Author Archives: Amelia Cangialosi

After the conclusion of the poster presentation for BSURF, I decided to reread my very first blog about my expectations of the summer. These past 8 weeks have flown by, yet the Amelia writing the first blog seems so different. She was just at the beginning of her journey to being a researcher, with so much ahead of her. 

I am truly amazed by how much I have learned throughout this program. I started out with very little programming skills and now that we’re the end of BSURF, I am comfortable with coding for the whole work day, and I was able to complete my goals for my project! I must admit, there were many times where I was overwhelmed by all of the troubleshooting and debugging I had to work through, as well as maneuvering my way through a new language, Python. Thankfully, I was able to push through, majorly thanks to the help of my amazing mentors Anne and Liz, and my fellow lab mate Chris. Overall, I was pleasantly surprised by how welcoming everyone was at the Pearson Lab. It made my summer research experience even more enjoyable. I’d also like to give a huge thanks to John for giving me the opportunity to join the Pearson Lab for the summer.

I could go on and on about how rewarding this experience was, but before I wrap up this final blog, I would like to thank everyone who is a part of BSURF. Without Dr. Grunwald, Dr. Harrell, and Austin, this experience would not be nearly as great as it has been. I always looked forward to your smiling faces in the mornings and Dr. Grunwald’s jokes throughout the day. The BSURF excursions were some of my favorite memories of the summer – canoeing, dinner at Dr. G’s house, the Lemur Center, the art gallery crawl, just to name a few. Last but not least, I really enjoyed the community of bsurfers and I’m lucky to say that I made some amazing new friends along the way. I wish you all the best of luck with your future research endeavors! 

All of the faculty seminars have been super insightful and Dr. Emily Bernhardt’s talk particularly stood out to me. She is an ecologist at Duke who studies how energy and elements move, specifically focusing on environmental issues that people care about. Ever since she was a kid, she loved being outside, and she pursued a career doing just that.

Initially, I was a bit surprised that her talk was one of my favorites because her work as an ecologist is pretty different from the computational work I’ve been doing in lab. Maybe it’s the shared love for National Parks that drew me in, maybe it’s the amazing outlook she has for life and your career. 

Here are 5 pieces of advice from Dr. Bernhardt that I’d like to share. She had many more than 5 pieces of advice, but these really resonated with me.

1. If you enjoy STEM in any capacity, go for it! No one should be afraid to pursue STEM because of its reputation of being all about quantitative skills. Scientists and other STEM careers involve many other soft skills. For example, being a good communicator is a key skill scientists need.
2. Surround yourself with good people. Having good mentors that can challenge and support you is super important for your current and future jobs/experiences. Being with brilliant and kind people improves your work and how much you enjoy your work.
3. Deciding to not pursue a specific STEM career is not a failure! Sometimes it takes some trial and error to discover what you really enjoy. A background in science is always helpful.
4. Always keep your options open and have a backup plan. Being open to change in your life and your career makes you more resilient to challenges and can make you happier in your career.
5. Last but not least, Dr. Bernhardt believes you should be having fun at least 50% of the year. One bad day or one bad week is not going to tank everything. Nevertheless, you need to make sure that your job, whatever it ends up being, is still fun and something you enjoy!

Mentors: Anne Draelos, Ph.D., Liz O’Gorman, John Pearson, Ph.D (Department of Biostatistics and Bioinformatics)

The intersection of neuroscience and advanced computational software opens the door for increasingly complex and integrative experiments. Improv is a software platform that allows users to have flexibility in controlling experiments and provides live data analysis and visualizations. The original visualization of improv works sufficiently, however it lacks accessibility and effortless control from the user. I am developing an updated visualization that addresses these issues and integrates seamlessly with improv. Jupyter Notebook is the base for the visualization, which can easily be accessed through a web browser and gives users control over which plots and visuals are displayed. In order to create the various components of the visualization, data must be loaded in from improv. This process will be facilitated by ZMQ, a program that can communicate between Jupyter Notebook and improv’s data store and data acquirer. After efficiently loading the data, I am developing live updating plots of neural data and images. These plots are built through Python packages such as Matplotlib and jupyterplot, and they will be timed for their efficiency. Key features of the updated visualization include easy accessibility and broader control for experimentalists, thus providing insightful and more intuitive information of ongoing experiments for the user.

