Plasticity and computing in the brain: Towards remedying the oversimplifications
Abstract:
In this talk, the following (subset of) oversimplifications in assessing information processing and plasticity in the brain will be discussed. Some approaches to remedy these oversimplifications will be presented with illustrative examples.
Oversimplification #1. Neurons are simple algebraic summation units with a threshold nonlinearity.
Oversimplification #2. Neural circuits are made of repeating homogeneous computational units.
Oversimplification #3. Learning and memory in biological systems is accomplished exclusively through synaptic changes.
Oversimplification #4. There is a unique solution to how biological learning is accomplished, and our goal is to find that solution.
Oversimplification #5. Glial cells are glue.
Brief Bio:
Rishi obtained his Ph.D. from the Department of Electrical Engineering at the Indian Institute of Science, Bangalore (Advisor: Prof. Y. V. Venkatesh). After that, he held two postdoctoral positions, the first at the National Centre for Biological Sciences, Bangalore (Advisor: Prof. Sumantra Chattarji), and the second at the University of Texas at Austin (Advisor: Prof. Daniel Johnston). He returned to the Indian Institute of Science in July 2009. He is currently a Professor at the Molecular Biophysics Unit of the Institute.
The primary focus of research in this laboratory is on experimental and theoretical aspects of information processing in single neurons and their networks. His laboratory addresses questions in this focus area using a variety of electrophysiological, imaging, and computational techniques.
Recording available on kcnhub youtube channel