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Fang and Koppes Receive $2.2M NIH Award Leading to State-of-the-Art Electrophysiological Capabilities

ECE Assistant Professor Hui Fang (PI) and ChE Assistant Professor Ryan Koppes (co-PI), in collaboration with UCLA and Boston Children’s Hospital, received a $2.2M NIH grant for “Novel transparent, ultra-soft neuroelectrode arrays based on nanomeshing conventional electrode materials.” In this study, they propose to prove a novel electrode concept, nanomeshing conventional electrode materials, can lead to state-of-the-art electrophysiological capabilities while allowing at the same time, optical and chronic-bio- compatibilities. Besides enabling new hypothesis-driven neuroscience studies from overcoming major barriers of integrating in-vivo electrical recordings with optical approaches, the proposed research will also provide unique opportunities for next-generation therapeutic interventions via sustainable neural prosthetics.


Abstract Source: NIH

There is a growing interest to effectively combine optical approaches with electrophysiology at large scale and with great precision to fully leverage the complementary spatial and temporal resolution advantages of both techniques. It is also widely recognized that device softness and compliance are important attributes to dramatically lower tissue injury and irritation and maintain signal quality over time. Our long-term goals are (i) to converge electrophysiology with optical brain recording/stimulation seamlessly at the large scale to achieve high-spatiotemporal-resolution brain activity mapping which captures both the finest spatial intricacies of the neuronal circuit and fastest temporal dynamics of neuronal communication and (ii) to integrate electrode arrays seamlessly with the brain tissue. The objective of this R01 application, which is the first step in achieving these goals, is to develop and validate a novel neuroelectronic tool which provides state-of-the-art electrophysiological capabilities while allowing at the same time, optical and chronic-bio- compatibilities, realized critically through the optical transparency and mechanical ultra-softness of the entire MEA, along with other engineering efforts. We are very ambitious about tackling both of these two big challenges because of a unified technical concept, nanomeshing conventional electrode materials. In our prior work, we have proposed this novel electrode concept, which has led to the demonstration of transparent, flexible electrodes with high performance of sizes down to 15×15µm2, and with the ability to record single-unit spikes. In this application, we aim to prove: this nanomeshing concept can lead to 100s-electrode- scale, high-density, transparent and ultra-soft electrode arrays that simultaneously allow both the capability of (i) effectively integrating electrical recordings/stimulation with optical imaging in vivo, and (ii) chronic stability of single-unit recordings. The proof of this concept will readily enable stable, concurrent electrical/optical investigations of the brain at the mm-to-cm scale with further scalability, while also providing unique opportunities for next-generation therapeutic interventions via sustainable neural prosthetics. In three inter- related aims, we will develop and validate proof-of-concept, nanomesh-microelectrode-based, transparent, ultra-soft, high-density (NANOMESH) array with at least 256 high-performance nanomesh microelectrodes and artifact rejecting wireless data link through an interdisciplinary 3-year plan integrating innovative technological developments with basic neuroscience testing. We will benchmark our devices to industry standards in vivo, and integrate neural engineering feedback throughout the design, testing and validation phases of the project. This project leverages a vibrant and successful collaboration between material scientists, neuro-engineers, electrical engineers, and neuroscientists at Northeastern University (NU), the University of California Los Angeles (UCLA), and Boston Children’s Hospital (BCH), to translate transparent nanomesh technology into large-scale brain-mapping tools and implantable devices.

Related Departments:Chemical Engineering, Electrical & Computer Engineering