1. High density carbon fiber arrays for chronic electrophysiology, fast scan cyclic voltammetry, and correlative anatomy
- Author
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Ciara M Caldwell, Pavlo Popov, Daniel Egert, Cynthia A. Chestek, Elissa J. Welle, Jeffrey R. Pettibone, Paras R. Patel, Joshua D. Berke, Jill B Becker, Douglas H. Roossien, and Dawen Cai
- Subjects
Materials science ,0206 medical engineering ,Biomedical Engineering ,Fast-scan cyclic voltammetry ,Insulator (electricity) ,02 engineering and technology ,Dielectric ,engineering.material ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,chemistry.chemical_compound ,0302 clinical medicine ,Coating ,Parylene ,Carbon Fiber ,Animals ,Electrodes ,Laser ablation ,020601 biomedical engineering ,Carbon ,Electrophysiological Phenomena ,Rats ,Electrophysiology ,chemistry ,Electrode ,engineering ,Microelectrodes ,030217 neurology & neurosurgery ,Biomedical engineering - Abstract
Objective. Multimodal measurements at the neuronal level allow for detailed insight into local circuit function. However, most behavioral studies focus on one or two modalities and are generally limited by the available technology. Approach. Here, we show a combined approach of electrophysiology recordings, chemical sensing, and histological localization of the electrode tips within tissue. The key enabling technology is the underlying use of carbon fiber electrodes, which are small, electrically conductive, and sensitive to dopamine. The carbon fibers were functionalized by coating with Parylene C, a thin insulator with a high dielectric constant, coupled with selective re-exposure of the carbon surface using laser ablation. Main results. We demonstrate the use of this technology by implanting 16 channel arrays in the rat nucleus accumbens. Chronic electrophysiology and dopamine signals were detected 1 month post implant. Additionally, electrodes were left in the tissue, sliced in place during histology, and showed minimal tissue damage. Significance. Our results validate our new technology and methods, which will enable a more comprehensive circuit level understanding of the brain.
- Published
- 2020