Aging in the brain involves interactions between multiple brain regions over years yet originates from electrophysiological changes in millisecond-scale firing events from micron-sized individual neurons. The spatiotemporal scales relevant to aging span many orders of magnitude and thus make it extremely challenging to study aging in the brain of live subjects. Our understanding of brain aging comes mainly from longitudinal studies with low spatiotemporal resolution (e.g., fMRI on human patients and primates over years), and cross-sectional studies comparing different subject populations due to chronic instability (e.g., single- neuron electrophysiology with invasive brain electrodes). Neither approach can span the spatial-temporal scales necessary to resolve single-neuron activities, unravel long-range functional connections of neurons across multiple brain regions, and track the evolution of neural activity during aging-related cognitive decline over extended time periods. Recently our group has demonstrated syringe-injectable mesh-like electronics as a powerful tool for stable long-term chronic tracking of the same single neurons in rodent and primate brains for ?8 months. These capabilities, which are not possible with other brain interrogation techniques, are due to the unique mechanical and structural design of the mesh-like electronics. This design encompasses a flexibility comparable to brain tissue, feature sizes on the order of axons/somata, and macroporous structure that allows interpenetration of neurons through the electronics produce minimal glial scarring that would otherwise insulate neurons from the probe and eliminate motion of probe relative to neurons during chronic experiments. I propose to carry out in-vivo longitudinal studies of natural and pathological aging in mice with stable single- neuron-level resolution. In the mentored phase of this award, I will focus on developing and using syringe- injectable mesh electronics with high multiplexity and appropriate distribution of recording electrodes to chronically track the electrophysiological evolution of individual neurons and corresponding neural circuitry from multiple key brain regions simultaneously, with a focus on alterations in neural connectivity and plasticity associated with memory retention deficit and learning impairment. In the independent phase of this award, I will focus on further development of this technology through incorporation of simultaneous electrical stimulation and recording of neural activity, to explore potential strategies for ameliorating deleterious changes in brain circuitry associated with memory and learning due to aging. The proposed research projects will demonstrate mesh electronics as a transformative tool for addressing the real-world medical challenges of aging, and enable me to acquire the needed knowledge and skills beyond my training in the physical sciences for successful transition to an independent and highly multidisciplinary research career.

Public Health Relevance

Syringe-injectable mesh electronics with chronically stable neural interface and single-neuron recording resolution provides a unique tool to expand our knowledge of the neurological basis of age-related cognitive decline by tracking the same individual neurons and the neural circuits they comprise in longitudinal studies spanning the entire aging process. In addition, injectable mesh electronics has the potential to be used as an `electroceutical' that can be delivered into the brain via syringe to modulate brain activity and ameliorate deleterious cognitive changes in brain circuitry due to aging.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Career Transition Award (K99)
Project #
5K99AG056636-02
Application #
9527721
Study Section
Neuroscience of Aging Review Committee (NIA)
Program Officer
Wise, Bradley C
Project Start
2017-07-15
Project End
2018-09-29
Budget Start
2018-07-01
Budget End
2018-09-29
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Harvard University
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
082359691
City
Cambridge
State
MA
Country
United States
Zip Code
Hong, Guosong; Fu, Tian-Ming; Qiao, Mu et al. (2018) A method for single-neuron chronic recording from the retina in awake mice. Science 360:1447-1451
Hong, Guosong; Viveros, Robert D; Zwang, Theodore J et al. (2018) Tissue-like Neural Probes for Understanding and Modulating the Brain. Biochemistry 57:3995-4004
Hong, Guosong; Yang, Xiao; Zhou, Tao et al. (2018) Mesh electronics: a new paradigm for tissue-like brain probes. Curr Opin Neurobiol 50:33-41
Dai, Xiaochuan; Hong, Guosong; Gao, Teng et al. (2018) Mesh Nanoelectronics: Seamless Integration of Electronics with Tissues. Acc Chem Res 51:309-318
Fu, Tian-Ming; Hong, Guosong; Viveros, Robert D et al. (2017) Highly scalable multichannel mesh electronics for stable chronic brain electrophysiology. Proc Natl Acad Sci U S A 114:E10046-E10055