BFS Masterclass with Danielle Bassett
"Your brain: A network of neurons that learns a network of concepts"
A Benjamin Franklin Scholars Masterclass by Danielle Bassett
Human learners acquire not only disconnected bits of information, but complex interconnected networks of relational knowledge. The 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. Here, I will discuss emerging work assessing network constraints on the learnability of relational knowledge, and theories from statistical physics that instantiate the principles of thermodynamics and information theory to offer an explanatory model for such constraints. I will then highlight corollaries between those constraints on the learnability of relational networks and the physical constraints on the development of interconnect patterns in neural systems, both leading to hierarchically modular networks. I will close with a discussion of whether and how we can extend this correlative observation to a claim regarding explanation and mechanism for knowledge acquisition. Is the architecture of an optimally learnable network a topological reflection of the architecture of an optimally developed neural network? And if so, what does that tell us about the nature of modeling and computation in the brain?
Please RSVP here.
Fireside Lounge, Arch 200