As a 3rd year PhD candidate in Biomedical Engineering at Boston University, I’m broadly interested in using my quantitative skills to investigate human attention, learning, neuropsychiatric disorders, and hard-to-quantify behaviors in neuroscience and psychoacoustics. I study these interests in the BU Auditory Neuroscience Lab under the mentorship of Dr. Barbara Shinn-Cunningham, Ph.D. Below are summaries of my proposed work, but of course I haven’t divulged everything so feel free to contact me to ask.

Current work for non-experts

My current project is a study of various forms of selective attention in young adults with Attention Deficit Hyperactivity Disorder (I’ll explain below!). In our world of innumerable distractions, my scientific goals are to better understand ADHD as a brain disorder, understand the influence of stimulant medications on the brain’s activity, and identify a relationship between our inattentiveness and our brain’s sensory (visual and auditory) processing. These basic science aims are important for neuroscience and pharmacology alike, as we aim to understand how our cognitive abilities influence our behaviors. On a clinical note, I also aim to design better criteria for diagnosis of ADHD using quantitative measures from neuro-imaging.

So how will I do this? By analyzing people’s performance on selective attention tasks. Auditory selective attention is our ability to pay attention to specific sounds within a complex mixture of sounds – for instance, a single conversation at a loud cocktail party. Visual selective attention is similar: it’s how we can use our eye movements or peripheral vision to single out a certain sight — for instance, finding a yellow dress in a closet of blacks, greys, and blues. To study these abilities, I have designed rich and complex selective attention tasks that young adults with and without ADHD will perform in our lab. Simultaneously, I will record electroencephalography (EEG), a measure of brain activity from the scalp similar to an EKG for the heart. From the EEG data, I will find neural correlates (measures from the brain that correlate to a brain process) of selective attention and then ask how they are different between ADHD and neuro-typical (non-ADHD) adults.


Current work for neuroscientists: 

Using 64-channel EEG, I will identify neural correlates of selective attention from several measures including but not limited to:

  • event-related potential (ERP) N1 component modulations
  • alpha band oscillatory activity (coherence and power)
  • theta and beta band power ratios
  • task performance

I plan to use source localization to identify ROIs with altered activity and then use machine learning techniques to classify subjects as ADHD or neurotypical. I also aim to develop a descriptive model of the interactions between pre-frontal, parietal, and occipital channels and sources. This work is underway. If you have more questions, please contact me directly.

Previous posters:

Australia Science of Learning 2017
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Quantitative Biology and Physiology Fellowship Symposium, 2016
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Society for Neuroscience, 2015
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Biomedical Engineering Society (BMES), 2012
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I like being able to laugh at myself, so here’s an incomplete poster from my first research position. I was 16 or 17 years old, so cut me a break…
IMSA Student Inquiry and Research Symposium, 2009
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Coming soon:
Society for Neuroscience 2017