Research Fellows Directory
Professor Rodolphe Sepulchre
University of Cambridge
Neuronal circuits pose fascinating challenges for the control engineer. On the one hand, their modeling principles strongly resemble those of artificial electrical circuits, suggesting that the mathematical tools of systems and control theory can contribute to their understanding. On the other hand, they exhibit adaptation and robustness properties rarely matched in artificial circuits, suggesting that the feedback principles that regulate artificial and natural behaviors are not identical. Our research aims at developing novel analysis tools in control theory to advance the understanding of the modulation and robustness properties of neuronal circuits. We put a particular emphasis on circuits that combine positive and negative feedback loops at every scale, a feedback architecture that seems ubiquitous in nature and not present in artificial systems.
Such architectures require novel analysis and design tools. Those tools will assist the experimental work of neurophysiologists by providing novel predictions about neuromodulation principles. Likewise, they suggest novel neuromorphic principles for the design of robust and tunable artificial devices.