Research: Applied Engineering

When we think of brains, we think of neurons. Non-neuronal cells, however, make up more than ten times the population of neurons in the brain. Our research aims to reveal the implications of this huge disparity by determining the principles that govern the roles of non-neuronal brain cells. To date, neural computation remains studied as a purely neuronal process, but that is like trying to solve a puzzle with 10% of the pieces. It will be necessarily insufficient for understanding circuit-level function and dysfunction. Recent results highlight that understanding the role of non-neuronal cells in slowly regulating neural activities could revolutionize our understanding of neural network activity and neurocomputation in neurodegenerative diseases and brain injuries.


The projects in my lab explore the three main thrusts:

1) Understanding the biology and material science of bi-directional communication (recording and stimulation) between brain and neurotechnologies, in order to guide intelligent-design (data driven) of more efficacious and longer lasting neural interfaces.

2) Elucidating the role of non-neuronal cells in neurodegeneration and neuroregeneration in brain injuries and neurodegenerative diseases. (Multiple Sclerosis, Alzheimer's, Autism)

3) Manipulating non-neuronal cells to influence the function of neuronal network activity.

See our recent Webinar

Therefore, our lab focuses on elucidating biological structures and biochemical pathways that control physiological function and bidirectional communication between the nervous system and neural interface technology, especially hidden, latent signals (glia, neurovascular coupling, LTP/LDP). We then apply these newly discovered constraints and possibilities into designing novel technologies and treat neurological conditions.

In order to elucidate real-time long-term cellular and molecular tissue interactions to chronically implanted medical devices, we employ in vivo functional electrophysiology, two-photon microscopy, biomaterials, and electrical and optical stimulation techniques. These technologies allow us to advance our understanding of the brain and brain interfaces, as well as create new avenues for diagnosis and treatment of brain pathologies. Ultimately, the goal is to understand how neuronal and non-neuronal cells are integrated in neurocomputation, and understand how to devise targeted intervention strategies for specific neurodegenerative diseases and brain injuries.

Current Active Research Areas include (but not limited to):

1) Understanding Neurostimulation induced neuronal and non-neuronal activity (Writing into the brain)

2) Exploring the role of Oligodendrocytes and progenitors in brain injuries and neurodegenerative diseases

3) Role of Blood-Brain Barrier structures on Neural Interface

4) Cybernetic evaluation of Neuronal and Non-neuronal circuitry and regulation (Reading from the brain)

5) Novel Neural Interface Technology

6) Elucidation of biochemical pathways governing the foreign body response to brain implants

7) Comprehensive elucidation of Neural Interface failure modes for next generation device design


Funding

NIH NIA R03AG072218 (1/2022-12/2023)

NIH NINDS R44 NS105500 (11/2020-10/2022)

NIH NINDS R01NS115707 (9/2020-6/2025)

NSF CAREER 194906 (07/2020-07/2025)

NIH NINDS R01NS105691 (12/2019-12/2024)

NIH NINDS R01NS094396 (09/2015-08/2021)

NIH NIBIB R21EB028055 (07/2019-04/2021 )

NIH NINDS R21NS108098 (08/2018-07/2020)

DARPA NESD DARPA-BAA-16-09-NESD-FP-001 (05/17—07/19)

NIN NINDS R01NS089688 (07/2015-06/2020)

NIH NINDS R01NS062019 (07/2014-06/2019)

Cybernetics is defined as the transdisciplinary approach for exploring regulatory system, their structures, constraints, and possibilities, particularly from biology and man-made technology. Our lab takes on a transdisciplinary approach for exploring glial, vascular, and neural regulatory systems for functional neural network activity in normal, injured, and disease brains. By understanding the structure and function of each regulatory component, it becomes possible to identify constraints of the system, and more importantly, possibilities for treatments and cures.