How does the brain represent, process, and regulate pain and affective experiences? The goal of the affective neuroscience team is to answer the question to better understand pain and emotions, thereby promoting the physical and psychological  well-being of people who suffer from pain and emotional distress. Specific aims include 1) understanding the brain mechanisms of pain and emotion dynamics (mechanisms), 2) developing integrated brain models of human affective experiences and clinical outcomes (biomarkers), 3) translating basic and computational neuroscience findings into clinical applications (translation), and 4) building life- and neuroscience-inspired artificial intelligence (AI) to better understand pain, affect, and human intelligence. 

 

(1) Pain and Emotion (PI: Choong-Wan Woo)

To achieve the specific aims, our team pursues systems-level, computational, and precision neuroscience research. First, now we know that pain and emotions involve distributed brain networks and have degenerate neural mechanisms—in other words, multiple brain systems and pathways exist for pain and emotions. Thus, to understand how the brain generates and regulates pain and affective experiences, we need to investigate the systems-level dynamics of the brain processes. For this, we use functional Magnetic Resonance Imaging (fMRI; including 3T and 7T MRI) as our main research tool. In addition, we use psychophysiology measures (skin conductance, pupillometry, electrocardiogram, respiration) and other behavioral measures such as facial expression, eye movement, etc. In addition, to develop integrative models with these multimodal data, we use data science techniques (e.g., machine learning and dimensionality reduction, etc.).  

Second, as Alan Turing—a father of modern artificial intelligence—suggested in his classical 1948 paper, “Intelligent Machinery,” a pleasure-pain system is a core computational component of natural and biological intelligence. Thus, we need to develop computational theories and models of relevant brain processes and behaviors for a deep understanding of pain and pleasure. We are particularly interested in the hierarchical models of perception and motivation for pain and emotions to contribute to neuroscience and artificial intelligence by integrating ideas from both fields. Lastly, the degenerate neural systems of pain and emotions suggest that different individuals would rely on different brain systems. Even within an individual, pain and emotion processing in the brain could be different every moment and across contexts. For this reason, we need to take personalized approaches to the study of pain and emotions and investigate the individual variability of the brain processes to develop clinically useful models and tools.

 

SELECTED PUBLICATIONS

1. Functional brain reconfiguration during sustained pain, Lee J.-J. et al. (2022), eLife, 11, e74463

2. When self comes to a wandering mind: Brain representations and dynamics of self-generated concepts in spontaneous thought, Kim B. et al. (2022), Sci Adv, 8, eabn8616

3. Individual variability in brain representations of pain, Kohoutová L. et al. (2022), Nat Neurosci, 25, 749–759

4. A neuroimaging biomarker for sustained experimental and clinical pain, Lee J.-J. et al. (2021), Nat Med, 27, 174–182

5. Toward a unified framework for interpreting machine-learning models in neuroimaging, Kohoutová L. et al. (2020), Nat Protoc, 15, 1399–1435