Softening Intracortical Recording Devices for Improved Biomechanical Interactions at the Brain-Device Interface

Intracortical recording devices can be implanted in brain tissue to record signals from neural populations making them important components of brain-machine interfaces. However, they are limited in clinical implementation due to their inability to reliably record neural signals over time, likely in part due to the effects of chronic neuroinflammation. While the causes of neuroinflammation are multifaceted, studies suggest that mechanical mismatch between stiff device materials and the soft brain tissue may result in mechanical strain that affect adjacent tissue. This hypothesis has driven the investigation of soft materials as substrates for neural interfaces. In this dissertation work we demonstrate: (1) positive correlation between device stiffness and severity of the neuroinflammatory response via a meta-analysis of existing literature, (2) the use of finite element analysis and ultrasound-based elastography to show that soft materials elicit decreased strain on surrounding tissue as compared to stiff materials, and (3) chronic implementation of softening, functional intracortical devices fabricated from a unique shape memory polymer substrate.