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HomeInVivo Biosystems Blog17 Minutes of ScienceSeventeen Minutes of Science: How Brain-Behaviour Relationships Vary on a Transdiagnostic Basis

Seventeen Minutes of Science: How Brain-Behaviour Relationships Vary on a Transdiagnostic Basis

Tune in weekly to our virtual series "Seventeen Minutes of Science" every Tuesday at 11am PST / 2pm ET where we go live on Facebook with a new guest each week to talk about how science and biotechnology is woven into their lives for (you guessed it) 17 minutes!

For episode 53 of 17 Minutes of Science we sat down with Natalia Zdorovtsova to talk about her research into brain-behavior relationships.

Natalia Zdorovtsova is a cognitive neuroscience PhD student based at the Cognition and Brain Sciences Unit, University of Cambridge. She is interested in how brain-behaviour relationships vary on a transdiagnostic basis, and rejects the idea that the complexity of human behaviour is adequately represented by current diagnostic standards. She is also fascinated by complex systems theory, which is why Natalia prefers to apply network models to the study of the brain.

During her PhD, Natalia hopes to understand how differences in brain networks might lead to variation in traits like inattention and hyperactivity. Additionally, she aims to uncover the neural mechanisms underlying hyperfocus, or 'Flow', which is an immersive state of heightened attention.

In her spare time, Natalia is an avid painter. Some of her art is inspired by her work in neuroscience.

Tune in to learn more about Natalia's research.

Transcript

Ben Jussila (Host): [00:00:10] Hello, everyone, and happy Tuesday. My name is Ben Jussila and I am your host today for today's episode of Seventeen Minutes of Science with InVivo Biosystems. It is my pleasure today to introduce our guest, Natalia Zdorovtsova. Natalia is a cognitive neuroscience PhD student based at the Cognition and Brain Sciences Unit at the University of Cambridge. She's interested in how brain behavior relationships vary on a trans diagnostic basis and rejects the idea that the complexity of human behavior is adequately represented by current diagnostic standards, which I think - that rings true for me. I appreciate that. She is also fascinated by complex systems theory, which is why Natalia prefers to apply network models to the study of the brain. During her PhD, Natalia hopes to understand how differences in brain networks might lead to variations and traits and inattention and hyperactivity. Additionally, she aims to uncover the neural mechanisms underlying hyperfocus or flow, which is an immersive state of heightened attention. In her spare time Natalia is an avid painter, and some of her art, inspired by her work - is inspired by work in neuroscience and is actually featured in the background of her frame. So with that, welcome Natalia and thank you for joining us today.

 

Natalia Zdorovtsova (Guest): [00:01:34] Thank you Ben. It's great to be here.

 

Ben Jussila (Host): [00:01:37] So, yeah, I mean, that's that's that's your intro. I don' know if there's anything that you, you want to kind of - any additional context you want to give or if you want to dive right into that timer and we'll hit our seventeen minutes running.

 

Natalia Zdorovtsova (Guest): [00:01:54] So I guess, as you mentioned, I'm a first year PhD student at Cambridge and I work with Duncan Astle at the 4D Lab over at the Cognition and Brain Sciences Unit. So that's a bit more context.

 

Ben Jussila (Host): [00:02:05] Alright. Well true to our name, I'm going to go ahead and start our 17 minute timer and I'm going to jump right in with the first question. So so you are a - so you've joined a lab in your PhD program. Can you tell us a little bit more about the kind of research that you do and what, what exactly it is that you do on the day to day?

 

Natalia Zdorovtsova (Guest): [00:02:36] Yeah. So basically I decided to do a PhD in this subject because I'm really interested in how the brain develops, because as children and early adults, our brains undergo an enormous variety of changes. And it's a very dynamic process. And it's also one that obviously varies between people. Everyone sort of starts off life with potentially similar building blocks and then we all become very different as we age. So what I'm interested in is what might drive those changes, how they look in the brain and also how we categorize people that we might in the diagnostic world consider to be different from the norm. So neurodivergent. And this includes people with autism, ADHD, Dyslexia, Dyspraxia and so on. And essentially in the past, a lot of, a lot of people in sort of the clinical world have categorized these conditions as separate entities, separate disorders based on their own traits with not necessarily much overlap. But actually what people are discovering now is that there's a lot of overlap between these conditions. So I want to understand whether this overlap in traits also translates to an overlap in brain structure and function.

