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Structural plasticity in neuronal networks

Citation

Mysore, Shreesh Pranesh (2007) Structural plasticity in neuronal networks. Dissertation (Ph.D.), California Institute of Technology. http://resolver.caltech.edu/CaltechETD:etd-11102006-021149

Abstract

Neuronal networks are established during development by the formation of connections (synapses) between neurons. Once formed, these synapses undergo experience-dependent modifications throughout the lifespan of the animal (synaptic plasticity). Additionally, the connectivity pattern itself can be modified in an activity-dependent manner (architectural plasticity). Changes in the structure of synapses, neurons, and networks – collectively called structural plasticity – are the predominant mechanisms for changes in the network architecture in the brain. Structural plasticity forms the focus of this thesis and motivates both the experimental and the computational modeling work reported here. With experiments, we look in detail at one form of structural plasticity, namely dendritic spine dynamics. We develop a unified approach to characterize motility and use this both to detect subtle forms of structural dynamics and to uncover novel phenomena in it. We show that disruption of N-cadherin, a synaptic adhesion molecule, causes spines to first be more motile and to shrink in length, and then to be lost. Along with this, synapses are eliminated as well. For the first time, we show that early structural changes can predict later synapse elimination, suggesting that early dynamics may be readouts for future changes in the neural wiring diagram. We also address some of the related mechanistic questions. In our computational modeling work, we address structural plasticity at the next higher scale of complexity. We provide a novel, neurobiologically plausible, and experimentally consistent explanation for how changes in visual experience may produce axogenesis and the formation of new synaptic pathways in the barn owl auditory localization system. We discuss implications of architectural plasticity to the representational power of networks and explore links with statistical learning theory. Taken together, our work argues that architectural changes are a powerful and indispensable form of neural plasticity and sheds new light on the mechanisms of structural plasticity in the brain, thereby contributing to our understanding of learning and memory.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:architectural plasticity; auditory localization; barn owl; computational modeling; confocal microscopy; dendritic spines; hippocampus; integrate and fire neurons; n-cadherin; neural plasticity; spike time dependent plasticity; spine motility; structural plasticity; time-lapse imaging
Degree Grantor:California Institute of Technology
Division:Engineering and Applied Science
Major Option:Control and Dynamical Systems
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Schuman, Erin Margaret (advisor)
  • Quartz, Steven R. (co-advisor)
Thesis Committee:
  • Schuman, Erin Margaret (chair)
  • Quartz, Steven R. (co-chair)
  • Koch, Christof
  • Murray, Richard M.
Defense Date:25 September 2006
Author Email:shreesh (AT) cds.caltech.edu
Record Number:CaltechETD:etd-11102006-021149
Persistent URL:http://resolver.caltech.edu/CaltechETD:etd-11102006-021149
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:4496
Collection:CaltechTHESIS
Deposited By: Imported from ETD-db
Deposited On:13 Nov 2006
Last Modified:26 Dec 2012 03:09

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