Closed-Loop Technologies

Recent hard- and software advances make it possible to integrate rapid online data analysis, adaptive sampling techniques, and computational modeling into the design of neuroscience experiments. The broad range of such approaches at the Bernstein Center Munich – from dynamic clamp and iso-response methods to virtual reality (see also Bernstein Virtual Reality Facility) – makes it possible to discuss methodological issues and transfer expert knowledge between different levels of investigation. The primary goal is to improve the design of experiments, addressing issues such as optimal spatio/temporal averaging of data and the stability of experimental feedback loops, which, in turn, may lead to new insight about closed-loop situations in neurobiological and artificial systems, the interaction of visual processing and eye movements, and course control.

Related Projects

A4: Monitoring neuronal activity with printed devices (B. Wolfrum)

B-T6: Influence of sensory conditions on the hippocampal population code for space (K. Thurley, C. Leibold, A. Sirota)

D3: Cognition and Neural Plasticity (A. Sirota)