Understanding synaptic connectivity principles in the local circuits of mammalian brains is one of the oldest and most important problems in neuroscience. Without clear knowledge of connectivity principles it is virtually impossible to understand how the brain functions or to understand neural circuitry changes, which underlie neurological disorders. The morphology of neuronal arbors holds valuable information about the principles of synaptic connectivity in the brain. Quantitative analysis of neuronal morphology can shed light on a number of important questions: Are there precise wiring mechanisms during development that lead to specific connectivity patterns in the adult brain? What are the structural plasticity potentials for connectivity between different classes of neurons? What are the strategies used by different neuronal classes to find their post-synaptic partners? We are developing a consistent methodology, which will put us in a position to approach these questions in a quantitative manner. We are building a new method for detecting significant spatial correlations between pairs of neuronal arbors reconstructed in three dimensions (3D). This method has potential for identifying specific features of synaptic connectivity that are introduced by precise widening mechanisms during development. In addition, we are introducing a quantitative description of the potential for structural synaptic plasticity for connectivity between different classes of neurons. I propose to study connectivity principles in local circuits of the mammalian brain under the mentorship of Drs. Chklovskii (sponsor) and Svoboda (co-sponsor) at Cold Spring Harbor Laboratory (CSHL). Their laboratories have track record in theoretical and experimental studies of synaptic connectivity. I will work with neuronal pairs and triplets, reconstructed in 3D with Neurolucida in Dr. Chklovskii's laboratory, which will provide a unique opportunity to get insight into the difficult questions of connectivity. This award will give me a chance to focus all my efforts on understanding a very interesting and important biological problem. It will help me enhance my knowledge of experimental and computational neuroscience through hands-on experimental training in CSHL facilities, participation in relevant courses, meetings and conferences, and interaction with leading neuroscience laboratories in the field such as the Chklovskii, Svoboda and Huang laboratories. By the time of the completion of the award I should have the skills and knowledge of experimental techniques necessary to conduct independent research.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Mentored Quantitative Research Career Development Award (K25)
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NST-2 Subcommittee (NST)
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Liu, Yuan
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Northeastern University
Schools of Arts and Sciences
United States
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Chapeton, Julio; Fares, Tarec; LaSota, Darin et al. (2012) Efficient associative memory storage in cortical circuits of inhibitory and excitatory neurons. Proc Natl Acad Sci U S A 109:E3614-22
Stepanyants, Armen; Escobar, Gina (2011) Statistical traces of long-term memories stored in strengths and patterns of synaptic connections. J Neurosci 31:7657-69
Fares, Tarec; Stepanyants, Armen (2009) Cooperative synapse formation in the neocortex. Proc Natl Acad Sci U S A 106:16463-8
Wen, Quan; Stepanyants, Armen; Elston, Guy N et al. (2009) Maximization of the connectivity repertoire as a statistical principle governing the shapes of dendritic arbors. Proc Natl Acad Sci U S A 106:12536-41
Stepanyants, Armen; Martinez, Luis M; Ferecsko, Alex S et al. (2009) The fractions of short- and long-range connections in the visual cortex. Proc Natl Acad Sci U S A 106:3555-60
Escobar, Gina; Fares, Tarec; Stepanyants, Armen (2008) Structural plasticity of circuits in cortical neuropil. J Neurosci 28:8477-88
Stepanyants, Armen; Hirsch, Judith A; Martinez, Luis M et al. (2008) Local potential connectivity in cat primary visual cortex. Cereb Cortex 18:13-28
Stepanyants, Armen; Tamas, Gabor; Chklovskii, Dmitri B (2004) Class-specific features of neuronal wiring. Neuron 43:251-9