Our research aims to provide a neurobiological framework for the psychological processes of the experience of our own emotions and evaluation of the emotions of others, by leveraging our responses to affective uncertainty and ambiguity. Using multimodal neuroimaging tools that include task-based and resting state functional magnetic resonance imaging (fMRI) and diffusion magnetic resonance imaging (dMRI), our work examines the role of a corticolimbic circuitry that centers on the amygdala, nucleus accumbens (NAcc) and the prefrontal cortex (PFC) in such affective processes and their implications for mental health (Kim et al., 2011, Behavioural Brain Research).
In our lab, there are two major lines of research that explore affective processing from two viewpoints: universal mechanisms and individual differences. The former focuses on elucidating the fundamental psychological and neurobiological mechanisms of affective processing that is shared across individuals, whereas the latter examines how such mechanisms may manifest as systematic differences across individuals – providing a link to mood and anxiety disorders. Summarized below are some examples of research questions that the HumAN lab seeks to answer:
Decoding Emotional Ambiguity in the Facial Expressions of Others
Evaluating the emotional state of another person involves some degree of uncertainty. Interpreting emotionally ambiguous facial expressions of others is one such instance. Surprised faces are a particularly potent example in this respect because of their inherent ambiguity – these expressions can signal either positive (e.g., I got the job!) or negative (e.g., My wallet is not in my pocket!) outcomes. One source of information that we may use to disambiguate surprised faces is embedded within the facial features per se. Using a machine learning classifier, we identified that the facial features in the mouth were driving the affective valence (i.e., positivity-negativity) of surprised faces – information that human perceivers were unable to explicitly report – and demonstrated that these features were eliciting the activity of the amygdala (Kim et al., 2017, Journal of Neuroscience).
What's next: With the global pandemic, we've seen two major changes to everyday social interactions: face masks and social distancing, both of which interferes with our ability to read emotions from facial expressions of others. Face masks in particular obstructs important facial features, effectively increasing emotional ambiguity. This offers an intriguing question: do we become more sensitive to the facial features in the unobstructed areas, which we did not need to utilize before? We seek to answer this question through laboratory experiments.
Integrating Affective Information from Multiple Sources in the Brain
When surprised faces are contextualized by a verbal description of a hypothetical scenario that could be either positive or negative, amygdala activity represented the valence values that were computed by considering a given context when judging a face on a trial-by-trial basis. Interestingly, only when a surprised face was viewed in a positive context, amygdala activity was functionally connected with the NAcc – a part of the ventral striatum best known for processing reward or positivity (Kim et al., 2020, Cognitive, Affective, and Behavioral Neuroscience). As no such interaction in brain activity was found when surprised faces were paired with a negative context, this served as evidence that supports the idea that extra neural computation is required when trying to view an emotionally ambiguous stimulus in a positive light.
What's next: In our next iteration of this experiment, our goal is to implement a more organic approach on providing contextual cues, moving beyond simple presentation of sentence-face pairs. This include using dynamic facial expression stimuli and allowing free-form responses by the perceivers. We also plan on leveraging the observed interindividual variability during such affective information integration processes, which is described in the next section.
Individual Differences in the Tendency to Rely on Contextual Information versus Facial Features
When a surprised face is presented with an accompanying social context – as is always the case in real world situations – perceivers will have varying degrees of sensitivity towards top-down (i.e., contextual cues) and bottom-up (i.e., facial features) information, when making a decision about how positive or negative the face seems to be. Adapting a computational approach, a behavioral model that considers the individual differences in the sensitivity to these contexts and features was constructed on a subject-by-subject basis to explain how social information from multiple sources are integrated. This measure of sensitivity showed adequate reliability (ICC > 0.8) and trait-like psychometric properties, and was subsequently found to be associated with the strength of amygdala-PFC connectivity (Kim & Shin., in preparation). We are investigating how the individual differences in sensitivity may be represented as distributed patterns of brain activity.
What's next: We aim to test whether this "context sensitivity" index is indeed capturing useful variance across individuals by assessing its link with dimensional measures of mood and anxiety-related constructs. Ultimately, our goal is to determine whether context sensitivity holds predictive utility for mood and anxiety disorders. Another intriguing question pertains to potential cultural effects, as individualistic vs. collectivistic societies substantially differ in how its members process contextual information.
The Nature of the Association Between Corticolimbic Circuitry and Anxiety
Neurobiological research on anxiety, or negative affect in general, has consistently implicated the amygdala and the PFC, leading to a hypothesis that an imbalance of the corticolimbic circuitry – reflecting an imbalance of top-down and bottom-up flow – may be key to understanding the generation and regulation of negative emotions (Kim et al., 2011, Cerebral Cortex). Using dMRI in conjunction with fMRI, we observed that the structural integrity of white matter pathways between the amygdala and the ventral PFC was weaker in trait-anxious individuals (Kim & Whalen, 2009, Journal of Neuroscience). We then found that this association was moderated by sex, such that this brain-anxiety correlation was substantially stronger in women compared to men (Kim et al., 2016, Frontiers in Systems Neuroscience). Both of these effects were replicated in a subsequent study, where we demonstrated that a functional polymorphism in the human BDNF gene (rs6265) further influenced the brain-anxiety association (Kim et al., 2017, Scientific Reports).
What's next: We are working on identifying other potential modulating factors, as it will allow us to better understand the neural underpinnings of trait anxiety, and inform clinical research on anxiety disorders.
Role of the Striatum in Emotional Responses to Uncertainty
In a thorough inspection of the structural characteristics of gray matter and white matter tissues across the whole brain, we found that increased volume of the striatum predicted normative variation in the intolerance of uncertainty – a psychological construct related to anxiety that focuses on how one responds to the uncertainty and ambiguity regarding the potential occurrence of future threat (Kim et al., 2017, Emotion). The scientific merit of this work is that it clearly delineated the impact of normative versus pathological anxiety (those characterized by exaggerated intolerance of uncertainty: e.g., obsessive-compulsive disorder, generalized anxiety disorder) on the volumetric properties of the striatum, which is crucial in understanding the pathophysiology of anxiety disorders.
What's next: We aim to expand the structural findings by elucidating the functional role of the striatum in processing affective uncertainty, in conjunction with the amygdala and the PFC via a network-based approach.