetic regulation and its role in neuropsychiatric disorders.

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BACKGROUND: Several studies have noted that genetic variants of SCARB1, a lipoprotein receptor involved in reverse cholesterol transport, are associated with serum lipid levels in a sex-dependent fashion. However, the mechanism underlying this gene by sex interaction has not been explored. METHODS: We utilized both epidemiological and molecular methods to study how estrogen and gene variants interact to influence SCARB1 expression and lipid levels. Interaction between 35 SCARB1 haplotype-tagged polymorphisms and endogenous estradiol levels was assessed in 498 postmenopausal Caucasian women from the population-based Rancho Bernardo Study. We further examined associated variants with overall and SCARB1 splice variant (SR-BI and SR-BII) expression in 91 human liver tissues using quantitative real-time PCR. RESULTS: Several variants on a haplotype block spanning intron 11 to intron 12 of SCARB1 showed significant gene by estradiol interaction affecting serum lipid levels, the strongest for rs838895 with HDL-cholesterol (p=9.2x10(-4)) and triglycerides (p=1.3x10(-3)) and the triglyceride:HDL cholesterol ratio (p=2.7x10(-4)). These same variants were associated with expression of the SR-BI isoform in a sex-specific fashion, with the strongest association found among liver tissue from 52 young women<45 years old (p=0.002). CONCLUSIONS: Estrogen and SCARB1 genotype may act synergistically to regulate expression of SCARB1 isoforms and impact serum levels of HDL cholesterol and triglycerides. This work highlights the importance of considering sex-dependent effects of gene variants on serum lipid levels.