scholarly journals Borderline personality disorder classification based on brain network measures during emotion regulation

2020 ◽  
Author(s):  
Henk Cremers ◽  
Linda van Zutphen ◽  
Sascha Duken ◽  
Gregor Domes ◽  
Andreas Sprenger ◽  
...  
Keyword(s):  
Emotion Regulation ◽  
Borderline Personality Disorder ◽  
Personality Disorder ◽  
Brain Network ◽  
Borderline Personality ◽  
Future Research ◽  
Support Vector ◽  
Classification Analysis ◽  
Network Analyses ◽  
Network Measures

AbstractBorderline Personality Disorder (BPD) is characterized by an increased emotional sensitivity and dysfunctional capacity to regulate emotions. While amygdala and prefrontal cortex interactions are regarded as the critical neural mechanisms underlying these problems, the empirical evidence hereof is inconsistent. In the current study, we aimed to systematically test different properties of brain connectivity and evaluate the predictive power to detect borderline personality disorder. Patients with borderline personality disorder (n = 51), cluster C personality disorder (n = 26) and non-patient controls (n = 44), performed an fMRI emotion regulation task. Brain network analyses focused on two properties of task-related connectivity: phasic refers to task-event dependent changes in connectivity, while tonic was defined as task-stable background connectivity. Three different network measures were estimated (strength, local efficiency, and participation coefficient) and entered as separate models in a nested cross-validated linear support vector machine classification analysis. Borderline personality disorder vs. non-patient controls classification showed a balanced accuracy of 55%, which was not significant under a permutation null-model, p = 0.23. Exploratory analyses did indicate that the tonic strength model was the highest performing model (balanced accuracy 62%), and the amygdala was one of the most important features. Despite being one of the largest data-sets in the field of BPD fMRI research, the sample size may have been limited for this type of classification analysis. The results and analytic procedures do provide starting points for future research, focusing on network measures of tonic connectivity, and potentially focusing on subgroups of BPD.

scholarly journals Borderline Personality Disorder classification based on brain network centrality during emotion regulation

2019 ◽  
Author(s):  
Henk Cremers ◽  
Linda van Zutphen ◽  
Sascha Béla Duken ◽  
Gregor Domes ◽  
Andreas Sprenger ◽  
...  
Keyword(s):  
Emotion Regulation ◽  
Borderline Personality Disorder ◽  
Personality Disorder ◽  
Null Model ◽  
Brain Network ◽  
Borderline Personality ◽  
Future Research ◽  
Support Vector ◽  
Network Analyses ◽  
Network Measures

Background: Borderline Personality Disorder is characterized by an increased emotional sensitivity and dysfunctional capacity to regulate emotions. While amygdala and prefrontal cortex interactions are regarded as the key neural mechanisms underlying these problems, the empirical evidence hereof is inconsistent. In the current study we aimed to systematically test different properties of brain connectivity and evaluate the predictive power to detect borderline personality disorder. Methods: Patients with borderline personality disorder (n=51), cluster C personality disorder (n=26) and non-patient controls (n=44) performed an fMRI emotion regulation task. Brain network analyses focused on two properties of task related connectivity: phasic refers to task-event dependent changes in connectivity while tonic was defined as task-stable background connectivity. Three different network measures were estimated (strength, local efficiency and participation coefficient) and then entered as separate models in a nested cross-validated linear support vector machine classification analysis. Results: Borderline personality disorder vs. non-patient controls classification showed a balanced accuracy of 55%, which was not significant under a permutation null-model, p=0.23. Exploratory analysis did indicate that the tonic strength model was the highest performing model (balanced accuracy 62%), and the amygdala was one of the most important features. Conclusions: Despite being one of the largest data-sets in the field of BPD fMRI research, the sample size may have been limited for this type of classification analyses. The results and analytic procedures do provide starting points for future research, focusing on network measures of tonic connectivity, and potentially focusing on subgroups of BPD.

scholarly journals Development and validation of an emotional picture set of self-injury (EPSI) for borderline personality disorder: protocol for a validation study

