Welcome to the SciPhiles, an impact 89 FM series that explores student research here at Michigan State University. cohosts, Marty Dowling.
And Dimitri Joseph.
We are joined by Jared Rielly. Hi, Jared. Thank you for joining us today. Could you tell us a little bit about what what your research is in?
Yes. Of course. So I am a first year PhD student here at Michigan State, the department of computational math, Math, Science and Engineering, and I'm a computational neuroscientist. So for my research, I developed an algorithm that improves multi animal motion tracking by supplementing deep learning models with body model based automatic corrections. Explain to me what multi animal motion tracking is.
We are understanding how 2 or more animals are interacting. We're using computer vision to map how their bodies are moving while they are playing with each other or jumping on top of each other.
Just based off of the titles that you mentioned, the multi animal motion tracking is recording how these 2 ferrets are interacting with each other. But in order to get a better recording or a better use of that data, you're using this approach called deep learning? That's correct. So what we are using is a deep learning model that is able to track these ferrets as they're moving in an enclosed space over time without specifically putting sensors or marking the animals physically. All we need
to do is analyze a video of just them moving around in the space to capture them.
What are the applications of this kind of technology and research?
Of course. So our overall scope is better understanding how social dynamics, social interaction can better help understand mental health disorders. So we are using animals as a model to build a correspondence to how these two animals are interacting with each other and what's going on in their brains. We then hope to take this research from an animal model and then put it into clinical practice and seeing how a therapist and a patient are interacting with each other, how that could help develop new pharmaceutical techniques that will target certain areas of the brain that need to be either stimulated or understimulated depending on what we see in these animal models.
But that that's a very interesting approach that your lab is taking to study mental behavior. And that leads me to the question, do you also probe the brains of these ferrets as you're recording their interactions?
That's correct. So we have sensors and electrodes put inside of these ferret brains, and they're recording cortical activity that's happening in both of these ferrets as they're moving and interacting with
other. Cool. It's interesting that your reads are just simultaneously both computational and hopefully translational.
Exactly. That's the whole point. Bringing together computational, experimental, and translational all into the same
How did you guys get from ferrets to mental health?
Well, ferrets are very social animals compared to other kinds of rodents or other animals, mammals in general. Ferrets are smaller, so there's less overhead in terms of upkeep and storage of these animals, and they're also very social. So using these animals as a model for understanding how people interact makes sense because they're very social with each other. So we can understand how the ferrets are interacting.
That could hopefully be a basis of understanding how humans are interacting. In mapping out or modeling some of the neural patterns that result from specific interactions, have you found an interaction that's best for happiness or that's associated with sadness, or are we just not there yet? Well, there's current research in understanding how these brains are synchronizing as they're interacting. In my stage of this brand new project,
we are first just trying to capture the motion of these animals moving. We hope to next understand what kind of brain synchronization is happening with these animals and link it back to how they're actually moving and interacting with each other.
Thank you, Jared, for giving us a snippet into some really fascinating research that's being done, and we look forward to hearing more in the future, especially as you continue on in your project.
My pleasure. Thank you for having us.
I am with the Department of Teacher Education, and I'm a 1st year student in curriculum instruction and teacher education. I was a teacher in India for 3 years. Teaching them in history classrooms and ideas they're taking back with them. Most of the students will not really study history once they graduate school. So my research interest is in history curriculum, and I'm also really interested in textbooks.
And what are the ideas of nationhood and nationalism that are being depicted in the textbook?
What are some of the things that you're looking at in terms of the history curriculum, and how are you hoping to apply that into teaching?
My group question is this. Like, history is everything that's happened. Like, I can't teach everything. I can only teach, like, small things. So the small things that I'm teaching the students and that we are talking about in history curriculum, Are they true representations of history or are they misrepresentations of history?
It's like a movie and, like, small scene and then you come out. But, like, it's that small scene that's going to give you some pictures, some idea of what the movie is and is it really what the movie is about? So I'm trying to understand how accurate and how relevant the history curriculum is. And right now, how can we make it more accurate and more relevant? A lot of these ideas are being talked about in the textbooks.
They're coming from, like, textbooks are really important as that of course, you can achieve in last week. So I'm also interested in looking at what are the things that are being talked about in the textbooks and how do you pick and choose. Let's say, I'm going to do the Russian revolution, but not the Chinese revolution, you know, things like that. And why does it happen? And the third thing that I'm interested in, how does it change over time?
Because history has happened, but, like, my parents studied something different than I did and probably the next generations must have. But history has not changed. We are just changing how we teach it. And what is it talking? What does it tell us about the society, about the changing sociopolitical curriculums? I'm interested in history and politics of education.
You have a very fascinating topic, and it covers so much. And from what I'm hearing is that you're basically studying how an institution can direct a curriculum and how they make the selective process of what they're teaching while remaining representative and kind of limiting the biases. What approach are you taking to understand how an institution makes these decisions?
It's very context specific, and that's something that I'm learning because, like, I come from India. In India, we have the Ministry of Education, which will publish textbooks that will then be used by the Central Board of Secondary Education, which is this big board of school, and it has been in school. So across India, whichever student studies in, like, the CBSE board schools, they will read that textbook. That's why I feel like it's all the more important to explore what really is it that we are talking about in their textbook because it's just being disseminated at such a public level. But in USA, there's no standardized textbook.
There is one, but it's not necessarily as important as it is for my context. So right now I'm just exploring how do these things context matter in history education and that's sort of what is getting me back to my third point, which was talking about how history curriculum is about so much more than which king fought which battle and, you know, who won which battle. That it's just more about these ideas of societies that we are talking about and that we are translating. So I'm trying to study and my approach right now is to try to figure out who are the people who are designing it, and that might help me understand some of the motivations.
Yeah. The topic that you're approaching, that you're tackling is just very difficult, and it's the idea is in a lot of different fields. For instance, in computational work, there's always that issue about data representation. On one end of the spectrum, we can't represent everyone's story. But as you mentioned, there is a decision that's made about which stories we do choose to tell. There's always a population that serves as the minority population and will be forgotten.
Definitely sounds like a really complicated sharing that.
Yeah. You're welcome.