The Experts below are selected from a list of 45 Experts worldwide ranked by ideXlab platform
Peter Kuppens - One of the best experts on this subject based on the ideXlab platform.
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assessing temporal Emotion dynamics using Networks
Assessment, 2016Co-Authors: Laura F Bringmann, Francis Tuerlinckx, Nathalie Vissers, Eva Ceulemans, Denny Borsboom, Wolf Vanpaemel, Peter KuppensAbstract:Multivariate psychological processes have recently been studied, visualized, and analyzed as Networks. In this Network approach, psychological constructs are represented as complex systems of interacting components. In addition to insightful visualization of dynamics, a Network perspective leads to a new way of thinking about the nature of psychological phenomena by offering new tools for studying dynamical processes in psychology. In this article, we explain the rationale of the Network approach, the associated methods and visualization, and illustrate it using an empirical example focusing on the relation between the daily fluctuations of Emotions and neuroticism. The results suggest that individuals with high levels of neuroticism had a denser Emotion Network compared with their less neurotic peers. This effect is especially pronounced for the negative Emotion Network, which is in line with previous studies that found a denser Network in depressed subjects than in healthy subjects. In sum, we show how the Network approach may offer new tools for studying dynamical processes in psychology.
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Emotion Network density in major depressive disorder
Clinical psychological science, 2015Co-Authors: Katharina Kircanski, Renee J Thompson, Laura F Bringmann, Francis Tuerlinckx, Merijn Mestdagh, Jutta Mata, Susanne M Jaeggi, Martin Buschkuehl, John Jonides, Peter KuppensAbstract:Major depressive disorder (MDD) is a prevalent disorder involving disturbances in mood. There is still much to understand regarding precisely how Emotions are disrupted in individuals with MDD. In this study, we used a Network approach to examine the Emotional disturbances underlying MDD. We hypothesized that compared with healthy control individuals, individuals diagnosed with MDD would be characterized by a denser Emotion Network, thereby indicating that their Emotion system is more resistant to change. Indeed, results from a 7-day experience sampling study revealed that individuals with MDD had a denser overall Emotion Network than did healthy control individuals. Moreover, this difference was driven primarily by a denser negative, but not positive, Network in MDD participants. These findings suggest that the disruption in Emotions that characterizes depressed individuals stems from a negative Emotion system that is resistant to change.
Laura F Bringmann - One of the best experts on this subject based on the ideXlab platform.
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assessing temporal Emotion dynamics using Networks
Assessment, 2016Co-Authors: Laura F Bringmann, Francis Tuerlinckx, Nathalie Vissers, Eva Ceulemans, Denny Borsboom, Wolf Vanpaemel, Peter KuppensAbstract:Multivariate psychological processes have recently been studied, visualized, and analyzed as Networks. In this Network approach, psychological constructs are represented as complex systems of interacting components. In addition to insightful visualization of dynamics, a Network perspective leads to a new way of thinking about the nature of psychological phenomena by offering new tools for studying dynamical processes in psychology. In this article, we explain the rationale of the Network approach, the associated methods and visualization, and illustrate it using an empirical example focusing on the relation between the daily fluctuations of Emotions and neuroticism. The results suggest that individuals with high levels of neuroticism had a denser Emotion Network compared with their less neurotic peers. This effect is especially pronounced for the negative Emotion Network, which is in line with previous studies that found a denser Network in depressed subjects than in healthy subjects. In sum, we show how the Network approach may offer new tools for studying dynamical processes in psychology.
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Emotion Network density in major depressive disorder
Clinical psychological science, 2015Co-Authors: Katharina Kircanski, Renee J Thompson, Laura F Bringmann, Francis Tuerlinckx, Merijn Mestdagh, Jutta Mata, Susanne M Jaeggi, Martin Buschkuehl, John Jonides, Peter KuppensAbstract:Major depressive disorder (MDD) is a prevalent disorder involving disturbances in mood. There is still much to understand regarding precisely how Emotions are disrupted in individuals with MDD. In this study, we used a Network approach to examine the Emotional disturbances underlying MDD. We hypothesized that compared with healthy control individuals, individuals diagnosed with MDD would be characterized by a denser Emotion Network, thereby indicating that their Emotion system is more resistant to change. Indeed, results from a 7-day experience sampling study revealed that individuals with MDD had a denser overall Emotion Network than did healthy control individuals. Moreover, this difference was driven primarily by a denser negative, but not positive, Network in MDD participants. These findings suggest that the disruption in Emotions that characterizes depressed individuals stems from a negative Emotion system that is resistant to change.
Francis Tuerlinckx - One of the best experts on this subject based on the ideXlab platform.