Over this past week I really enjoyed listening to everyone’s chalk talks and learning about their projects. I was particularly interested in Piper’s talk and her project on the gut microbiome. Nutrition is very important to me, so I’m always eager to learn more about the interaction of our nutrition, the immune system, and the gut.

Piper works in Dr. Lawrence David’s lab and her project revolves around the question: How does total parenteral nutrition (TPN) affect gut fiber fermentation? TPN is a form of nutrient delivery from a tube that is commonly used for patients undergoing HSCT, a stem cell chemotherapy treatment for cancer. TPN is necessary because HSCT can cause nausea and negative side effects which make it difficult to eat. One big downside to TPN is that the nutrients never reach the gut, and the gut microbiome is starved. Piper is looking to explore the negative effects of TPN on the gut, specifically fiber. Piper’s lab has previously established the importance of fiber for gut health, specifically the amount of bacteria and level of diversity. 

Piper did an amazing job of explaining the background information that was necessary to understand her research question. Throughout her entire presentation, she kept the whole audience engaged, and it was easy to follow the logic of her project and methods. Piper emphasized the significance of her project in relation to the issues TPN causes and how her work could open the door for research on less harmful solutions. Of course, her research also has the potential to further what scientists know about the gut microbiome. Overall, I was very impressed by Piper’s chalk talk and I’m excited to see how her project progresses!

Down a few stairs of the LSRC and through the doors of the Center for Cognitive Neuroscience lies the Pearson Lab. As I walk in each morning, I’m greeted by the other undergrad in the lab, Chris, my mentor Dr. Anne Draelos, and whoever else is there. To start my day, I set up my laptop with a monitor and get settled into my desk, usually with tea or coffee in hand. Anne always comes by to check in on the progress I’ve made with my project, and we discuss objectives for the day as well as general goals going forward.

The bulk of my day consists of coding, debugging, and researching. Currently, I’m working on creating plots that have live updates as new neural data comes in and also including information about the stimuli that’s present during the experiment. Tackling tasks like this requires me to explore different Python packages and experiment with different lines of code. As a coder, my best friends are Stack Overflow and Slack. Whenever I get stuck working on a piece of code, my first line of defense is to google to the problem and then look on Stack Overflow for solutions from people with similar problems. If I’m still stuck after a couple of attempts, I’ll use Slack to send a message to Anne. Slack is one of the main forms of communication at the Pearson Lab, aside from talking in-person. We all use Slack to send messages about meetings, questions, and other general lab information. My mentor Anne works between two labs, so at least once a day I hear “If anything comes up, send me a message on Slack,” and her response comes minutes and usually seconds later.

As for general day to day life in the lab, many other people trickle in throughout the day. There can be as many as 10 or 15 people there on a given day. My desk is in the side room, along with Chris, Liz (another one of my mentors on the improv team), and Trevor. The PI, Dr. John Pearson, comes down from his office around once a day and checks in on everyone. We have lab meetings on Mondays, a meeting with the improv team on Thursdays, and a meeting to merge code branches on GitHub on Fridays. I really enjoy the comradery of the lab and the research work I’m doing makes me feel like a real computer scientist!

Ever since Dr. John Pearson was a kid, he knew he wanted to be a scientist. He is now living out that dream with his own lab, the Pearson lab. Earlier this week, I had the privilege of sitting down with him to hear his story.

Dr. John Pearson grew up in Kentucky and went to University of Kentucky to study math and physics and earn his Bachelor’s degree. Afterwards, he earned his PhD in Physics from Princeton. At this point, he was unsure about what he wanted to do, but he knew he had an interest in neuroscience, sparked by a neuroscience and physics class he took his last year of grad school. Inspired by that interest and his passion for science, he applied for a couple postdoc positions. He started at Duke in 2005 working under Dr. Michael Platt and he studied the neurobiology of decision making in monkeys. This lab was on the bigger side, which was something Dr. Pearson really enjoyed. He appreciated being in an environment where collaboration and learning was encouraged. This stood out to me because the value of teamwork is central to his own lab currently.

