Youngmin Park: On Oscillating Postdoctoral Tenures and Dynamically Creative

By Robyn Humphreys, Communications and Event Assistant

Youngmin Park is doing his second post-doc at the University of Manitoba, with Stephanie Portet. He has two research directions, one in cell physiology and the other in neuroscience — using methods from dynamical systems in both fields. Additionally, this fall he will be teaching MATH 3440, ordinary differential equations.

He is careful not to burn out though and takes work-life balance very seriously. In Youngmin’s spare time he enjoys creative pursuits such as playing his ukelele or guitar and singing. Art has also become a recent interest, setting time aside every night to sketch a reference image of whatever subject comes to mind. And to help relieve stress, Youngmin takes high-intensity interval-style training 4–5 times a week. His workouts are often a combination of running, biking, rowing, and/or lifting.

During Covid, Youngmin has been thankful for his good mental health. Taking better care of himself and connecting more closely with his friends has helped him engage more deeply with his hobbies and research, making him more productive in both.

Fennec Fox — By Youngmin Park

Your research is a combination of dynamical systems and physiology and you will be working with Stephanie Portet (our PIMS site Director at the University of Manitoba). How did you get here?

The work I’ll be sharing for my talk stems from my doctoral work in neuroscience. I study neural oscillators, which are often found in central pattern generator (CPG) circuits, which maintain rhythms such as feeding, swimming, breathing, and walking. A subset of this work includes reducing the dimensionality of models to simpler equations that capture the model’s desired properties. For networks of oscillators in CPG circuits, the desired property often involves phase differences between oscillators. One of the most general methods to this end over the past 50 years includes the classic “weak coupling” theory — however, it comes with the significant caveat that oscillators influence each other very weakly. In my work I extend this theory to include strong coupling, allowing for applications in more realistic CPG circuits where neurons are strongly coupled (i.e., each neuron strongly influences the membrane potential of postsynaptic neurons).

This figure shows how my strong coupling theory (a dimension reduction method) predicts phase-locking in synaptically coupled neural oscillators with coupling strength varying from weak (gsyn=0.02 left column) to strong (gsyn=0.25 right column). My method is labeled “Order 4”. A, top: For weak coupling (gsyn=0.02) all reduction methods, weak and strong, predict stable antiphase and unstable synchrony. A, bottom: Phase differences in the original system suggest that antiphase is stable and synchrony is unstable, consistent with A, top. B, top: For a moderate coupling strength, gsyn=0.09, all reduction methods, weak and strong, predict stable antiphase and stable synchrony. B, bottom: phase differences in the original system are consistent with the reduction methods. C, top: For strong coupling, gsyn=0.25, only the fourth-order theory predicts near-synchronous phase-locked states. C, bottom: phase differences in the full system are consistent only with the fourth-order reduction method. This figure demonstrates how my method theory greatly outperforms existing coupling theory.

I’ve only recently moved into cell physiology, which started with my previous postdoc at Brandeis, and will continue with Stephanie Portet at Manitoba. Experimental data is sparse when it comes to molecular motor transport (due to exceedingly small spatial scales on the order of nanometers), so modeling becomes a valuable tool in this context. We will consider models of molecular motor transport at different levels of coarse-graining to better explain the mechanisms behind experimentally-observed data. In particular, I will be determining precisely how noise (paradoxically) stabilizes the transport of intermediate filaments.

This is your second postdoc. What or how do you think it will be different from the first you did at Brandeis? How have you been settling in since your move?

I anticipate the differences won’t be too great: both Manitoba and Brandeis are excellent academic environments full of passionate people. Both postdoc advisors are accomplished academics who have and will teach me a great deal of expertise. Maybe since I am further along into my postdoc career, I will be more productive in research.

However, the move from the US has had its challenges—everything is just slightly different enough that it’s been hard to settle into a regular routine. Fortunately, I have friends who genuinely care about my well-being and have helped immensely with the mental part of the adjustment. It also helps that everyone I’ve met in the city has been so kind and friendly. Slowly but surely I am settling in!

Youngmin holding a spider crab. In this photo he was a TA for a computational neuroscience course at Woods Hole, MA, and they were in the middle of a lab dissecting various animals to either record neural activity from them, or stimulate different muscle fibres with music. The crab was unharmed.

Youngmin Park will be speaking at the PIMS Emergent Research Seminar Series, October 13, 2021 at 9:30AM Pacific. Details on his talk, High-Order Accuracy Computation of Coupling Functions for Strongly Coupled Oscillators, can be found here.