Seminar Title: Actively Multiplexed µECoG Array Based on Thin-Film Electronics for High-Resolution Brain Mapping
Speaker: Sebastian Haesler, PhD.
Director, NeuroElectronics Research Flanders (NERF)
Associate Professor of Neuroscience, KU Leuven
Abstract: Electrode arrays are widely used in neuroscience research and the clinic to record electrical activity from the surface of the brain. However, current passive electrocorticography (ECoG) technologies have limited spatial resolution and/or cortex coverage. The fact that each electrode must be individually wired is a major factor restricting the expansion of electrode-counts and -densities. In my presentation I will share our recent work on an active uECoG platform that circumvents these challenges. The 1x1-cm2 uECoG array is based on a metaloxide thin-film transistor technology on a 15-um flexible foil and is coupled to a 1.25x1.25-mm2 CMOS readout integrated circuit (ROIC). Thanks to 256:16 time-division multiplexing achieved in the electrode array, only 16 multiplexed channels are required to acquire signals from all electrodes simultaneously. The system has been validated in-vivo in anesthetized mice, recording spontaneous activity and somatosensory-evoked potentials. By combining TFT multiplexing with anewly designed ROIC, we can achieve >10x less noise than existing active arrays and obtain >2x effective channel area reduction in the ROIC, while maintaining comparable electrical performance over state-of-the-art ECoG readouts.
About the Speaker: Sebastian Haesler is group leader at NeuroElectronics Research Flanders (NERF) and an Associate Professor at the Department of Neuroscience of KU Leuven. Following his PhD at the Max-Planck-Institute for Molecular Genetics (Berlin, Germany) and postdoctoral work at the Center for Brain Science at Harvard University (Cambridge, USA), he moved to Leuven, Belgium to start his own lab at NERF. Since 2015 he also serves as Director of the institute. His lab combines systems neuroscience research and neuroengineering to reveal mechanistic principles of brain function and to derive new technologies which will ultimately find their use in research and clinical applications.