A few years and a couple postdoc positions later, Dr. Pearson developed an interest in data science and machine learning. In his time away from the lab, he started taking online coursera classes and training himself in that area. Not long after, he received a grant from the National Institutes of Health (NIH) to explore the intersection between computation work and neuroscience. He was an Assistant Research Professor in the Duke Institute for Brain Sciences from 2015-2018. In 2018, he signed to stay at Duke and started his own lab, the Pearson lab, which focuses on modeling and analyzing neural data using cutting edge computational tools. Since 2018, he has been an Assistant Professor in the Department of Biostatistics and Informatics, under Duke’s School of Medicine. He really enjoys being the Principle Investigator of the Pearson Lab and some of the highlights include: overseeing a multitude of projects, training and mentoring students, creating an energizing environment with the team, and of course developing amazing new technology. 

Interviewing Dr. Pearson about his journey to becoming a scientist was super insightful and also inspiring for me as I start my journey into science. His path was pretty complex and there is one final piece of insight related to this that I would love to share. I asked him about general lessons for budding scientists and he told me this: Research is hard – it’s as if you’ve been dropped in a jungle with no map. You might panic and it might take a long time to get out, but with some hard work, you will eventually find your way to your passion.

Visualizations are a key tool for researchers to be able to communicate their data and results. Great visuals can give scientists the power to internalize complex systems. This summer, I am working with Dr. John Pearson’s lab on their improv software, which has its own visualization of real-time neural activity when implemented with neurobiology labs. For my research project this summer, I am creating a new visualization that integrates seamlessly with the improv software and improves upon the legacy visualization.

Currently, Anne Draelos, a postdoc at the Pearson Lab, collaborates with Dr. Eva Naumann’s lab to implement improv in their experiments with zebrafish. The zebrafish are shown various stimuli to mimic shadows that would be seen in the water, and improv identifies real-time neural activity that correlates to each stimuli. After a few rounds of different stimuli, improv then predicts and suggests which stimulus will prompt the most neural activity. During this entire process, improv displays its GUI (a graphical user interface, also referred to as “gooey”). This GUI contains a live image of active neurons that are color coded for their correlating stimuli, a line graph of population neural activity, and a replica of stimuli being shown. Below is an example of the GUI in action from the improv paper.

For my new visualization, I plan to improve on the legacy GUI by making it more accessible to users through a platform called Jupyter Notebook. This can be accessed through a browser, unlike the old PyQt platform used. I also plan to add a wider variety of graphs and plots to aid experimentalists’ understanding of the data. Some examples include histograms, scatter plots, and video plots of the current stimuli and what improv suggests. My project will be split into two major steps:

1. First, I will be exploring how to create plots with live updates of the data. This will require me to learn how to use Jupyter Notebook as my base platform and learn how to plot some basic data. Then, I will explore some Python packages to help with the live aspect of the data. The incoming data needs to be integrated into existing plots in a fast and efficient way.
2. Next, I will look into the best ways to access the actual data from improv and incorporate it into the Jupyter Notebook. One potential solution is to implement plasma, a software developed by Apache Arrow.

Overall, I am excited to tackle this project and contribute to the future implementation of improv!

Hi everyone! My name is Amelia and I’m excited to blog about my journey with BSURF. I expect to learn a lot this summer, and grow as both a researcher and a person. 

I am working in the Pearson lab, more specifically with a team that is working on a software called improv. For some basic background, improv is a platform used for adaptive neuroscience experiments. The Pearson lab works in collaboration with other neuroscience labs to collect brain scans, and improv allows for real-time data analysis of neural activity.

Prior to the start of BSURF and working in the Pearson lab, I was apprehensive about my lack of experience with Python and developing software. However, having Week 1 under my belt has eased those nerves and helped shift my mindset to a state of excitement and preparation about the work that lies ahead. From just Week 1, I have already learned so much, and I expect this to be a continuing trend for the next 7 weeks. I have begun maneuvering my way around a Linux command line, I finished installing the improv software, and I am starting to dive into more Python specific tasks. 

Going forward, I foresee a lot of trial and error, and personal devotion to advance my abilities as a coder. It is still intimidating to be a newbie working with very intelligent people on such a cool project. But, I predict that by the end of these 8 weeks, I will feel more confident and proud of the work I’ve done. I am very grateful for BSURF, Dr. Grunwald, Dr. Harrel, and everyone at the Person lab for this amazing opportunity and I am eager to make the most of this summer research experience!