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'''1. What topics do you have some expertise in and would you be willing
[[Image:Sarahpic2009.jpg]]
to help others learn them?'''


Well, I suppose that I have some knowldege about physics in general, although these days much of my time is devoted to neuroscience- specifically to epilepsy and seizure prediction.  I look at measures of phase synchrony in neural networks so I have a fair amount of knowledge about networks and synchronization.  I also know a little about stochastic processes but would love to learn more.  On a more practical level, I program in IDL (a language similar to Matlab) and can program a bit in Matlab and Mathematica as well.


'''2. What do you want to learn at the CSSS?'''
I recently finished my Ph.D. in physics at the University of Michigan and am about to head off to a postdoc at UC Irvine.  The title of my dissertation was "Understanding the interplay of structure and dynamics in neuronal networks", and much of my research has focused on questions in the field of neuroscience.  Networks are very important in this field as the brain is a prime example of a very complicated network.  Important features of neuronal networks are that the nodes (neurons) are dynamic due to the firing of action potentials, and the edges (synapses) are constantly evolving.  The main part of my dissertation focused on a new clustering algorithm that utilizes these neuronal dynamics to detect groupings of neurons with similar firing patterns.  I think that studying networks with dynamic nodes will become increasingly important as we try to apply network theory to more types of networks. Since neuronal networks can be viewed as time series of discrete events, I'd like to extend this line of thinking to types of networks outside of neuroscience, and I'm hoping that this workshop will be a good place to do so.


I'm interested in learning more about techniques used to study complex systems in general, but specifically, I'm currently interested in the effects of structure on network dynamics and synchrony.  I'm also looking foreward to interacting with people from a variety of disciplines so that we can all learn from eachother and integrate new ideas into our current work. 
In addition to the algorithm development and subsequent data analysis, much of my time in graduate school was spent doing experimental work growing dissociated hippocampal cultures and studying how the underlying structure of these networks influences their dynamics.  I also spent some time doing computational modeling of epilepsy where I studied two coupled networks of neurons and looked at resonance and driving relationships between the networks as one network transitioned into seizure dynamics. Although this was my first project as a graduate student, my new postdoctoral position will also be in the field of epilepsy research. Network analysis is becoming increasingly important in epilepsy to study the initiation and propagation of seizures, so I'm quite excited to work in this area.
 
'''3. Do you have any projects or research interests that would benefit
from an interdisciplinary approach?'''
 
As a physicist who studies neuroscience, I'd say that every research interest can benefit from an interdisciplinary approach.  I  would be excited if anyone knew something about nonlinear time series analysis in any application. 
 
'''4. Do you have any ideas for what sort of project you would like to
do this summer?'''
 
I would love to study the effects of structure on a neural network's ability to synchronize.  However, I've noticed that there are a few others who work in neuroscience and I'm open to other ideas as well.
 
'''5. Suppose you could travel one-hundred years in the future and ask
researchers any three questions.  What would those questions be?'''
 
1.  What has been the biggest advance in science in general in the past 100 years?
2.  How does the brain work?
3.  Did anyone ever figure out how to fix the fact that quantum mechanics and general relativity don't actually agree?
 
 
 
 
[[Image:sarahpic.jpg]]
 
Hi everyone! I'm Sarah Feldt and I've just finished up my second year of the Ph.D. program in physics at the University of Michigan.  Although my degree will be in physics, my research is best described as being in neuroscience.
 
My current research project investigates network dynamics and communication between two interacting networks of neurons. Through the use of computer simulations, I examine measures of phase synchrony within each network as well as between the networks to gain an understanding of the underlying dynamics. The collective signal of each network can be interpreted as an EEG recording, allowing for a comparison of this model with phase synchrony measurements currently used in seizure prediction.
 
My interests outside of the academic world include KU basketball (my undergrad was at the University of Kansas), baking, and hiking. I also play flute and piccolo in the U of M Life Sciences Orchestra and have the world's cutest kitten named Einsteinia.  I'm very excited about getting to travel to Beijing this summer and meet all of you!

Latest revision as of 05:05, 10 July 2009


I recently finished my Ph.D. in physics at the University of Michigan and am about to head off to a postdoc at UC Irvine. The title of my dissertation was "Understanding the interplay of structure and dynamics in neuronal networks", and much of my research has focused on questions in the field of neuroscience. Networks are very important in this field as the brain is a prime example of a very complicated network. Important features of neuronal networks are that the nodes (neurons) are dynamic due to the firing of action potentials, and the edges (synapses) are constantly evolving. The main part of my dissertation focused on a new clustering algorithm that utilizes these neuronal dynamics to detect groupings of neurons with similar firing patterns. I think that studying networks with dynamic nodes will become increasingly important as we try to apply network theory to more types of networks. Since neuronal networks can be viewed as time series of discrete events, I'd like to extend this line of thinking to types of networks outside of neuroscience, and I'm hoping that this workshop will be a good place to do so.

In addition to the algorithm development and subsequent data analysis, much of my time in graduate school was spent doing experimental work growing dissociated hippocampal cultures and studying how the underlying structure of these networks influences their dynamics. I also spent some time doing computational modeling of epilepsy where I studied two coupled networks of neurons and looked at resonance and driving relationships between the networks as one network transitioned into seizure dynamics. Although this was my first project as a graduate student, my new postdoctoral position will also be in the field of epilepsy research. Network analysis is becoming increasingly important in epilepsy to study the initiation and propagation of seizures, so I'm quite excited to work in this area.