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assessing temporal Emotion dynamics using Networks
Assessment, 2016Co-Authors: Laura F Bringmann, Francis Tuerlinckx, Nathalie Vissers, Eva Ceulemans, Denny Borsboom, Wolf Vanpaemel, Peter KuppensAbstract:Multivariate psychological processes have recently been studied, visualized, and analyzed as Networks. In this Network approach, psychological constructs are represented as complex systems of interacting components. In addition to insightful visualization of dynamics, a Network perspective leads to a new way of thinking about the nature of psychological phenomena by offering new tools for studying dynamical processes in psychology. In this article, we explain the rationale of the Network approach, the associated methods and visualization, and illustrate it using an empirical example focusing on the relation between the daily fluctuations of Emotions and neuroticism. The results suggest that individuals with high levels of neuroticism had a denser Emotion Network compared with their less neurotic peers. This effect is especially pronounced for the negative Emotion Network, which is in line with previous studies that found a denser Network in depressed subjects than in healthy subjects. In sum, we show how the Network approach may offer new tools for studying dynamical processes in psychology.
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Emotion Network density in major depressive disorder
Clinical psychological science, 2015Co-Authors: Katharina Kircanski, Renee J Thompson, Laura F Bringmann, Francis Tuerlinckx, Merijn Mestdagh, Jutta Mata, Susanne M Jaeggi, Martin Buschkuehl, John Jonides, Peter KuppensAbstract:Major depressive disorder (MDD) is a prevalent disorder involving disturbances in mood. There is still much to understand regarding precisely how Emotions are disrupted in individuals with MDD. In this study, we used a Network approach to examine the Emotional disturbances underlying MDD. We hypothesized that compared with healthy control individuals, individuals diagnosed with MDD would be characterized by a denser Emotion Network, thereby indicating that their Emotion system is more resistant to change. Indeed, results from a 7-day experience sampling study revealed that individuals with MDD had a denser overall Emotion Network than did healthy control individuals. Moreover, this difference was driven primarily by a denser negative, but not positive, Network in MDD participants. These findings suggest that the disruption in Emotions that characterizes depressed individuals stems from a negative Emotion system that is resistant to change.
Katharina Kircanski - One of the best experts on this subject based on the ideXlab platform.
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Emotion Network density in major depressive disorder
Clinical psychological science, 2015Co-Authors: Katharina Kircanski, Renee J Thompson, Laura F Bringmann, Francis Tuerlinckx, Merijn Mestdagh, Jutta Mata, Susanne M Jaeggi, Martin Buschkuehl, John Jonides, Peter KuppensAbstract:Major depressive disorder (MDD) is a prevalent disorder involving disturbances in mood. There is still much to understand regarding precisely how Emotions are disrupted in individuals with MDD. In this study, we used a Network approach to examine the Emotional disturbances underlying MDD. We hypothesized that compared with healthy control individuals, individuals diagnosed with MDD would be characterized by a denser Emotion Network, thereby indicating that their Emotion system is more resistant to change. Indeed, results from a 7-day experience sampling study revealed that individuals with MDD had a denser overall Emotion Network than did healthy control individuals. Moreover, this difference was driven primarily by a denser negative, but not positive, Network in MDD participants. These findings suggest that the disruption in Emotions that characterizes depressed individuals stems from a negative Emotion system that is resistant to change.
Robert C Welsh - One of the best experts on this subject based on the ideXlab platform.
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integrated cross Network connectivity of amygdala insula and subgenual cingulate associated with facial Emotion perception in healthy controls and remitted major depressive disorder
Cognitive Affective & Behavioral Neuroscience, 2017Co-Authors: Lisanne M Jenkins, Jonathan P Stange, Alyssa Barba, Sophie R Deldonno, Leah R Kling, Emily M Briceno, Sara L Weisenbach, Luan K Phan, Stewart A Shankman, Robert C WelshAbstract:Emotion perception deficits could be due to disrupted connectivity of key nodes in the salience and Emotion Network (SEN), including the amygdala, subgenual anterior cingulate cortex (sgACC), and insula. We examined SEN resting-state (rs-)fMRI connectivity in rMDD in relation to Facial Emotion Perception Test (FEPT) performance. Fifty-two medication-free people ages 18 to 23 years participated. Twenty-seven had major depressive disorder (MDD) in remission (rMDD, 10 males), as MDD is associated with Emotion perception deficits and alterations in rsfMRI. Twenty-five healthy controls (10 males) also participated. Participants completed the FEPT during fMRI, in addition to an 8-minute eyes-open resting-state scan. Seed regions of interest were defined in the amygdala, anterior insula and sgACC. Multiple regression analyses co-varied diagnostic group, sex and movement parameters. Emotion perception accuracy was positively associated with connectivity between amygdala seeds and regions primarily in the SEN and cognitive control Network (CCN), and also the default mode Network (DMN). Accuracy was also positively associated with connectivity between the sgACC seeds and other SEN regions, and the DMN, particularly for the right sgACC. Connectivity negatively associated with Emotion perception was mostly with regions outside of these three Networks, other than the left insula and part of the DMN. This study is the first to our knowledge to demonstrate relationships between facial Emotion processing and resting-state connectivity with SEN nodes and between SEN nodes and regions located within other neural Networks.