My name is Lilianne Mujica-Parodi.
I'm an associate professor at Stony Brook University in the department of biomedical engineering and I'm also
director of the laboratory for computational neurodiagnostics.
I'm interested in developing an area that I call neurodiagnostics. So, traditionally,
clinical neuroscience has focused on the question of
biomarkers, that is can we identify
Properties of the brain that would then be used potentially diagnostically to say someone's in this category versus that category
Right now I'm working on a very exciting project for the BRAIN Initiative on a brain aging.
I think it's
it's really unusual and it's very
Specifically appropriate to the BRAIN Initiative mechanism because it's operating at many different levels.
So on the one hand, there is a public health component.
It's addressing a real world very timely problem
which is the impact of insulin resistance and Type 2 diabetes on brain aging and the development of
dementia.
It's asking
Again, very practical questions about the impact of diet.
Are there scientifically justified reasons to eat one thing versus another?
And, instead of looking over
Many populations and asking questions that don't have a way to dissociate causality --
That is it's not possible to
identify the specific role of the diet and the outcome -- we're able to probe much deeper and to be able to
Ask what is the role of this nutrient and feeding the neuron versus this nutrient? From a scientific perspective,
it's also
asking a very, very deep fundamental question about
How neurons utilize fuel and how they essentially make decisions in
Reorganizing when those those resources are limited? And
So, on the one hand that there's a really real-world practical application that I think can have an impact
Even in the short-term, but on the other hand, it's a very deep fundamental question about how the brain works
That I think kind of appeals at a totally different level for me as a scientist. So the project that I'm working on
Is actually asking a very deep fundamental question about neuroscience, which is that
When the brain forms Network -- so as a clinical neuroscientist we're used to thinking about networks and visualizing networks with neuroimaging
But we don't really understand what drives the formation of those networks. So. we tend to think that those networks are
produced as a way to
Achieve certain functions in the brain. Let's say
thinking about math, you activate your math network, and if you're
Navigating a maze you activate your spatial navigation network,
But in fact, there are two
optimization
problems that in fact, you have to not only achieve the function that you want to achieve,
If you're a brain network, but you also need to do so in the face of limited
resources. I live in New York and I had to come to this conference which was in Maryland and there are many different routes
I could have taken
And so I had to choose which route to take and if I'm in a hurry
I might take a flight even though it's more expensive
And if I'm more leisurely, but don't have as much money
I might, you know, drive and whether I take a road toll versus one that is more scenic
These are all decisions that are made in the face of competing
Constraints and so what I'm asking about neurons is are they operating in the same way?
Are they making essentially decisions in the face of competing constraints? And
how do those decisions change?
when the amount of resources that they have available changes?