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July 2021


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Fri, 16 Jul 2021 14:54:27 +0000
Carol McHugh <[log in to unmask]>
Carol McHugh <[log in to unmask]>
PHD-BIOE-L <[log in to unmask]>
To: "BIOE-Faculty ([log in to unmask])" <[log in to unmask]>, "[log in to unmask]" <[log in to unmask]>, Amir A Khan <[log in to unmask]>, Bengt Roland Ljungquist <[log in to unmask]>, Carolina Tecuatl Tolama <[log in to unmask]>, David Lemonnier <[log in to unmask]>, Diek W Wheeler <[log in to unmask]>, Fernando Mut <[log in to unmask]>, Ketan Mehta <[log in to unmask]>, Ramya Chandrasekaran <[log in to unmask]>, Samuel Acuna <[log in to unmask]>, Suman Alishetty <[log in to unmask]>, Susannah Engdahl <[log in to unmask]>
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Notice and Invitation
Oral Presentation of Dissertation Proposal
Department of Bioengineering
Volgenau School of Engineering, George Mason University

Nate Sutton

Bachelor of Science in Biology, Quinnipiac University, 2005
Master of Science in Biomedical Informatics, Arizona State University, 2012
Data-Driven Spiking Neural Network Models To Refine Theories Of Hippocampal Function

Friday, July 30, 2021, 2:00-4:00 pm
Via Zoom<>
All are invited to attend.

Dr. Giorgio Ascoli, Dissertation Director
Dr. Vasiliki Ikonomidou, Committee Chair
Dr. Nathalia Peixoto
Dr. David Hamilton

Computational modeling has contributed to hippocampal research in a wide variety of ways and through a large diversity of approaches, reflecting the many advanced cognitive roles of this brain region. The work in this proposal has a purpose of advancing theories of hippocampal function through providing resources for and modeling of data-driven simulations. Planned work includes the creation of a literature review and knowledge base on spiking neural network models of the hippocampal formation. This knowledge base will offer advanced search options, a variety of statistical reporting, and many types of simulation property annotations including neuron types and anatomical subregions which match those reported on The annotations will also consistently include evidence descriptions that provide details about why they were chosen. A large-scale simulation of spatial navigation is planned, and it will include the investigation of complex navigation dynamics. High-performance computing will be used to support the modeling scale. The integration of several neural properties based on data will benefit the biological accuracy of the work. The software will be designed in a way that is modular and can be efficiently customized for future experiments. Specific hypotheses related to how boundary cells communicate with grid cells will be studied. The use of place cells as an intermediary process in the communication will be investigated. Analyses will be made of alterations that the communications make on grid cell neural activities. Evaluations will be made of differences that occur in neural activity when improved neural property representations are added to modeling through the use of data.