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April 2017

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From:
"Diane St. Germain" <[log in to unmask]>
Reply To:
Diane St. Germain
Date:
Fri, 14 Apr 2017 16:57:49 +0000
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Thesis Defense Announcement
To:  The George Mason University Community
Candidate:  Ryan Purwin

Program: M.S. in Biology



Date:   Thursday, April 27, 2017

Time:   1:00 pm

Place:  Krasnow Institute, room 222
             George Mason University
             Fairfax Campus<http://www.gmu.edu/resources/welcome/Directions-to-GMU.html>




Title: “Enhanced Recording of Discharge Events by Localizing Genetically Encoded Voltage

               Indicators to the Neuronal Soma”
Thesis Director: Dr. Theodore Dumas

Thesis Committee: Dr. Nadine Kabbani, Dr. Patrick Gillevet



All are invited to attend the defense.



Abstract:
Genetically Encoded Voltage Indicators (GEVIs) convert changes in the electrical potentials of cell membranes to changes in the intensity of fluorescence emission. Numerous types of GEVIs have been created and shown to track neuronal action potentials with high fidelity and a sufficient signal to noise ratio in cultured neurons and simple organisms. Problems have been encountered when even the best GEVIs have been expressed in complex mammalian circuits, the most concerning being a low signal-to-noise ratio resulting from cell-wide expression of the GEVI and high density and overlapping neural architectures from different cells. A way to rectify this issue is to restrict the surface expression of the GEVI to a specific neuronal compartment; for action potentials, the optimal compartment is the neuronal soma. Restriction of any GEVI to the neuronal soma can be achieved by fusing it to a soma-localizing motif. Differentiated PC12 cells transfected with our construct, FireFluo, have been shown to emit fluorescence that is largely contained in the soma. Future directions include soma localization of additional GEVI types, testing of soma-restricted GEVIs in complex circuits, and eventually tracking of thousands of neurons in behaving animals, leading to a better understanding of relationships between activity patterns in neural circuits and specific cognitive abilities.


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