Brain Connectivity & Machine Learning

1st Serafim Rodrigues talk

Dr Serafim Rodrigues
University of Bristol, UK
A mathematical and computational paradigm to compute stability boundaries and bifurcations directly from data in closed-loop experiments
Tue June 28, 2011. 11.00am
I will present a novel paradigm that enables to track unstable states and transitions between qualitatively different dynamics from noisy experimental data. These data are recorded from real-time computer-controlled closed-loop experiments such as dynamic-clamp in electrophysiology, HILL systems in electronics and hybrid testing in mechanical engineering. This technique does not assume any underlying model nor does it rely on inverse problems, however it suitably combines dynamical systems theory and feed-back control theory. This result opens new avenues of research, allowing the possibility of implementing intelligent closed-loop machine brain interfaces that allow to efficiently control and explain both normal and pathological neuronal states.

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