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Dynamics and network motifs in neuroscience

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Professor Carina Curto, The Pennsylvania State University (Mathematics Department)
When
12 September 2019 from 3:45 PM to 5:00 PM
Where
117 Osmond
Contact Name
Reka Albert
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 Beginning with the Hopfield model in the 1980s, attractor neural networks have been a popular framework for modeling neural functions such as memory encoding and retrieval. In this talk, I will present a related attractor neural network model that exhibits a wide variety of nonlinear dynamics, including multistability, limit cycles, and chaotic attractors. We study how the dynamics in these networks relates to the underlying graph of connectivity. Interestingly, we find that some architectures support a variety of dynamic regimes, while others tightly constrain the qualitative dynamics. These findings are based on mathematical analyses, but give some insights about the relationship between network structure and function in the brain.

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