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Engineering control theory helps create dynamic brain models
Date:2/19/2013

ff. "In comparison, the weather is a breeze."

There are seven equations that govern weather, but the number of equations for the brain is uncountable, according to Schiff. One of the problems with modeling the brain is that neural networks in the brain are not connected from neighbor to neighbor. Too many pathways exist.

"We make and we have been making models of the brain's networks for 60 years," Schiff said at the recent annual meeting of the American Association for the Advancement of Science in Boston. "We do that for small pieces of the brain. How retina takes in an image and how the brain decodes that image, or how we generate simple movements are examples of how we try now to embody the equations of motion of those limited pieces. But we never used the control engineer's trick of fusing those models with our measurements from the brain. This is the key -- a good model will synchronize with the system it is coupled to."

Schiff is looking for the models that represent the parts of the brain he is studying. He looks at the model to see if it can simulate what he observed and if he can fuse the model with the real system. He and his colleagues, with support from the National Institutes of Health, are exploring a wide range of control strategies for epilepsy, Parkinson's disease and migraines.

To do this with brain networks, researchers often have to measure from only one or a few nodes of the system and seek to reconstruct the rest.

"We need to simplify, and then ask, how far into that network can we reconstruct?" asks Schiff. "How far can we control?"

Using group theory, Schiff is trying to answer these questions. Group theory tests whether the inputs onto these nodes can be swapped. If a regular swap of the nodes ends up with the same network, then this is a symmetry of the network. Such symmetries underlie powerful ways to simplify models that represent the underlying structure within brain networks. The
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Contact: A'ndrea Elyse Messer
aem1@psu.edu
814-865-9481
Penn State
Source:Eurekalert

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