BMJ Open ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. e027063 ◽  
Author(s):  
Katharina Bachmann ◽  
Marcel Schulze ◽  
Peter Sörös ◽  
Christian Schmahl ◽  
Alexandra Philipsen
Keyword(s):  
Emotion Regulation ◽  
Borderline Personality Disorder ◽  
Personality Disorder ◽  
Validation Study ◽  
Emotional Responses ◽  
Borderline Personality ◽  
Future Research ◽  
Self Injury ◽  
Emotional Picture ◽  
Development And Validation

IntroductionBorderline personality disorder (BPD) is a severe psychiatric disorder that is characterised by major problems in emotion regulation. Affected persons frequently engage in non-suicidal self-injury (NSSI) to regulate emotions. NSSI is associated with high emotionality in patients with BPD and it can be expected that stimuli depicting scenes of NSSI elicit an emotional response indicative of BPD. The present study protocol describes the development and validation of an emotional picture set of self-injury (EPSI) to advance future research on emotion regulation in BPD.Methods and analysisThe present validation study aims to develop and validate an emotional picture set relevant for BPD. Emotional responses to EPSI as well as to a neutral picture set will be investigated in a sample of 30 patients with BPD compared with 30 matched, healthy controls and to 30 matched depressive controls. Emotional responses will be assessed by heart rate variability, facial expression and Self-Assessment Manikin.Ethics and disseminationEthics approval was obtained by the medical ethics committee of the Carl-von-Ossietzky University of Oldenburg, Germany (registration: 2017–044). The results of the trial will be submitted for publication in a peer-reviewed journal.Trial registration numberNCT03149926; Pre-results.

scholarly journals Borderline Personality Disorder Classification Based on Brain Network Centrality During Emotion Regulation

2020 ◽  
Vol 87 (9) ◽  
pp. S146
Author(s):  
Henk Cremers ◽  
Linda van Zutphen ◽  
Sascha Duken ◽  
Gregor Domes ◽  
Andreas Sprenger ◽  
...  
Keyword(s):  
Emotion Regulation ◽  
Borderline Personality Disorder ◽  
Personality Disorder ◽  
Brain Network ◽  
Borderline Personality ◽  
Network Centrality

scholarly journals Dyadic Emotion Regulation in Women with Borderline Personality Disorder

2021 ◽  
Author(s):  
Annemarie Miano ◽  
Sven Barnow ◽  
Stina Wagner ◽  
Stefan Roepke ◽  
Isabel Dziobek
Keyword(s):  
Emotion Regulation ◽  
Borderline Personality Disorder ◽  
Personality Disorder ◽  
Positive Emotions ◽  
Male Partner ◽  
Borderline Personality ◽  
Self Report ◽  
Negative Behaviors ◽  
Support Seeking ◽  
Threatening Situation

Abstract Background Emotion regulation (ER) and interpersonal dysfunction constitute key features of borderline personality disorder (BPD). Here, we tested if females with BPD show impairments in dyadic ER, that is in their support seeking and creation of closeness. We investigated if women with BPD might over-rely on their male partner by excessive support seeking and establishing of closeness, during conversations with personally and relationship-threatening topics. Methods Thirty couples in which the women were diagnosed with BPD and 34 healthy control (HC) couples were videotaped while discussing neutral, personally threatening, and relationship-threatening topics. Support seeking was rated by three independent raters, using a naïve observer method. The creation of closeness was rated using a continuous video-rating. Perceived emotions were assessed using self-report after each conversation. Results Women with BPD engaged in more support seeking than HC women, especially in more negative behaviors to elicit support, they created less closeness to their partner than HCs and reported a greater decline of positive emotions in both threatening conditions. Women with BPD displayed more fluctuations than controls between creating closeness and distance in the personally-threatening situation. They reported a larger increase in negative emotions after the relationship threatening conversation compared to female HC. Conclusions The present study indicates an increased demand of dyadic ER in BPD. Increased negative support seeking and less creation of closeness to the partner might reflect ineffective strategies to actually receive support from the partner.

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