We are all embedded in multiple, ever-changing networks – the network of colliding particles in the universe, the interacting flows in Earth’s atmosphere, the highways and city streets we traverse, and the family, friends, coworkers, and neighbors that comprise our social networks. But the most complex networks we engage with every day are the ones inside our own brains. When humans learn, we don’t just acquire disconnected bits of information, but interconnected networks of relational knowledge. Our capacity for such learning naturally depends on the architecture of the knowledge network itself, and also on the architecture of the computational unit — the brain — that encodes and processes the information.
In this SFI Community Lecture, neuroscientist Danielle S. Bassett discusses emerging work assessing network constraints on the learnability of relational knowledge, and physical constraints on the development of interconnected patterns in neural systems. What do the correspondences between these domains tell us about the nature of modeling and computation in our brains, and mechanisms for knowledge acquisition? Can we, as networks, use network science to think about ourselves?
Q4 hedge fund letters, conference, scoops etc
Danielle Bassett - Social Engineering Systems
Transcript
So I was home schooled from kindergarten through 12th grade. So all the way through until I went to college and my parents had this really wonderful home library that was had at least a thousand books last time we counted. And so I grew up really loving reading and loving all kinds of areas of science of Humanities of philosophy. And in fact when I became around high school aged I really thought that I was going to be a philosopher. So there's that. And then. Another interesting tidbit about myself is that my dad is an orthopedic surgeon and when I was young even sort of 7 years old he would come back with videos of new surgeries I had to learn and he would play them on the local video or videotape. Does I forget what they used to call them. But anyway. And I wouldn't I would sit there next to him and watch these videos of these new different kinds of surgeries that he had to do. So I became really fascinated by the human body and by the beautiful mechanics of the human body and the idea that a physician can intervene so carefully and so precisely to make someone better. So I became very interested in biology at that point as well. And then lastly towards the later years of high school while homeschooled high school I became very interested in mathematics and in physics and I just thought it was so amazing that we could take these very simple formal isms and formulations and use them to understand the world around us.
I was just blown away by the fact that we can use these these simple mathematical constructs to explain really complicated things from the universe to the human mind. So one thing I think that was a common theme across all of these different interests was the mind. So whether it was philosophy of the mind biology of the mind or mathematics of the mind. And ever since then I've been really fascinated with the mind itself I'm trying to tackle it from all of these different perspectives. So when I think about the mind today is a little bit different than how I thought about it as a 7 year old when I think about the mind today. I often actually think about Leonardo da Vinci and the reason that I think about him is that he made some of the most beautiful artistic representations of the organ of the mind which is the human brain. And when I think about Leonardo da Vinci I often think about his book called thoughts on art and life and the reason that I think about that book is that it provides a really beautiful context for why the mind does what it does. Often it's to create or to engage in relationships with other individuals and that brings me to thinking about love and friendship which motivates many of the things that we do in our lives whether it's science or art. And when I begin to think about love and friendship I think about Facebook and Twitter and Snapchat and obviously Leonardo da Vinci is really rolling over in his grave that I put these two on the same side so I apologize but I do want to ask the question is this more than just free association. What do these two things have in common.
If anything is on the left hand side we have social engineering systems like Facebook. I actually didn't even know the the little icon for Snapchat I had to put that in somebody Shorja I should really get with the program here. All right so what is what is the similarity between a social engineering program. And. The human brain. On the surface of it these two things are could not be more different. However if you think about them in terms of their underlying mathematical structure they have some really beautiful similarities that we can actually use to try to understand the human brain better and that underlying mathematical similarity is that they both turn out to be networks. So what is a network. A network is an object like this which is composed of units which we often called nodes and then relationship between uses which we often call edges. Now the first very simple question is how is Facebook or other social engineering systems a network and that's pretty straightforward right. So node in the network as a person and a edge between two people is friendship. And of course we can put terms on here like the geeks and the jocks and the emo and goth which were very relevant when I was younger. I've been told by undergraduates who engage in research in my laboratory that these terms are very outdated so you can put it whichever term you prefer from your experience high school experience probably on those little groupings. Okay so the mapping of friendships to networks is very straightforward but what about the brain. How is the brain network on the surface of it.
This is the wet gooey organ that sits inside of your skull and there's nothing about it that is really particulate in that way that a social network is. So what I'd like to do is to suggest that we look inside and see whether we can understand mathematically why the network structure is relevant for understanding the mind. The first question we have to ask is what our.
