Projects

Activity becomes transformed into changes at synapses that allow us to learn and retain information for hours, days, months and years. How are inputs modified by activity to accomplish this, and does it involve the physical reorganization of circuits? One mechanism may involve the production of newly made proteins, a critical process that supports long lasting information storage which is often the target of mutations in neurodevelopmental disorders with a high incidence of autism, including Fragile X Syndrome and Tuberous Sclerosis Complex. By discovering how activity is encoded in these disorders, we hope to understand what gives rise to the observed cognitive deficits and how they could be reversed.

Although the genetic code was elucidated over 60 years ago, we do not have a similar fundamental understanding of how different patterns of activity lead to changes in synaptic strength and the encoding of information. Several projects in the lab work towards addressing this basic question in neuroscience. We examine how diverse patterns of naturalistic activity give rise to functional and structural changes at synapses, and how coincident yet distinct forms of plasticity are integrated across inputs. Such mechanisms may be critical when adapting to fluctuating levels of activity over the lifetime of an organism, including in response to synapse loss as seen in Alzheimer's Disease and other neurodegenerative states.

Our software, called “SpineS”, is a semi-automatic image analysis toolbox within Matlab, aimed at improving the efficiency and quality of spine volume quantification. Using machine learning to achieve optimal segmentation of structures, our goal is to more fully capture the diversity of shapes and volumes observed in multiphoton images, both at the level of local dendritic branches and across the neuronal arbor.  SpineS is freely available to the research community on Github.

Dendritic spines are the primary sites of excitatory synapses in the brain, yet they appear on a wide range of neuronal cell types that differ in receptor expression and plasticity mechanisms. Our research aims to uncover the fundamental rules of structural plasticity across neurons - distinguishing universal principles from those specialized to particular cell types. We also seek to determine whether these plasticity paradigms are conserved across species.