Functional Analysis of Probe-Tissue Interactions Using Soft and Stiff Probes

Relevant for Research Area

A - Foundations

B - Core Technologies

The project builds on

CAPRI, BioEPIC, ProLongBrain, DeepDecode, BIG, Advanced-EDC


Dr. Maria Asplund

Dr. Tuan Leng Tay

Dr. Patrick Ruther


Major progress in flexible neurotechnology has reduced brain tissue damage during intracortical recordings. On the other hand, Si-based neural probes, fabricated using CMOS-MEMS technologies, enable the integration of large numbers of densely packed recording sites impossible with established polymer probe processes. Further, flexible PI and stiff Si probes generally differ in geometrical dimensions, implantation methods and probe fixation likely leading to differential tissue responses. To establish innovative designs for the next generation of neural tools, new approaches that combine multidisciplinary expertise and marry the best of both probe technologies require a systematic analysis of the attributed tissue response and probe-tissue interface. Currently, the large variability in probe implantation and fixation methods prohibits a direct comparison of tissue reactivity and identification of beneficial attributes of the applied materials.

Our project StiffFlex addresses these challenges by studying the tissue response to polymer and Si probes that are geometrically identical (technologies by PIs Asplund and Ruther). We will establish a sophisticated implantation procedure that is compatible with both flexible and stiff probes to enable highly reproducible insertions of single- and multi-shank probe configurations. We will systematically analyze the local and global changes in the mammalian brain using the latest single-cell RNA-sequencing (scRNAseq) and histological approaches on various cell populations (PI Tay). We furthermore take advantage of the Soft-FIB to generate precise sections containing the implanted probes once the system is installed at IMBIT. By integrating multi-parameter tissue response measurements with the long-term recording performance of the two probes types, we aim to establish the design basis for the next-generation mixed-material neural probes.