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Our Research

The Embodied Emotion Laboratory is involved in numerous research projects related to emotional perception, embodied emotional experiences, and emotion regulation.  We uses several different methodologies including functional magnetic resonance imaging (fMRI), electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), machine learning, and computer-based experiments.  Please read below for descriptions of our team's research projects.

  • The Neuroscience of Emotion-Movement Interactions

 

Previous research by our research team has found that looking at emotional images leads to an increase in neural activity in areas of the spinal cord related to planning movements. The results of these studies suggest that the brain and spinal cord work together to help people plan out which movements will be necessary when people need to respond to emotional stimuli in the environment. Recently, we published a paper showing the time-course of emotion-movement interactions in the brain; this experiment used event-related potentials (ERPs).  Both lines of research—as well as new studies using functional near-infrared spectroscopy (fNIRS)—will continue over the next few years.

 

  • Empathy, Alexithymia, and the Brain

 

Empathy involves the ability to experience the emotional state of another individual.  In this research project, my collaborators and I have examined how two personality traits—alexithymia and sensory processing sensitivity—are related to different forms of empathy.  Individuals with alexithymia have difficulty identifying and describing their emotions; they also tend to focus on external stimuli rather than internal feelings.  Sensory processing sensitivity (SPS) reflects a tendency to be particularly attuned to one’s internal and external environment.  SPS can lead to positive experiences (e.g., a deep appreciation of the beauty of art) and/or negative experiences (e.g., being overwhelmed by noisy, crowded environments).  Our current research uses both fMRI and questionnaire-based research to examine how empathy, alexithymia, and SPS interact, both in the brain and in real-world behaviours.

 

  • The Influence of Emotion Regulation on Reading and Math Skills During Early School Years

 

Reading and math are fundamental skills that are critical for both academic success as well as everyday tasks such as running a household.  In the current research project, my colleagues and I will use behavioural and neuroimaging (event-related potentials and functional near-infrared spectroscopy) tasks to accomplish three goals: 1) to specify the mechanisms that develop to support reading and math development, 2) to identify the factors that predict successful development in these skills, 3) and to determine whether and how emotion-regulation impacts the development of reading and math.

 

  • Brain Assistive Tools for Investigating Failures of Emotional Regulation

 

Emotion regulation failures are common in the elderly, particularly in those experiencing symptoms of dementia.  This poses challenges for medical teams and care-givers.  In this project, we use portable EEG to attempt to identify patterns of brain activity that occur prior to emotional dysregulation.  Earlier studies in this line of research established that portable EEG data can be used to create machine-learning models that correctly classify emotion regulation successes and failures.  We have also compared the neural activity of younger and older adults during emotion regulation.  The next stage of this research will take us to the Misericordia Health Centre to assess the usefulness of our portable devices in a healthcare setting.

  • Using Machine Learning to Identify Patterns in Neuroimaging Data for Healthy and Clinical Populations

 

Machine learning is a rapidly developing area of computer science.  Using different machine-learning models, researchers can detect patterns in data that are not observable using traditional statistical analyses.  We are working with collaborators in the Department of Applied Computer Science to examine how machine can be applied to multiple EEG and fMRI data sets.  We have performed machine learning analyses on an open-source data set consisting of people who have different genetic susceptibilities to developing Alzheimer’s disease.  We have been able to predict whether someone has Alzheimer’s risk genes using both EEG and fMRI data.  We are now using similar techniques to investigate the effect of sleep on mental health as well as the relationship between alexithymia and empathy.

 

In addition to these more established lines of research, the Embodied Emotion Laboratory is also involved in a number of curiosity-driven projects (e.g., humor perception, politics and the brain, ASMR, yoga).  If we aren’t curious about the world, we aren’t scientists…

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515 Portage Avenue, Winnipeg, MB, Canada, R3B 2E9

s.smith (at) uwinnipeg.ca

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