DIBS News

Student Spotlight: Aurelio Falconi

November 27, 2017

Aurelio Falconi

Class of 2018

 Hometown: Albuquerque, NM

 Your current research project at Duke: I am currently working under Felipe de Brigard in the Imagination and Modal Cognition Lab. I work with Dr. Laura Niemi researching the effects of testimonial injustice which is defined as the deficit in credibility of a speaker due to prejudices held by the listener. This kind of repeated epistemic injustice has proven detrimental to the health of the speaker as it can produce clinical levels of stress in marginalized communities. We aim to find the neural correlates of this type of stress and compare it to chronic traumatic stress in order to better elucidate how it can truly affect the population at risk. This would offer new opportunities and more efficient approaches in therapeutic treatments.

Thoughts on neuroscience education: I may be biased, but I believe neuroscience is one of the most exciting fields of study to invest one's time in. Neuroscience is on an exponential rise in interest, and the number of new discoveries we continue to make about the brain will follow suit as well. Our passions, personalities, and quirks all come from deep inside our brains, and I enjoy learning the science behind what makes us tick. Thankfully, Duke has a wide array of neuroscience classes to choose from which has made it easy for me to further explore my interest with the brain and mind.

 What makes your brain "light up”? I love learning about how music interacts with the brain. Musical frisson, or the full-body chills you get when you listen to that perfect song, was always a fascinating phenomenon to me. What I think is even more interesting is that frisson is not always caused by the intense emotions you feel during a song. Rather, researchers seem to also think that people who try to predict musical progressions are more likely to experience chills when the music deviates from their expectation. This is a connection to how our brain is constantly trying to predict what is going to happen next in the real world, and how it reacts most to changes in what it expects.

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