Special Computational Physics Seminar - Professor Andrew Sornborger, UC Davis
Title: "Time Translational Invariance, the Propagation of Graded Information and the Structure of Information Coding in Neural Circuits"
Abstract: Neural oscillations can enhance feature recognition, modulate interactions between neurons, and improve learning and memory. Coherent spiking can give rise to windows in time during which information transfer can be enhanced. Unanswered questions are: 1) What is the transfer mechanism? And 2) how well can a transfer be executed? To answer these questions, I will present a mechanism by which a graded current amplitude may be exactly propagated from one neuronal population to another. Transfer is pulse-gated, allowing information to be dynamically routed through a neural circuit with fixed connectivity. Thus, it may used as a building block for fast, complex information processing in neural circuits. Then, I will show how the mechanism naturally provides a framework where neural information coding and processing can be considered as a product of linear maps under the active control of a pulse generator. Finally, I will show examples of neural circuits where distinct control and processing components combine to form the basis for the binding, propagation, and processing of dynamically routed information.