Self-report vs psychophysiological measures of emotion and emotion regulation

Data for https://github.com/daisyburr/DoYouKnowHowYouRegulate

Anxiety, not regulation tendency, predicts how individuals regulate in the laboratory: An exploratory comparison of self-report and psychophysiology

Anxiety influences how individuals experience and regulate emotions in a variety of ways. For example, individuals with lower anxiety tend to cognitively reframe (reappraise) negative emotion and those with higher anxiety tend to suppress negative emotion. Research has also investigated these individual differences with psychophysiology. These lines of research assume coherence between how individuals regulate outside the laboratory, typically measured with self-report, and how they regulate during an experiment. Indeed, performance during experiments is interpreted as an indication of future behavior outside the laboratory, yet this relationship is seldom directly explored. To address this gap, we computed psychophysiological profiles of uninstructed (natural) regulation in the laboratory and to conduct an exploratory analysis of the coherence between these profiles and a) self-reported anxiety and b) self-reported regulation tendency. Participants viewed negative images and were instructed to reappraise, suppress or naturally engage. Electrodermal and facial electromyography signals were recorded to compute a multivariate psychophysiological profile of regulation. Participants with lower anxiety exhibited similar profiles when naturally regulating and following instructions to reappraise, suggesting they naturally reappraised more. Participants with higher anxiety exhibited similar profiles when naturally regulating and following instructions to suppress, suggesting they naturally suppressed more. However, there was no association between self-reported reappraisal or suppression tendency and psychophysiology. These exploratory results indicate that anxiety, but not regulation tendency, predicts how individuals regulate emotion in the laboratory. These findings suggest that how individuals report regulating in the real world does not map on to how they regulate in the laboratory. Taken together, this underscores the importance of developing emotion-regulation interventions and paradigms that more closely align to and predict real-world outcomes

Anxiety, not regulation tendency, predicts how individuals regulate in the laboratory: An exploratory comparison of self-report and psychophysiology.

Anxiety influences how individuals experience and regulate emotions in a variety of ways. For example, individuals with lower anxiety tend to cognitively reframe (reappraise) negative emotion and those with higher anxiety tend to suppress negative emotion. Research has also investigated these individual differences with psychophysiology. These lines of research assume coherence between how individuals regulate outside the laboratory, typically measured with self-report, and how they regulate during an experiment. Indeed, performance during experiments is interpreted as an indication of future behavior outside the laboratory, yet this relationship is seldom directly explored. To address this gap, we computed psychophysiological profiles of uninstructed (natural) regulation in the laboratory and explored the coherence between these profiles and a) self-reported anxiety and b) self-reported regulation tendency. Participants viewed negative images and were instructed to reappraise, suppress or naturally engage. Electrodermal and facial electromyography signals were recorded to compute a multivariate psychophysiological profile of regulation. Participants with lower anxiety exhibited similar profiles when naturally regulating and following instructions to reappraise, suggesting they naturally reappraised more. Participants with higher anxiety exhibited similar profiles when naturally regulating and following instructions to suppress, suggesting they naturally suppressed more. However, there was no association between self-reported reappraisal or suppression tendency and psychophysiology. These exploratory results indicate that anxiety, but not regulation tendency, predicts how individuals regulate emotion in the laboratory. These findings suggest that how individuals report regulating in the real world does not map on to how they regulate in the laboratory. Taken together, this underscores the importance of developing emotion-regulation interventions and paradigms that more closely align to and predict real-world outcomes

Emotion dynamics across adulthood in everyday life: Older adults are more emotionally stable and better at regulating desires

Older adults report experiencing improved emotional health, such as more intense positive affect and less intense negative affect. However, there are mixed findings on whether older adults are better at regulating emotion—a hallmark feature of emotional health—and most research is based on laboratory studies that may not capture how people regulate their emotions in everyday life. We used experience sampling to examine how multiple measures of emotional health, including mean affect, dynamic fluctuations between affective states and the ability to resist desires—a common form of emotion regulation—differ in daily life across adulthood. Participants (N = 122, ages 20-80) reported how they were feeling and responding to desire temptations for 10 days. Older adults experienced more intense positive affect, less intense negative affect and were more emotionally stable, even after controlling for individual differences in global life satisfaction. Older adults were more successful at regulating desires, even though they experienced more intense desires than younger adults. In addition, adults in general experiencing more intense affect were less successful at resisting desires. These results demonstrate how emotional experience is related to more successful desire regulation in everyday life and provide unique evidence that emotional health and regulation improve with age

Identifying the representational structure of affect using fMRI

The events we experience day to day can be described in terms of their affective quality: some are rewarding, others are upsetting, and still others are inconsequential. These natural distinctions reflect an underlying representational structure used to classify the affective quality of events. In affective psychology, many experiments model this representational structure with two dimensions, using either the dimensions of valence and arousal, or alternatively, the dimensions of positivity and negativity. Using an fMRI dataset, we show that these affective dimensions are not strictly linear combinations each other, and show that it is critical that all four dimensions be used to examined the data. Our findings include (1) a gradient representation of valence anatomically organized along the fusiform gyrus, and (2) distinct subregions within bilateral amygdala tracking arousal versus negativity. Importantly, these patterns would have remained concealed had either of the prevailing 2-dimensional approaches been adopted a priori

Identifying the representational structure of affect using fMRI

The events we experience can be described in terms of their affective quality: some experiences are rewarding, others are upsetting, and still others are inconsequential. These natural distinctions reflect an underlying representational structure that we use to classify the affective quality of everyday events. In affective psychology, many experiments model this representational structure with two dimensions. Either there is a choice to use the dimensions of valence and arousal, or alternatively, to use the dimensions of positivity and negativity. Some theories even claim that this choice does not matter, and that one set of dimensions is simply a linear rotation of the other. Using an fMRI dataset, we verify that these affective dimensions are not strictly linear combinations each other, and because of this lack of linear redundancy, it is critical all four dimensions be used to examined the data. Our findings include (1) a gradient representation of valence that is anatomically organized along the fusiform gyrus, and (2) distinct subregions within bilateral amygdala that track arousal versus negativity. Critically, these patterns would have remained concealed had either of the prevailing 2-dimensional approaches been adopted a priori, demonstrating the utility of the new synthesized approach

Functional connectivity predicts the dispositional use of expressive suppression but not cognitive reappraisal

Previous research has identified specific brain regions associated with regulating emotion using common strategies such as expressive suppression and cognitive reappraisal. However, most research focuses on a priori regions and directs participants how to regulate, which may not reflect how people naturally regulate outside the laboratory. Here, we used a data-driven approach to investigate how individual differences in distributed intrinsic functional brain connectivity predict emotion regulation tendency. Specifically, we used connectome-based predictive modeling to extract functional connections in the brain significantly related to the dispositional use of suppression and reappraisal. These edges were then used in a predictive model and cross-validated in novel participants to identify a neural signature that reflects individual differences in the tendency to suppress and reappraise emotion. We found a significant neural signature for the dispositional use of suppression, but not reappraisal. Within this whole-brain signature, the intrinsic connectivity of the default mode network was most informative of suppression tendency. In addition, the predictive performance of this model was significant in males, but not females. These findings help inform how whole-brain networks of functional connectivity characterize how people tend to regulate emotion outside the laboratory