Theoretical Condensed Matter and Biological Physics
PhD University of Rhode Island, 1999
The research in my group is aimed at understanding the principles of synaptic connectivity in the cerebral cortex. Most of my research projects are linked by a common theme which can be summarized as: inferring synaptic connectivity through the quantitative analysis of neuron morphology. The topics of interest range from the theoretical and computational analyses of real and artificial neural networks and their memory storage capacity, to building cortical connectivity diagrams based on the experimental datasets of neurons reconstructed in 3D, to developing algorithms for automated tracing of neural circuits from light microscopy stacks of images.
Chothani, P., Mehta, V., and Stepanyants, A. Automated tracing of neurites from light microscopy stacks of images, Neuroinformatics, 9(2-3): 263–278 (2011)
Escobar, G. and Stepanyants, A., Statistical traces of long-term memories stored in strengths and patterns of synaptic connections, J. Neuroscience, 31(21): 7579–7590 (2011)
Fares, T. and Stepanyants, A., Cooperative synapse formation in the neocortex, PNAS, 106(38): 16463-16468 (2009)
Wen, Q., Stepanyants, A., Elston, G.N., Grosberg, A.Y., and Chklovskii, D.B., Maximization of the connectivity repertoire as a statistical principle governing the shapes of dendritic arbors, PNAS, (2009).
Stepanyants, A., Martinez, L.M., Ferecskó, A.S., and Kisvárday, Z.F., The fractions of short- and long-range connections in the visual cortex, PNAS, 106(9): 3555-3560 (2009).
Escobar, G., Fares, T., and Stepanyants, A., Structural plasticity of circuits in cortical neuropil, J. Neuroscience, 28(34): 8477-8488 (2008).