Carbon Fiber Electrode Array

Type: Electrophysiology / Probes,

Keywords: Carbon Fiber Electrodes, Electrophysiology, Dopaminergic Measurements, Fast Scan Cyclic Voltammetry (FSCV)

Carbon fiber electrodes for electrophysiological or dopamingeric recordings

We have developed carbon fiber electrode arrays that can be optimized for either electrophsiology or the detection of dopamine. In addition, we have implemented tip sharpening techniques for better penetration into tissue such as nerves and ganglia. We wish to continue distributing these electrodes to existing collaborators and expand to new labs, with an overall emphasis on electrode customization per the user’s needs.

* We have developed high density carbon fiber arrays that can be used for the detection of electrical or dopaminergic activity. In addition they are minimally damanging to tissue owing to their small size
* Validated a laser cutting technique that produced electrodes of approximately 257 μm2 surface area, achieving a much larger apparent neuron recording yield than our previous carbon fiber work
* The increase in recording yield is in part due to more consistent exposure of carbon at the tip, a volumetrically compact geometry with increased surface area, and a reduction in 1 kHz impedance
* The recording site created by laser cutting may provide a stable platform for any impedance- reducing coating or treatment and result in a high recording yield
* Provides evidence to support carbon fiber arrays as a viable approach to high-density, clinically-feasible brain-machine interfaces
* With greater improvements in device manufacturing, carbon fibers electrodes may ultimately provide the means to create a stable, high density interface to the nervous system
* An additional benefit of the carbon fiber arrays is that they can left in place during tissue slicing, allowing for precise localization of their implant location
* Currently ramping up production of a new 16 channel carbon fiber array design that comes in 3mm, 6mm, and 9mm lengths designed to self-insert and target any brain region for optimized electrophysiology or dopamingeric recordings

* Animal behavioral studies requiring either acute or chronic electrophysiology or dopamine detection in the brain
* Animal studies needing acute detection of electrophysiology in the peripheral nervous system
* High density recordings (16ch at a pitch of 100 to 120 µm) of dopamine signals in pathways of the brain such as the dorsal or ventral striatum which are associated with reward and addiction behavior

* Chronically implant the array into a region of the brain associated with dopamine release and perform behavioral tasks (nose poke for rewards, narcotic self-administration, etc) to better understand dopamine kinetics

* Rats
* Mice
* Aplysia

* Low noise and high yield for electrodes optimized for electrophysiology
* High spatial resolution and low noise for the detection of dopamine in regions of the brain with heterogenous kinetics
* Ability to localize the electrode after implantation by slicing the electrodes in place with the tissue

* Welle et al. 2020, Ultra-small carbon fiber electrode recording site optimization and improved in vivo chronic recording yield, Journal of Neural Engineering 17: 026037

* Patel et al. 2020, High density carbon fiber arrays for chronic electrophysiology, fast scan cyclic voltammetry, and correlative anatomy, Journal of Neural Engineering 17:056029




Paras Patel (Assistant Research Scientist)
Cynthia Chestek (Associate Professor)


University of Michigan



Euisik Yoon (U-M Professor of Electrical Engineering and Computer Science)
György Buzsáki (Professor of Neuroscience at New York University)
Dawen Cai (Assistant Professor of Cell and Developmental Biology at U-M)
Cynthia Chestek (Associate Professor of Biomedical Engineering at U-M)
Viviana Gradinaru (Professor of Biology and Biological Engineering at California Institute of Technology)
John Seymour (Assistant Research Scientist in Electrical Engineering and Computer Science at U-M)
James Weiland (Professor of Biomedical Engineering at U-M)
Ken Wise (the William Gould Dow Distinguished University Professor Emeritus of Electrical Engineering and Computer Science at U-M)



NIH #1OT2OD024907
NINDS #UF1NS107659
NSF DBI-1707316
NINDS #U01NS094375