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12:30pm, Corner Building, 1400 University Avenue and Zoom
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12:30pm, Academic Commons
12:30pm, Zoom and CDW 2677
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12:30pm, Mill 123 and Zoom
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12:00-1:00pm, Zoom, Millmont Cottage Conference Room
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Social lunch -- Dr. Amit Goldenberg (Harvard Business School).Social lunch -- Dr. Amit Goldenberg (Harvard Business School).
12:30pm, Zoom, CDW 2539
People respond emotionally to events that are related to their groups, even when these events do not have any direct effect on their lives. These emotions are often shared through social interactions, and may play a key role in fueling and perpetuating social movements and intergroup conflicts. Using a multi-method approach, my research focuses on identifying emotional dynamics that lead to increased emotional intensity in groups. I plan to focus on three aspects in emotional dynamics that contribute to an increase in emotional intensity: Social tie selection, perception of others’ emotions and emotional influence.
12:30pm, Zoom and 138 Millmont
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12:30pm, Corner Building, 1400 University Avenue and Zoom
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12:30pm, Academic Commons
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12:30pm, Academic Commons
12:30pm, Mill 123 and Zoom
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12:00-1:00pm, Zoom, Millmont Cottage Conference Room
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12:30pm, Zoom and 138 Millmont
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12:30pm, Academic Commons
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12:30pm, Academic Commons
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12:30pm, Academic Commons
Quantitative lunch -- Amalia Skyberg.Quantitative lunch -- Amalia Skyberg.
12:30pm, Mill 123 and Zoom
Emotion regulation is an essential component of socio-emotional cognition and behavior. Functional connectivity between the amygdala and the prefrontal cortex, specifically the medial prefrontal cortex (mPFC), has been identified as a neural substrate of emotion regulation that undergoes changes throughout development. Amygdala-mPFC connectivity has been well studied in adolescents and adults, with a mature profile typically emerging at 10 years of age. Maternal bonding in childhood has been shown to buffer amygdala reactivity and to influence the trajectory of amygdala-mPFC coupling, which in turn may impact socio-emotional dysfunction later in life. Additionally, a relevant biomarker of social behavior and maternal bonding is oxytocin. DNA methylation of the oxytocin receptor gene (OXTRm) impacts expression of the receptor that allows an individual to make use of oxytocin, which has important social and emotional ramifications. Early life parental care influences the methylation status of OXTR in animal models and humans, and higher OXTRm is associated with lower amygdala-PFC functional connectivity in adults. Using a neuroimaging-epigenetic approach, we investigated OXTRm as a biological marker of functional connectivity maturation in middle childhood. We find that higher levels of OXTRm are associated with a more adult-like functional connectivity profile, irrespective of chronological age. We also find that lower OXTRm blunts the association between amygdala-mPFC connectivity and future internalizing behaviors in early adolescence. These findings implicate OXTRm as a biological marker at the interface of the social environment and amygdala-mPFC coupling in emotional and behavioral regulation. Ultimately, identification of neurobiological markers may lead to earlier detection of children at risk for socio-emotional dysfunction.
12:30pm, Mill 123 and Zoom
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12:00-1:00pm, Zoom, Millmont Cottage Conference Room
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12:30pm, Zoom and 138 Millmont
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12:30pm, Academic Commons
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Quantitative lunch -- Elena Martynova.Quantitative lunch -- Elena Martynova.
12:30pm, Mill 123 and Zoom
Many psychological phenomena may be understood as nonlinear dynamical systems, which may have sensitive dependence on initial conditions. These systems increase in uncertainty as predictions are forecast further into the future. Few methods exist for predicting nonlinear time series. HAVOK (Hankel Alternative View of Koopman; Brunton et al., 2017) analysis is an exception. HAVOK was designed to globally linearize and model nonlinear and chaotic systems by decomposing nonlinear systems into intermittently forced linear systems. A forcing parameter allows HAVOK to demarcate regions where a time series is approximately linear from those that are nonlinear. Obtaining linear representations for strongly nonlinear and chaotic systems could revolutionize the prediction and control of these systems. HAVOK is a robust modeling method that can model noisy Likert-type data with missingness, making it a powerful tool for the prediction and control of psychological processes.
HAVOK is exceptionally good at modeling dynamic phenomena across different fields when the right hyperparameters are found. Two years ago, we introduced the havok R package (Moulder, Martynova & Boker, 2020), which allows estimation of HAVOK models for any time series given user selected hyperparameters. However, determining a set of hyperparameters that will produce a well-fitting model might be challenging as the relationship between hyperparameters does not follow a consistently predictable pattern. Unlike havok(), parallel HAVOK (phavok) is a parallelized optimization routine for HAVOK that optimizes hyperparameter/model selection and consistently yields well-fitting models (given at least one exists). phavok() runs multiple models simultaneously across many sets of hyperparameters and generates model fit surfaces in a reasonable amount of time. In this presentation, I will demonstrate some results from both theoretical and applied examples, discuss phavok()’s implementation, discuss differences between havok() and phavok(), and our plans on the havok package’s further development and upcoming CRAN release.
12:30pm, Mill 123 and Zoom
12:30pm, Academic Commons
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12:00-1:00pm, Zoom, Millmont Cottage Conference Room
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Social lunch -- Dr. Richard Lopez (University of Michigan).Social lunch -- Dr. Richard Lopez (University of Michigan).
12:30pm, Zoom, CDW 2539
Previous theorizing suggests that self-regulatory strategies may be variably effective, but their efficacy in real world settings, as well as the role of person-and situation-level moderating factors, is not well known. In this talk, I will discuss a series of experience sampling and daily diary studies that assessed or trained up people’s self-regulatory abilities in the eating and smoking domains via a range of strategies, including situation selection/modification, cognitive reappraisal, distraction, and others. Across studies, no one strategy appeared to be a magic bullet when it comes to successful self-regulation, but the findings pave the way for future work to tease out the boundary conditions of strategy efficacy and establish the ecological validity of various models of self-regulation. I will conclude the talk by briefly discussing an exciting new line of research in my lab that will examine people’s experiences of self and identity on social media platforms and ways to regulate social media use to promote mental health and wellbeing.
2021-22 Department of Psychology Colloquium Series - Jay van Bavel (New York University). Zoom.2021-22 Department of Psychology Colloquium Series - Jay van Bavel (New York University). Zoom.
2:00pm (Zoom)
Jay van Bavel
Associate Professor of Psychology and Neural Science,
New York University
Director of the NYU Social Identity & Morality Lab.
Author of “The Power of Us Book.”
“For Better or Worse:
The Role of Social Identity in the Pandemic”
We are in the midst of one of the greatest global health crises in the past century. To mitigate catastrophe, the major public health response has required massive collective behavior change—especially at the national level. In this talk, I will present several recent studies on the role of social identity in the coronavirus pandemic. These studies will draw on the movement of millions of cell phones tracking human mobility and vaccination records in the US as well as an international sample of health intentions in 67 countries. This work suggests that social identity can both facilitate and impair collective action and clarifies how social identity might be leveraged effectively for global public health.
Tuesday, February 28, 2022
2:00 – 3:00pm
Zoom
12:30pm, Zoom and 138 Millmont
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