In PSY/NEU 338, From Animal Learning to Changing People’s Minds, my group recently presented our capstone project for the course: we researched irrationality, trying to understand when humans make irrational decisions, how that is implemented in the brain, and if certain things might actually be incorrectly labeled as ‘irrational’. Our emotions are a leading example: although some call them irrational, in practice, they play a key role in fine-tuning our decision-making and reasoning abilities. When you’re happy, for example, everything might be going more positively than expected. Your mood is thus encouraging you to continue the behaviors that led to those rewards, since that positive trend might continue (for a neuroscientific discussion of this topic, see this paper).
To demonstrate this phenomenon first-hand, we had students in the class play what is known as the Ultimatum Game:
You are the proposer. You have been given $100. You are tasked with splitting your money with a stranger, the responder. If the responder accepts the split that you propose, you both keep the money after the game ends. If the responder does not accept, no one keeps the money.
The question: how much money do you decide to offer the responder?
After reading this, students had five seconds to provide their answer. They were then asked to report their mood. The question we wanted to answer was simple:
Is the amount of money people offered statistically different between those who reported “positive” versus “negative” moods?
In this post, I’ll explain some of the basic statistics I used to formally answer this question, bolding some key terms in the field along the way. In my next post, I’ll walk through the programming aspect for visualizing those statistics.
It’s that time of year again: everyone is spending endless amounts of time browsing and discussing the available spring courses with their friends, advisers, and mentors. The buildup is for good reason: it’s important to put together a balanced, enjoyable course schedule (for tips on how to go about doing that, check out this post).
I’ve personally had my eye on NEU 350, the neuroscience major requirement known for teaching data analysis techniques and lab procedures. Thus far in my Princeton career, I’ve learned a lot about theoretical methods within the discipline, but I’ve yet to actually apply those methods myself and work with real data. I wanted to take the class to learn these skills and broaden my understanding of what actual work within the neurosciences looks like.
However, I noticed under the “Prerequisites and Restrictions” header of the course on the registrar website that sophomores need permission from the Instructor to take the course. I found this odd considering that many sophomores are enrolled in NEU 314, a class that is typically taken by neuro majors the semester before NEU 350. The need for instructor permission felt intimidating to say the least, and in this post, I’ll share a few steps I took to learn more about NEU 350 and whether or not I should take it this spring.
As early as November of my freshman year, I remember hearing conversations around campus about summer plans. These conversations were not about the anticipation of vacation and relaxation, but rather the frantic and stressful search for the perfect summer opportunity to pad their resumes. It was safe to say that I was freaking out.
But this pressure motivated me to learn about my options, which ultimately allowed me to further explore my interests and participate in an incredibly rewarding research opportunity. After many meetings with my amazing academic advisers and career advisers at Career Services, I secured a position as a research assistant at a developmental neuroscience lab at UNC Chapel Hill.
This position consisted of nine consecutive weeks of unpaid, nine to five workdays, and the occasional shift on evenings and weekends. Sound draining? Yes, but I loved every second of it. Don’t get me wrong, it was a lot of work. But what was so enlightening about the experience was the fact that I actually enjoyed doing the work. I found something I was passionate about and I had the opportunity to engage with it every single day.
The first day was a blur—meeting everyone in the lab, getting familiar with the lab space, moving into my office (my own office!!!), and running around campus collecting my various parking permits and ID badges. After taking care of these logistical details, I hit the ground running.