Campuses:

Complexity

Monday, February 12, 2018 - 10:30am - 11:30am
Kentaroh Takagaki (Leibniz Institute for Neurobiology )
Advances in multi-channel/multi-detector recordings and data analysis over the last decades have led to an explosion in the exploration of complex neural dynamics in mammalian cortex. Powerful methods have been applied to investigate such dynamics, including connectivity measures (correlation, causality, resting state synchrony, etc.), spatiotemporal pattern analyses, and finite-element modelling based on model neurons.
Sunday, October 31, 2010 - 5:00pm - 6:30pm
Jan Hesthaven (Brown University)
The development and application of models of reduced computational
complexity is used extensively throughout science and engineering to
enable the fast/real-time modeling of complex systems for control,
design, or prediction purposes. These models, while often successful
and of undisputed value, are, however, often heuristic in nature and
the validity and accuracy of the output is often unknown. This limits
the predictive value of such models.

In this tutorial we will review recent and ongoing efforts to develop
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