Upinder Bhalla

Upinder Bhalla
Neurobiology, Computational neuroscience and systems biology, National Centre for Biological Sciences
Bangalore, India

Speaker of Workshop 2

Will talk about: Synaptic learning rules from multiscale neuronal signaling

Bio sketch:

I was interested in physics and computers through school and college, but the biology undergraduate courses at Cambridge captivated me and I decided to switch fields for my PhD at Caltech. Among the most inspiring moments of my bachelor's courses were the realization that bacteriophage life-cycles could actually be thought of as hacked- together living programs, and the glimpse of computation happening in the brain. I took these interests to my PhD, which was on an experimental and computational study of the rat olfactory system. My post-doc research at Mount Sinai was also serendipitous, starting with the idea that perhaps molecular interactions in the neuron could bbe modeled computationally, and eventually leading into one of the early kinetic models of signaling pathways in memory storage. Since 1996 I have been at the National Centre for Biological Sciences in Bangalore, and I have continued to pursue both experiments and models in my research into neural computation at levels ranging from single molecules up to the entire brain.

Talk abstract:

The synapse is at the intersection of many levels of neuronal function, including network, biophysical, molecular and genetic. Learning rules are an attempt to capture these interactions in a concise mathematical form. The complexity of these interactions means that learning rules are difficult to formulate with sufficient generality.

We have approached this problem from the systems viewpoint, by explicitly considering a diverse range of biological processes that contribute to synaptic plasticity. We are assembling a framework of multiscale interactions within which to analyze synaptic plasticity. This includes models of key signaling pathways, receptor traffic, cellular biophysics, network interactions and dendritic protein synthesis. All these models have been developed as biologically motivated, mechanistic formulations at the level of chemical kinetics, molecular transport, and electrophysiology. In this talk I will describe the addition of mRNA synthesis components to this framework. This closes an important feedback cycle involving cellular activity, genetic control, and dendritic protein synthesis. It also constitutes a key mechanism by which the activity of thousands of synapses is coordinated by the soma and nucleus. I will discuss how these combined, multiscale interactions contribute to synaptic learning rules.