Graduate Student Spotlight: Ryan Senne, Computational Neuroscience PhD Student

How does the brain implement adaptive decision-making strategies?

By Hariri Institute Staff

Hariri Institute Graduate Student Fellow Ryan Senne studies how the brain implements adaptive decision-making strategies, focusing on internal systems like neurotransmitters and astrocytes, and developing state-of-the-art machine learning models to describe datasets. His research interest is at the intersection of machine learning, statistical modeling, and neurological decision-making. Senne is a computational neuroscience PhD student at BU’s Chobanian & Avedisian School of Medicine and is advised by BU Professors Brian DePasquale (ENG, BME) and Benjamin Scott (Psychological and Brain Sciences, BME). Senne graduated with a bachelor’s degree in neuroscience from Boston University in 2021.

Hariri Institute: Can you describe your research focus and its applications? 

Senne: Everyday agents must make decisions by integrating sensory information from their environment, weighing evidence, and predicting future outcomes. This decision-making process is significantly influenced by internal states—factors such as motivation, circadian rhythms, and satiety, which can shape the behavioral strategies employed. My research focuses on how the brain implements adaptive decision-making strategies, with particular emphasis on two novel candidates: neurotransmitters and astrocytes (non-neuronal cells in the brain). Neurotransmitters are the chemical messengers that neurons use to communicate, and the noradrenergic system is believed to be crucial for optimizing these strategies. In parallel, astrocytes have recently been recognized as vital regulators of neurotransmitter systems. My work aims to explore how these two elements contribute to adaptive decision-making. 

To address these questions, I employ two primary methodological approaches. First, I conduct empirical studies using fluorescence microscopy to record activity from neurons and astrocytes while animals perform “evidence-accumulation” tasks. Second, I am developing novel machine learning models to infer how neuronal and glial dynamics change from moment to moment and how these dynamic changes are reflected in the behavioral states of animals. 

My research has several important applications. Neuropsychiatric diseases and disorders are increasingly recognized for their broad impact on decision-making and higher cognition. These conditions indisputably affect how neurotransmitter systems operate in the brain, and consequently, the behavioral systems they modulate. Understanding how an agent makes a decision provides insight into the inner workings of the brain and the delicate systems vulnerable to malfunction. Additionally, the field of neuroscience is generating massive multivariate time series datasets, which are challenging to analyze without methods that can succinctly describe the underlying data-generating processes. My goal is to develop tools that address this challenge, enabling neuroscientists to continue advancing our understanding of the brain. 

Hariri Institute: How did you become interested in this? Was there something that inspired this area of interest?

Senne: I have always been drawn to the “big questions”—why are we here, what makes us human, and what does it mean to live a good life? Neuroscience is central to many of these questions because human behavior and our very essence emerge from highly advanced evolutionary mechanisms. During my undergraduate studies at Boston University, I worked in Dr. Steve Ramirez’s lab, where I was given the freedom to explore a range of projects. This experience hooked me on research, as I realized I could be the first person to discover something new. I soon became enamored with using mathematics to describe large neural datasets, and when I started my Ph.D., I knew I wanted to build models to describe complex behavior. This passion continues to drive my work. 

Hariri Institute: What are the main goals or objectives of your research?

Senne: My research has two primary goals: to understand how internal systems like neurotransmitters and astrocytes are necessary for adaptive decision-making and to develop state-of-the-art machine learning models to describe the datasets I intend to collect. 

Hariri Institute: Has there been a recent development or finding that you find particularly exciting?

Senne: Over the past year, I have been developing an open-source software package in Julia that can fit a variety of state-space models. These models are incredibly powerful in neuroscience, yet few existing packages can handle the breadth of models we aim to implement in a single package. This is particularly exciting for the neuroscience community, as it is increasingly easy to amass massive time-series datasets that are ideally suited for this type of modeling. I anticipate releasing this package in the next few months, providing neuroscientists and those interested in state-space modeling with a robust toolset in Julia! 

Hariri Institute: What advice do you have for students entering the first year of a PhD program?

Senne: My advice is to take it slow. It’s easy to become overwhelmed by the sheer volume of material one could study, leading to overcommitment and burnout. I found it easy to burn out in my first year with classes, rotations, and research. Make time for yourself and accept that you won’t have time to figure everything out. A Ph.D. is brief; what makes yours special is your deep interest in your specific topic, leading to a thesis amount of work. 

Hariri Institute: How do you plan on using this fellowship opportunity?

Senne: I’m particularly excited about this fellowship because it will enable me to attend more conferences and potentially summer programs in computational neuroscience. As someone relatively new to computational neuroscience, I’m always looking for opportunities to expand my knowledge. I’m incredibly thankful for this opportunity and intend to use it to enhance my skills.

The Hariri Institute’s Graduate Student Fellowship recognizes outstanding PhD Student Researchers at BU and supports their development through collaboration with other Graduate Student Fellow cohorts to organize and support Institute-sponsored events and through internal networking between fellows and the wider Hariri Institute community. 

Learn more about current Graduate Student Fellows and the program here.