When was the last time you caught a ball, typed an email, or crossed the street? Did you think about this action, or was it simply something you did? These movements are second nature to us, but each one involves complex interactions between sensory input, neural noise and split-second decision making.
How the brain transforms perception into action drives the work of and the multidisciplinary team in his lab. Dr. Blohm is Professor for Computational Neuroscience at Queen’s University, as well as the Vice-Director (黑料吃瓜资源) of Connected Minds. Members of his lab combine physics, psychology and mathematics to investigate how the brain learns to move, adapt, and make decisions.
鈥淪ensory-motor processes are the things to study because they are the reason the brain evolved — to use sensation, or sensory inputs, to sense and act on the world,鈥� says Dr. Blohm.
Dr. Blohm began his academic career with a Master鈥檚 degree in physics, but pivoted to neuroscience during his PhD, drawn in by the challenge of understanding living systems. For Dr. Blohm, the mission behind his research is clear: to uncover the brain鈥檚 most fundamental mechanisms. As he explains, 鈥渢hrough the study of sensory motor control, [researchers] can uncover fundamental principles and mechanisms of brain functions at various scales [from] behaviour to how the brain is set up.鈥�
In practice, how does this mission shape the research questions in his lab? It tends to attract a diverse group of researchers from different fields. While the students in Dr. Blohm鈥檚 lab may be investigating different parts of a system (for instance, from normative to behavioural modelling) they all seek to answer the same fundamental question: how does the brain adapt, decide, and act in the world?
At the same time, building a lab isn鈥檛 just about answering questions. It鈥檚 also about training students to ask better ones. 鈥淕raduate school is training through research,鈥� Dr. Blohm says. He hopes the main skill his students take away from their time in the lab is critical thinking: learning how to ground ideas in evidence, assess the logic behind different scientific approaches, and analyze data in a systematic way. He also encourages students to follow their passions, pursue unconventional questions, and collaborate across disciplines.
3 Students, 3 Paths, 1 Mission
For Connor, understanding the brain begins with pen and paper. As a mathematics PhD student, he is investigating the idea that neurons are not simply passing along signals but acting as decision-makers with each neuron operating with limited information in a complex network. Connor鈥檚 research uses mathematical frameworks from multi-agent systems and reinforcement learning to model the brain as a decentralized network. His research asks how neurons know what to do in such a noisy environment. It鈥檚 a question that mirrors problems in economics and game theory, fields where individual agents make choices based on sparse and sometimes conflicting information.
Connor chose to work with Dr. Blohm after seeing the diversity of research in his lab. 鈥淸Dr. Blohm] really emphasizes the importance of collaboration and multi-disciplinary work for answering questions about the brain,鈥� he explains. This openness led to co-supervision of Connor鈥檚 thesis with , a mathematician at 黑料吃瓜资源. Their project now sits at the intersection of neuroscience, systems theory, and machine learning. 鈥淚t鈥檚 exciting to have an idea,鈥� Connor says, 鈥渁nd to realize that not many people are having the same idea.鈥�
While Connor builds mathematical theories of how neurons communicate, Arefeh is focused on how humans move. With a background in electrical engineering and control systems, Arefeh鈥檚 research blends machine learning, biomechanics, and neuroscience to answer one question: how can we detect abnormal movement patterns, and possibly diagnose disease, just by analyzing video?
鈥淗ow do we distinguish different movements, extract primitives, and then, from those features, distinguish abnormality?鈥� she explains. Her project uses machine learning tools to analyze simple, even smartphone-recorded, videos. She extracts 3D pose data from these videos and identifies movement primitives鈥攕ubtle, repeated patterns in how we walk or gesture. The long-term goal is to create a tool that flags movement irregularities, prompting early screenings or medical follow-ups. 鈥淟ike, hey,鈥� she says, 鈥渕aybe your grandma鈥檚 walk looks a little different鈥攎aybe she should consult with a physician.鈥�
Finally, while Connor builds theoretical frameworks and Arefeh designs practical tools, Sydney鈥檚 work unfolds in real time, with participants adapting to vision loss as her experiment unfolds. Her research investigates how people respond to central vision loss, such as by age-related macular degeneration (AMD), and whether the brain can rewire itself to compensate.
Using eye-tracking, Sydney鈥檚 experiments mimic a central blind spot on screen, forcing participants to rely on their peripheral vision to follow moving targets and track motion. Over the course of several sessions, she observes whether participants develop a new point of focus, known as a preferred retinal locus (PRL). 鈥淲e already know that some AMD patients can develop a PRL in place of their absent fovea in tasks such as reading,鈥� she explains. 鈥淗owever, it鈥檚 unknown if and how this PRL can be used in tracking [moving] targets.鈥�
Her path to the lab was simple: 鈥溾�業鈥檝e been in the lab since my [undergraduate] 4th year thesis project,鈥� she says. 鈥淚 read about the research in this lab and thought it would really align with my interests. I鈥檝e been here ever since!鈥�
Conclusion: The Lab, in Practice
These PhD students work on diverse problems, yet all of their research is grounded in a core mission and philosophy, asking: how does the brain adapt, decide, and act in the world? And how do we train scientists to answer this question in a way that promotes curiosity and critical thinking in equal measure? As Dr. Blohm explains, he wants to give his students 鈥渢he tools and critical thinking and perspectives [to find] their own paths.鈥�
The work coming out of Dr. Blohm鈥檚 lab reminds us that the future of neuroscience lies in embracing uncertainty and complexity. Whether it鈥檚 a neuron making a choice, a body moving abnormally, or a brain adapting to vision loss, the questions that matter are rarely the easiest ones to answer. What connects these researchers isn鈥檛 a single method or problem, but a philosophy that progress begins with curiosity, collaboration, and the courage to ask meaningful questions.
As Dr. Blohm explains, 鈥渢he future of science lies in complex science.鈥�
