Journal
NATURE MATERIALS
Volume 19, Issue 6, Pages 679-+Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41563-020-0638-3
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Funding
- Columbia University, School of Engineering and Applied Science
- Columbia University Medical Center, Department of Neurology
- National Science Foundation [ECCS-1542081]
- Human Frontiers Postdoctoral Fellowship Program
- NIH [1U01NS108923-01]
- NSF CAREER award [1944415]
- CURE Taking Flight Award
- Columbia School of Engineering
- Columbia University Medical Center, Institute for Genomic Medicine
- Directorate For Engineering
- Div Of Electrical, Commun & Cyber Sys [1944415] Funding Source: National Science Foundation
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Bioelectronic devices must be fast and sensitive to interact with the rapid, low-amplitude signals generated by neural tissue. They should also be biocompatible and soft, and should exhibit long-term stability in physiologic environments. Here, we develop an enhancement-mode, internal ion-gated organic electrochemical transistor (e-IGT) based on a reversible redox reaction and hydrated ion reservoirs within the conducting polymer channel, which enable long-term stable operation and shortened ion transit time. E-IGT transient responses depend on hole rather than ion mobility, and combine with high transconductance to result in a gain-bandwidth product that is several orders of magnitude above that of other ion-based transistors. We used these transistors to acquire a wide range of electrophysiological signals, including in vivo recording of neural action potentials, and to create soft, biocompatible, long-term implantable neural processing units for the real-time detection of epileptic discharges. E-IGTs offer a safe, reliable and high-performance building block for chronically implanted bioelectronics, with a spatiotemporal resolution at the scale of individual neurons. Internal ion-gated organic electrochemical transistors operating in enhancement mode are shown to record electrophysiological signals in vivo, with a speed and sensitivity that enable the detection of action potentials from individual neurons.
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