 

Ben Jussila (Host): [00:04:06] That's that's really cool, and that's I mean, for me, for myself, that's that's particularly interesting and reflects what I've found in the literature. At least I have a fairly recent diagnosis with ADHD. And so I've been trying to pull in as much information as I can. And it seems increasingly that it is recognized as more of a spectrum or a set of interrelated disorders that do have a lot of overlap. Um, in your in your research are there are there any particular disorders or differences from from the neurotypical brain that you're interested in? I know that you mentioned inattention and hyperactivity, and I guess I kind of associate that with ADHD or ADD type disorders. But is that is that the main focus or is that just kind of a kind of a subset?

 

Natalia Zdorovtsova (Guest): [00:05:06] Yeah. So, um, basically, I wouldn't say that I'm interested exclusively in ADHD, but I am really interested in kids that we would associate with reduced attention and hyperactivity and also hyper focused states, which, um in terms of flow or intense concentration that are somewhat paradoxically - if you're just looking at the diagnostic criteria of ADHD associated with the experiences of people who have this condition. The great thing about working is in the Cognition and Brain Sciences Unit here at Cambridge is that we have a huge cohort of kids at the Centre for Attention Learning and Memory, otherwise known as CALM. So we pretty much have brain scans of about a thousand kids, as well as a huge behavioral and cognitive inventory that we've taken for each child. And all of these kids vary a lot in their behavioral profiles, cognitive profiles, and potentially also in their neurological profiles. So I have a huge dataset that I'm working with, and we're not necessarily limited to just recruiting kids with a specific diagnosis of this or that. We get to actually see the full scope of variance, which I think is a really special thing.

 

Ben Jussila (Host): [00:06:31] I imagine that's also more informative so that you can look for commonalities and and things that are distinguishing features rather than focusing on a more common, overlapping set of features.

 

Natalia Zdorovtsova (Guest): [00:06:47] Yeah, there are clusters between traits and a neurological profile. so it's really cool. It's kind of helping to redefine how we think about neurodevelopment.

 

Ben Jussila (Host): [00:06:58] That's that's phenomenal. I love to hear that because it's, it seems to be that there's a lot of catching up to do in terms of the way that we used to categorize things versus what's actually helpful and informative for treatment and and lifestyle. And that's - I don't know. I'm, I'm very pleased to hear  things in this context and that this kind of research is going on in that you have access to those kind of tools. We have a question that came in, and the question is, you mentioned an interest in flow and what is that? And so if you can elaborate, that'd be great.

 

Natalia Zdorovtsova (Guest): [00:07:39] So flow states have been reported mainly anecdotally. They're not categorized well in the scientific literature yet, but essentially it's a very immersive state of concentration in which you're, quote, unquote 'in the zone', um, and I reckon that it might have distinct, functional and also maybe structural neurological properties, because it's not just like regular attention as people report, it's it's really a state that people can be in for a stretch of many hours at a time without even considering things going on in their surroundings. So that's kind of what it is.

 

Ben Jussila (Host): [00:08:23] Yeah, and that's I mean, and I guess this is speaking a little bit from experience and from my understanding of the anecdotal evidence, is that it also can be sort of to a detriment of like paying attention to things like, I'm hungry, I need to use the restroom. There's something going on around me that I should be paying attention to. So it can be both an advantage and a detriment, depending on the context, right.

 

Natalia Zdorovtsova (Guest): [00:08:54] Yeah, and also, can affect the way we think about conditions like ADHD. Because, you know, typically we see ADHD as disorder of exclusively inattention. Like you say, these people just can't pay attention to anything. But that's not true because people with ADHD regularly engaged in low or hyperfocus states. So maybe it's an issue of maldistribution of attention rather than necessarily just being a condition where people can't focus on anything.

