B.I.O.N.I.C. Lab

Bio-Integrating Optoelectric Neural Interface Cybernetics Lab
@ University of Pittsburgh, Department of Bioengineering

The goal of the lab is to enable and conduct leading-edge research at the frontier of neuroscience and neurobiology by developing and using novel engineered technologies and tools. This unique research facility is focused on developing trainees to blend high-quality hypothesis-driven scientific inquiry and problem solving engineering design skills. Aside from technical training, this lab’s structure is aimed at refining individual’s critical thinking skills and project management skills and prepares next-generation leaders in Neural Engineering and fusing Science & Engineering.


Our lab employs a highly multidisciplinary approach to understand interactions at micro-scale neural interfaces and develop next-generation Neural Technologies that attenuate or reverse negative tissue interactions. In order to elucidate real-time long-term cellular and molecular tissue interactions to chronically implanted medical devices, we leverage principles in molecular and cellular neurobiology, electrical engineering, mechanical engineering, computer science, physics, biochemistry, material science, optics, and biomaterials.

Specifically, we employ functional in vivo two-photon imaging, functional in vivo electrophysiology (primarily in visual and somatosensory cortex), electrochemical impedance spectroscopy, post-mortem immunohistochemistry, intrinsic imaging, cyclic voltammetry, transgenic & AAV, silicon & carbon microelectrodes, polymer devices, electrical and optical stimulation techniques, and biological and pharmaceutical intervention strategies. (see details)

Left: In vivo two-photon movie of GCaMP6f in visual cortex. Blue square indicates duration of visual stimulation into the eye (click for movie).

Bionics is the application of biological methods and systems found in nature to the study and design of engineering systems and modern technology. Our goal is to understand molecular, cellular, and structural biology, so that we can leverage these natural tools to engineer microscale neural interface technologies.