Fadi Karameh

Title: System Identification as a searchlight for Neuronal Modeling

Abstract: 

System Identification (Sys ID) is a set of well-established theoretic concepts utilized for developing predictive models in control theory.   With Sys ID sharing many common goals with neural modeling, several of its concepts can be extended and utilized to improve upon of current techniques in experimental data assimilation for understanding brain function. In this talk, I will discuss how some of the shortcomings and challenges of experiment design and nonlinear neural modeling can be addressed using system identification concepts.  I will present examples that include:  designing efficient stimulation schemes for identifying neural models, and constraining   brain connectivity models of electrically-induced seizures from scalp EEG signals

Biography:

Fadi N Karameh is an Associate Professor in the Electrical and Computer Engineering Department at the American University of Beirut (AUB) in Beirut, Lebanon. Prof Karameh joined AUB in 2003 shortly after graduating from the Laboratory of Information and Decision Systems at the Massachusetts Institute of Technology (MIT) in Cambridge, USA. With an emphasis on neurophysiological signals and systems, his interdisciplinary research brings together detailed understanding of cellular mechanisms in the area of computational neuroscience and system-theoretic approaches in identification, estimation and signal processing in the area of electrical engineering. His current interests include using intracranial and scalp recordings for the analysis, detection and modeling of the initiation and propagation of naturally-occurring and stimulus-induced seizures in brain cortical networks.


 

 

 

 


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