 

Ben Jussila (Host): [00:09:24] Yeah, that's. I mean, that's - I like to hear that, because that's - I guess when I was first exploring a diagnosis, that was the hesitancy that I had. I was like, well, are people going to think that I'm just kind of like an airhead, that I can't pay attention to anything? That I'm easily distracted? But that's, that's not the whole picture. That's not - that's a very simplified view of things. So I guess in terms of the research that you're doing, the tools that you use - so it sounds like you have this very rich data set and patient base using these neurological profiles and behavioral profiles. What other sorts of tools are you using to sort of interrogate those datasets, to interrogate imaging? Are there any other things like familial traits or genetic information that you're, that you're looking at as well?

 

Natalia Zdorovtsova (Guest): [00:10:18] Yes, I think some of my colleagues are looking more into the genetic side of things. I'm not really involved with that line of research. But this past year, I've been looking at structural MRI scans from about four hundred of these children. And it's important to know that this isn't a patient base. It's recruitment from a wide pool of people. So it's not necessarily people who have had a diagnosis because there are certain biases associated with even getting a diagnosis in the first place

 

Ben Jussila (Host): [00:10:50] Okay.

 

Natalia Zdorovtsova (Guest): [00:10:52] So, yeah, I've been looking at the structural, and also functional MRI scans, which have been really conveniently formatted in some connected models, which are models based on graph theory, if you have any familiarity with that, that essentially - they still play a role in reducing the amount of complexity that we see in actual MRI scan, but they maintain so much of it. So we're looking at, um, kind of the strength of connections between areas of the brain and how certain mathematically defined measures of the brain network or Brain Connectome vary with these inattention and hyperactivity traits. So those are mainly the data sets that I'm interested in right now. And then in the future, I hope to complete some more experimental work with lower hyperfocus states.

 

Ben Jussila (Host): [00:11:54] That's that's really cool. That's - I guess I'm only used to hearing connectome in the context of, like, model organisms, so in C. elegans or zebrafish. But that's, you know, I kind of don't think about those human data sets or those human resources. So one thing that that you mentioned, or is mentioned in your bio, is complex systems theory. How does that fit into either the way that you're modeling these things or the way that you're interpreting the data that you're getting from these, from these datasets?

 

Natalia Zdorovtsova (Guest): [00:12:35] Yeah. So it's important to recognize the complexity of what we're dealing with in Neuroscience, which we seem really self-evident and obvious because we know the brain is probably the most complex object that we know of, but it hasn't always seemed that way. And Neuroscience is a very new field, still in its infancy. So in the past, it's been really easy to just kind of reduce the brain down to segmented parts that in some way they communicate with each other, but this kind of fails to capture, I think, the overall dynamical functions of the brain and kind of the complexity of the structure of the brain that certain connectome models can in some ways capture. So complex systems theory, kind of, it covers a huge scope of things so like Physics, Biology, Chemistry, Sociology. It can pretty much be applied to anything because we're surrounded by complex systems in nature. But I think the real beauty of this way of thinking is that it allows us to see brain function and structure in a new way from before. And so I'm hoping to kind of draw some inspiration from that in building my own connectome models and potentially rely on - relying on more non-linear measures of brain function rather than simply being a reductionist in everything that I do.

 

Ben Jussila (Host): [00:14:17] Yeah, no, that's - I mean, I can I can certainly identify with that in terms of, you know, in a genetics and a model systems sense. Simplified models can be really informative for asking very specific questions. But when you take things in isolation or out of their context, you lose a lot of information and you can really oversimplify things. And I guess to that point, I kind of want to segue into another question, which is about sort of current diagnostic processes and measures versus what you see as sort of what is needed to shift in the field in terms of providing accurate diagnoses or accurate treatment or better treatment, being more inclusive and forward thinking with these things. So how does - what sort of, what's the old way and what do you see as the new way, I guess, is what I'm trying to get at.

