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Browsing by Author "Silverman, Merav"

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    Altered Patterns Of Amygdala Activation And Functional Connectivity In Individuals With Borderline Personality Disorder During Nonconscious And Conscious Emotion Processing
    (2015-05) Silverman, Merav
    Objective: Borderline personality disorder (BPD) is characterized by emotion dysregulation, which underlies symptoms such as suicidality and impulsivity. Neuroimaging provides a method for probing the biological basis of emotion dysregulation. We examined neural activation and connectivity in individuals with BPD and healthy controls (HCs) during nonconscious and conscious emotion processing. Methods: 21 unmedicated individuals with BPD and 10 healthy controls (HCs) completed an fMRI task viewing masked and unmasked happy and fearful faces. Whole brain and region of interest (ROI) analyses examined between group differences in activation. Differences in amygdala connectivity were assessed using psychophysiological interactions (PPI). Results: During unmasked emotion processing, whole-brain and ROI analyses reveal greater activation in the amygdala and hippocampus and PPI analyses show greater connectivity between the amygdala and subgenual anterior cingulate cortex (sgACC) in participants with BPD. In HCs, greater connectivity was found between the amygdala and areas of the prefrontal cortex. During masked emotion processing, HCs show greater activation in frontal and temporal regions and greater connectivity between the amygdala and temporal regions. Conclusion: Results find altered frontal-limbic activation and connectivity in individuals with BPD relative to HCs, varying depending on whether the emotional stimulus is consciously or nonconsciously perceived. This suggests that there may be more than one neural pathway underlying emotion dysregulation in BPD.
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    Operationalizing Neuroticism Using Task-Based Fmri And Psychological Measures In A Large Sample
    (2018-08) Silverman, Merav
    Background: Trait neuroticism is characterized by individual differences in the experience of, and proclivity toward, negative emotions. As such, neuroticism has been associated with increased rates of transdiagnostic psychopathology. The emerging field of personality neuroscience aims to explain the underlying neurobiological sources for individual personality variation. A limited number of studies, mostly in relatively small samples, have examined the relationship between individual differences in trait levels of neuroticism and patterns of brain activation, assessed using functional neuroimaging, typically during negative emotion processing tasks. In particular, studies have suggested an association between neuroticism and magnitude of amygdala activation, rate of amygdala habituation, and amygdala-prefrontal cortex connectivity. The results of these studies are, at times, contradictory and generally inconclusive. Methods: In the current project, we examine the relationship between trait neuroticism and these three hypothesized neural markers (amygdala activation, amygdala habituation, and amygdala-prefrontal connectivity) during negative emotion processing in a large sample (N=663) of twins from the Minnesota Center for Twin and Family Research. Participants were scanned during a negative emotional face-matching task. For Aim 1 of this project, twin pairs were broken up such that we examined each hypothesized marker in a group of first-born twins and replicated the analyses in a group of second-born twins, resulting in two large sub-samples. Using a series of general linear models (GLM) in FSL software, amygdala activation, amygdala habituation, and amygdala-prefrontal functional connectivity (assessed using a psychophysiological interaction [PPI]) in response to negative face processing were analyzed and neuroticism scores were included as a regressor in the models. For Aim 2, this study utilized a multivariate approach in the full sample by developing a psychoneurometric model in an effort to refine the construct of trait neuroticism. This method utilizes multiple indicators across different measurement domains (e.g., psychological domain, neuroscientifically-derived domain) in an attempt to better characterize the latent trait of neuroticism. Three self-report measures for neuroticism and three hypothesized neural measures of neuroticism (magnitude of amygdala activation, rate of amygdala habituation, and amygdala-prefontal cortex connectivity) were used in attempt to build a psychoneurometric model to better characterize trait neuroticism. Results: Across both twin groups, neuroticism did not show a reliable association with magnitude of brain activation in the amygdala or with amygdala habituation during the negative emotional face matching. Across both twin groups, PPI analyses revealed that amygdala–vmPFC connectivity during emotional face matching was positively correlated with neuroticism scores. Results of the psychoneurometric model suggest that there is no reliable relationship among the three hypothesized neural markers or between the hypothesized neural markers and the self-report measures of neuroticism. Conclusions: The corticolimbic circuitry involving the vmPFC and amygdala has been associated with emotion regulation and increased vmPFC activity has been correlated with reduced activation in the amygdala. The results of the current study suggest that the regulatory function of the vmPFC may be diminished in individuals who are higher in neuroticism or that emotion regulation may be more effortful in these individuals. Additionally, these findings, replicated across two large samples, suggest that magnitude of amygdala activation and rate of amygdala habituation may not serve as useful neural correlates of neuroticism. There is evidence that habituation of other brain regions might be an area deserving further research. Taken together, these findings suggest that trait neuroticism may represent a failure in top-down control and regulation of emotional reactions, rather than from overactive, emotion perception processes. The current project highlights the challenges of employing fMRI in building a psychoneurometric model for personality domains and suggests future directions for such studies.