I was interested in an ARIA project for many reasons. Primarily, this project allowed me to apply and expand my knowledge of neuroscience and computer science in an a unique experiential setting. I was tasked with understanding the research goals of our lab and implementing methods to reach those aims. Additionally, an ARIA project provided an opportunity to work full time and explore research as a future career or educational direction.
My project involved the recording and analysis of electrophysiological data in the anterodorsal nucleus of the thalamus and medial entorhinal cortex in the mouse brain. These areas are known to have navigational functions and my analysis aimed to identify directionally selective cells in these areas. In particular, I investigated the dynamics of a compass-like head direction system. Outside of the physical recording of data, a large portion of my time was spent writing code to identify features of cells that were identified as directionally selective. Partway through my internship, I had the opportunity to present my project to the entire lab which was a challenging yet rewarding experience. In the following weeks, I incorporated feedback from my supervisors and other lab members and adjust in a way that made my analysis more thorough and presentable. Throughout this process, I learned how to design and create scientific figures with my results using data analysis libraries such as Matplotlib.
One main objective of the project was to develop my coding skills through the creation of python scripts for data analysis. While interacting and recording data from the mice was an interesting experience, I found coding to be much more rewarding than expected. Starting from scratch and piecing together snippets of code, I exercised numerous problem solving techniques and implemented skills I have learned in classes. Beyond that, my patience and dedication was tested by errors that often took longer than expected to correct. Knowing that my work could produce results with real data motivated me through difficulties Overall, I learned from each step of the process and gained a sense of the challenges and rewards of data analysis coding.
Another challenge I encountered throughout my project was the transition from assignment-based courses to a work environment. For example, may of my coding tasks required strategies and skills I was forced to learn through experience instead of during lectures or tutorials. Working through difficult challenges taught me that there are multiple ways to arrive at the same result and sometimes I approached a problem one way and find myself failing and adjusting to adopt a new strategy.
While I faced many challenges on a day-to-day basis, one of the most significant was interpreting our findings. After collecting and analyzing data, it became clear to me that I could not fully interpret our results. To address this, I compiled and summarized a list of academic papers to further my understanding of relevant studies. My supervisors and I took time to discuss explanations and interpretations during meetings which were a valuable experience. This highlighted an important part of the research process which is an ongoing dialogue to evaluate and continually adjust goals and strategies.
My experience with ARIA also opened doors for my future in research at McGill and elsewhere. I would like to thank the Arts Undergraduate Society for funding my project and making such an amazing opportunity possible. With the award, I was able to focus my energy on learning as much as I could this summer and discovering how much I enjoyed working with others towards a better understanding of the world and how we perceive it.