 

Natalia Zdorovtsova (Guest): [00:15:33] So my supervisor, Dr. Duncan Astle, and a few of my other colleagues recently had papers out kind of outlining this shift from core deficit models, which are sort of the old deficit oriented way of looking at neurodevelopmental conditions, to transdiagnostic models, which instead of just looking at diagnostic labels that we put on people, um, dimensions of traits. So basically in the past, we used to kind of say, evaluate someone that comes into a clinic and say, OK, according to this inventory, you you're probably autistic or something like that. And you may or may not get this label. And of course, there are impediments to even making it to the clinic in the first place. Right. So unless you get to a certain, I guess, threshold in that clinical evaluation process, and could you make it to the clinic -you're not going to get help for, you know, maybe some of the things that you're struggling with let's say at school, whereas with the more transdiagnostic method, we're not necessarily pointing to deficits that people have. Instead, we're looking at people's traits holistically, seeing how they vary, maybe points where people can receive some extra help, but not putting any specific pressure on whether a person's cognitive, or behavioral profile aligns perfectly with some diagnostic criteria. So, because essentially people who subscribe to transdiagnostic thinking believe that - especially in educational settings - anyone should be able to get help for things that they're struggling with, not just people who are fortunate enough to be able to access a diagnosis.

 

Ben Jussila (Host): [00:17:32] Yeah, I am glad that, that's the thinking. And that sort of rings true to a lot of what I've heard lately about sort of educationally thinking about evaluating learning styles versus trying to fit people into a set way of learning things or a set criteria, or set media for for for learning. How does that get incorporated more readily? How do we work on adopting those kinds of things in the classroom, I guess. I mean, are there are there things that are sort of lacking from an infrastructure standpoint or a health care perspective or a social - social dynamics? I mean, what do we need to do to sort of address that at the, at the root in addition to changing these diagnostic criteria?

 

Natalia Zdorovtsova (Guest): [00:18:39] Yeah. So, I mean, I think there's there's so much, but one thing is probably the bias that people tend to have or preset thinking that people tend to have around neurodevelopmental conditions. So, for instance, a lot of people regard autism as a male exclusive condition, at least on assumption. I'm not necessarily talking about experts or colleagues in my field, but among the general public, it may be assumed that that autism is exclusive to boys and men. And that's not really true. It's just that so much of the research in the past has been focused on boys and men. Oh I hear your timer. Sorry, I'll finish up.

 

Ben Jussila (Host): [00:19:25] It's fine.

 

Natalia Zdorovtsova (Guest): [00:19:25] But now what we're seeing is that there are autistic women they just experience a different profile of traits. So basically within this field, we're constantly proving ourselves wrong about our assumptions. And I think that as this seeps into education and policy and practice, I think we're going to see some improvements in treatment of people with these conditions, not just pharmaceutical treatment, I'm not just talking about that, but simply the regard that we have for the complexity of human behavior and actually the excellence of the fact that there's such diversity. Rather than just, you know, conformity to some model of this ideal person that doesn't exist.

 

Ben Jussila (Host): [00:20:18] Yeah, I mean, it's those differences are something that should be celebrated and those differences are something that should be encouraged or supported. And that's, I think, similar to where precision medicine is going. I feel like we're getting to a point where we're learning and we are making tools and making more resources available that allow for treatment of the individual or support and uplifting the individual rather than trying to categorize and do sort of one-size-fits-all blanket treatments or, you know, or to treat people or talk about people even a certain way. We did come up to the end of our 17 minutes there. I, I certainly could fill another 17 minutes or several asking you, asking you questions about this. But I guess I will close out by asking, is there anything in particular that we wanted the general public to know about your work or know more about your work or about their day to day interactions to take away from this? What would it be?

 

Natalia Zdorovtsova (Guest): [00:21:40] I guess it would be to challenge their assumptions both about people and also the field of Neuroscience, which is rapidly evolving and changing all the time. I think the more readily that we accommodate other people's differences and look for strengths rather than weaknesses, the better off we'll be, both in terms of our personal interactions and also as a society as a whole. So that's sort of my platitude to end on.

 

Ben Jussila (Host): [00:22:12] Well I think it's a really good platitude to end on. Well, you heard it. Everyone go out there and challenge your assumptions and just be excellent and be kind to one another. Thank you so much, Natalia, for joining us today. This will be - this recording will be available. We'll send it to you if there's any information that you want to share with us in terms of resources we're happy to do so. But thank you for joining us and for everyone watching. Thank you. And we will see you next time.

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