Neurotechnology for real-time experiments

In the era of large-scale recordings, the experimenter’s intimate, moment-to-moment interaction with the neural system is often replaced by the hope that post hoc “big data” analysis will answer systems-level questions. The long delay between data collection and analysis is a major bottleneck to neuroscientific progress. We develop sample-efficient, model-based methods for data collection, online analysis, and control that leverage prior knowledge to form a tighter loop between experimentalists and the neural systems they study and perturb.

We advance real-time closed-loop tools for next-generation neuroscience experiments and clinical devices.