Relative contributions of specific activity histories vs. spontaneous processes to synaptic remodeling.
Changes in synaptic properties are widely believed to be governed by the specific activity histories experienced by synapses. However, synapses also exhibit significant changes which occur in the absence of particular activation patterns or, for that matter, any activity at all. This project, based on long-term imaging of individual synapses and chronic recordings of network activity, seeks to compare the relative contributions of specific activity histories to those of other processes to changes synapses undergo over times scales of many hours and days.
Roman Dvorkin (PhD student)
Synaptic remodeling in experimental models of Huntington’s disease
Huntington’s disease (HD) is most known for the severe motor disorders it causes. Its earliest symptoms, however – often manifesting years before severe motor symptoms develop – are cognitive deficits and neuropsychiatric disorders, which gradually deteriorate into dementia and severe behavioral problems. These early aspects of the disease have been attributed, in part, to synaptic dysfunction and loss. This project aims to examine and compare various aspects of synaptic biology and function in experimental models of this disease using proteomics, fluorescent reporters, long-term imaging and chronic electrophysiological recordings.
Vicki Hakim (PhD student)
Acute and chronic effects of neuromodulation on network function
Neuromodulators, such as dopamine and acetylcholine have enormous effects on myriad aspects of neural network function. This project seeks to examine how such neuromodulators affect aspects various forms of adaptation to external stimuli over multiple time scales in generic networks of cortical neurons, using open and closed loop recording/stimulation systems.
Liran Hazan (PhD student)
Synaptic protein catabolism
Synaptic function crucially depends on uninterrupted synthesis and degradation of synaptic proteins. While much has been learned on synaptic protein synthesis and trafficking, much less is known on the manners by which synaptic proteins are degraded. This project seeks to examine the roles of canonical catabolic pathways in the degradation of synaptic proteins using proteomics, bioinformatics, long-term imaging techniques, chronic recordings, pharmacological / molecular perturbations and immunocytochemistry.
Laurie Cohen (PhD student)
Separability, stability and persistence of potential representation schemes
The manner by which objects in the external word are represented in neuronal networks is still not understood, yet it is widely believed that such representations involve groups of neurons activated in particular spatial and/or temporal orders. This project seeks to measure the separability of potential neural representation schemes by employing a set of classification approaches, characterizing the relations between multi-electrode array (MEA) topologies and the ability to separate activity patterns invoked from different sources, and examine the invariance of such classification schemes to sampling regimes and the passage of time.
Recent studies from several labs, including our own, reveal that synapses, in addition to directed changes, also change spontaneously in an apparently stochastic manner, even in the absence of specific activity patterns, or, for that matter, any activity at all. We have recently shown that such synaptic remodeling dynamics are captured remarkably well by a simple statistical model known as the Kesten process. The abstract nature of this statistical model, however, provides little insight on the fundamental biophysical processes that might give rise to these dynamics. This project thus aims to bridge the gap between the abstract macroscopic realm and the enormously complex molecular realm by identifying potential mesoscopic biophysical processes that can give rise to such dynamics.
Aseel Shomar (M.Sc. student)
A new experimental platform for closed-loop interactions with neuronal networks
The ability to perform experiments in which input (stimulation, neuromodulation) delivered to neuronal networks is constantly tuned to the networks activity and responses to prior stimuli is essential for exposing the abilities of such networks or studying their interactions of with simulated environments. While experimental platforms designed for these purpose exists, most of these are difficult to use, depend on idiosyncratic programming interfaces, are not user friendly, depend on dedicated and expensive hardware or all of the above. In this project a new, GUI based, powerful, flexible and interactive platform is constructed which is based on generic and inexpensive hardware. Once completed, the application and its source code will be made public.
Hananel Hazan (Postdoc)