11/04/2025
By Danielle Fretwell
The Francis College of Engineering, Department of Mechanical Engineering, invites you to attend a Doctoral Dissertation defense by Dongyang Yi on: "Accurate and Buckling-Free Implantation of Microelectrode Arrays as Brain-Machine Interfaces."
Candidate Name: Dongyang Yi
Degree: Doctoral
Defense Date: Friday, November 14, 2025
Time: 9 - 11:30 a.m.
Location: Southwick 240
Committee:
- Advisor: Lei Chen, Assistant Professor, Department of Mechanical and Industrial Engineering, UMass Lowell
- Lei Chen (University of Massachusetts Lowell), Assistant Professor, Department of Mechanical and Industrial Engineering
- Walfre Franco (University of Massachusetts Lowell), Chair/Associate Professor, Department of Biomedical Engineering
- Scott Stapleton (University of Massachusetts Lowell), Professor, Department of Mechanical and Industrial Engineering
- Bendon Watson (University of Michigan), Assistant Professor, Department of Psychiatry
Abstract:
High temporal resolution electrophysiological recordings using implantable microelectrode arrays (MEAs) are essential for understanding neural activity at the single-neuron level, but broad implantation across multiple brain regions remains constrained by the labor-intensive nature of manual implantation and the mechanical instability of ultra-small and flexible electrodes. The challenges associated with large-scale MEA implantation include the inability to efficiently implant multiple devices in a reproducible manner and the tendency of minimally invasive electrodes to buckle against meningeal layers during insertion. This dissertation proposal addresses these issues by integrating engineering advancements and mechanistic investigations to improve the efficiency, precision, and reliability of neural probe implantations. The first component of this work involves the development of a 3D-printed headcap system designed to streamline multi-region electrode implantations by enabling pre-digitally determined implantation locations tailored to specific experimental needs. This system significantly reduces the reliance on manual stereotaxic alignment by incorporating a preassembled support framework that allows for precise and repeatable electrode placement while minimizing surgical time and improving consistency. Beyond procedural advancements, this dissertation also explores the mechanical properties governing microwire electrode buckling, a key limitation during insertion. A systematic study is conducted to examine the influence of microwire geometry, including variations in tip profile, diameter, and material properties, on the critical buckling load. This investigation employs a multi-layer brain-mimicking phantom replicating the dura-pia-brain tissue properties, enabling controlled experiments to quantify insertion mechanics and inform predictive models for electrode stability. Additionally, the work extends to evaluating the dynamic effects of ultrasonic vibration-assisted insertion, a promising technique for improving penetration through biological membranes. Although preliminary studies suggest that ultrasonic vibration enhances buckling resistance, the underlying mechanisms remain poorly understood. This dissertation proposal systematically examines how vibration-generated forces interact with electrode mechanics to influence insertion stability, penetration efficiency, and tissue response. By performing controlled insertions against rigid substrates and brain-mimicking phantoms, the study quantifies the impact of vibration frequency and amplitude on buckling resistance, offering insights into its potential application for dura mater penetration and next-generation flexible neural interfaces. Through the integration of novel surgical platforms, experimental biomechanics, and theoretical modeling, this research contributes to the advancement of scalable, minimally invasive, and mechanically stable neural probe implantation strategies, ultimately improving the feasibility of large-scale electrophysiological recordings for neuroscience research.