Aurel A. Lazar

819 CEPSR, Mail Code: 4712
Phone: +1 212-854-1747
Fax: +1 212-932-9421
Home Page
Office hours: TBA
My research interests are at the intersection of computational, systems and theoretical neuroscience. The computational/theoretical work builds on
methods of communications/networking, information theory, machine learning, nonlinear systems, signal processing and systems identification. The experimental work employs methods of genetics, neurophysiology and systems biology.
In silico, my focus is on neural encoding in and systems identification of sensory systems, and, spike processing and neural computation in the cortex.
In this work, I investigate rigorous methods of encoding information in the
time domain, functional identification of spiking neural circuits as well as
massively parallel neural computation algorithms in the spike domain.
Furthermore, I am interested in genetic, structural, functional and
plasticity principles of sensory systems in mammals and simple
invertebrates.
In vivo, my focus is on the olfactory system of the Drosophila. My current work primarily addresses the nature of odor signal processing in the antennal lobe of the fruit fly.
Publications
Aurel
A. Lazar and Eftychios A. Pnevmatikakis, Consistent
Recovery of Sensory Stimuli Encoded with MIMO Neural Circuits,Computational Intelligence and Neuroscience, Volume 2010,
2010, Special Issue on Signal Processing for Neural Spike Trains, doi:10.1155/2010/469658.
Aurel
A. Lazar, Population Encoding with
Hodgkin-Huxley Neurons, IEEE Transactions on Information Theory, Volume 56, Number 2, pp.
821-837, February, 2010, Special Issue on
Molecular Biology and Neuroscience, doi:10.1109/TIT.2009.2037040.
Aurel
A. Lazar, Eftychios A. Pnevmatikakis and Yiyin Zhou, Encoding Natural Scenes with Neural Circuits with
Random Thresholds, Vision Research, 2010, Special Issue on
Mathematical Models of Visual Coding, doi:10.1016/j.visres.2010.03.015.
Anmo
J. Kim, Aurel A. Lazar and Yevgeniy B. Slutskiy, System Identification of Drosophila Olfactory Sensory
Neurons, Journal of Computational Neuroscience, 2010, Special Issue on
Methods of Information Theory in Neuroscience Research, doi:10.1007/s10827-010-0265-0.