Progress in the Field of Micro-Electrocorticography

Mehdi Shokoueinejad^{1

2}, Dong-Wook Park^{3

4}, Yei Hwan Jung⁵, Sarah K Brodnick⁶, Joseph Novello⁷, Aaron Dingle⁸, Kyle I Swanson⁹, Dong-Hyun Baek¹⁰, Aaron J Suminski^{11

12}, Wendell B Lake¹³, Zhenqiang Ma¹⁴, Justin Williams^{15

16}

Affiliations

¹ Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. mehdi.snm@bme.wisc.edu.
² Department of Neurosurgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA. mehdi.snm@bme.wisc.edu.
³ Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. dwpark31@uos.ac.kr.
⁴ School of Electrical and Computer Engineering, University of Seoul, Seoul 02504, South Korea. dwpark31@uos.ac.kr.
⁵ Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. yhjung89@gmail.com.
⁶ Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. skkorinek@wisc.edu.
⁷ Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. novello@wisc.edu.
⁸ Division of Plastic and Reconstructive Surgery, Department of Surgery, University of Wisconsin-Madison, Madison, WI 53792, USA. dingle@surgery.wisc.edu.
⁹ Department of Neurosurgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA. kiswanson@gmail.com.
¹⁰ Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. wpvmqor@gmail.com.
¹¹ Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. suminski@neurosurgery.wisc.edu.
¹² Department of Neurosurgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA. suminski@neurosurgery.wisc.edu.
¹³ Department of Neurosurgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA. lake@neurosurgery.wisc.edu.
¹⁴ Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. mazq@engr.wisc.edu.
¹⁵ Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. jwilliams@engr.wisc.edu.
¹⁶ Department of Neurosurgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA. jwilliams@engr.wisc.edu.

PMID: 30658503
PMCID: PMC6356841
DOI: 10.3390/mi10010062

Review

Progress in the Field of Micro-Electrocorticography

Mehdi Shokoueinejad et al. Micromachines (Basel). 2019.

. 2019 Jan 17;10(1):62.

doi: 10.3390/mi10010062.

Authors

Affiliations

¹ Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. mehdi.snm@bme.wisc.edu.
² Department of Neurosurgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA. mehdi.snm@bme.wisc.edu.
³ Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. dwpark31@uos.ac.kr.
⁴ School of Electrical and Computer Engineering, University of Seoul, Seoul 02504, South Korea. dwpark31@uos.ac.kr.
⁵ Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. yhjung89@gmail.com.
⁶ Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. skkorinek@wisc.edu.
⁷ Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. novello@wisc.edu.
⁸ Division of Plastic and Reconstructive Surgery, Department of Surgery, University of Wisconsin-Madison, Madison, WI 53792, USA. dingle@surgery.wisc.edu.
⁹ Department of Neurosurgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA. kiswanson@gmail.com.
¹⁰ Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. wpvmqor@gmail.com.
¹¹ Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. suminski@neurosurgery.wisc.edu.
¹² Department of Neurosurgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA. suminski@neurosurgery.wisc.edu.
¹³ Department of Neurosurgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA. lake@neurosurgery.wisc.edu.
¹⁴ Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. mazq@engr.wisc.edu.
¹⁵ Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. jwilliams@engr.wisc.edu.
¹⁶ Department of Neurosurgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA. jwilliams@engr.wisc.edu.

PMID: 30658503
PMCID: PMC6356841
DOI: 10.3390/mi10010062

Abstract

Since the 1940s electrocorticography (ECoG) devices and, more recently, in the last decade, micro-electrocorticography (µECoG) cortical electrode arrays were used for a wide set of experimental and clinical applications, such as epilepsy localization and brain⁻computer interface (BCI) technologies. Miniaturized implantable µECoG devices have the advantage of providing greater-density neural signal acquisition and stimulation capabilities in a minimally invasive fashion. An increased spatial resolution of the µECoG array will be useful for greater specificity diagnosis and treatment of neuronal diseases and the advancement of basic neuroscience and BCI research. In this review, recent achievements of ECoG and µECoG are discussed. The electrode configurations and varying material choices used to design µECoG arrays are discussed, including advantages and disadvantages of µECoG technology compared to electroencephalography (EEG), ECoG, and intracortical electrode arrays. Electrode materials that are the primary focus include platinum, iridium oxide, poly(3,4-ethylenedioxythiophene) (PEDOT), indium tin oxide (ITO), and graphene. We discuss the biological immune response to µECoG devices compared to other electrode array types, the role of µECoG in clinical pathology, and brain⁻computer interface technology. The information presented in this review will be helpful to understand the current status, organize available knowledge, and guide future clinical and research applications of µECoG technologies.

Keywords: ECoG; brain–computer interface; electrocorticography; electrophysiology; graphene; in vivo imaging; micro-electrocorticography; neural electrode array; neural interfaces; tissue response; µECoG.

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Conflict of interest statement

Multiple authors have financial or intellectual property interests in technologies that are described in this review or in the more general area of neuroengineering. J.C.W., D.-W.P., M.S., and Z.M. all have patents on technology described in this review. J.C.W. has an equity interest in NeuroOne Medical (Minnetonka, MN) and NeuroNexus (Ann Arbor, MI), companies that manufacture microfabricated electrode arrays for research and clinical applications.

Figures

**Figure 1**
(a) Picture of a clinical electrocorticography (ECoG) grid underneath a micro-ECoG (μECoG) array. Side-by-side comparison of the regular macro-ECoG and μECoG arrays showing difference in electrode spacing. (b) X-ray image showing the implanted ECoG and μECoG electrode. (c) Coherence analysis to characterize independent neural signals recorded from both macro-ECoG and μECoG. This suggests μECoG offers higher spatial resolution for neural signal recording. (a) Photo was taken at Neural Interfaces Research (NITRO) lab at University of Wisconsin (UW) Madison; (b,c) reprinted with permission from Reference [6].

**Figure 2**
Spatial resolution versus invasiveness for various types of neural electrodes. Micro-ECoG has a balanced spatial resolution and invasiveness.

**Figure 3**
Anodic stimulation via indium tin oxide micro-ECoG. Neural activity captured via fluorescent voltage sensitive dye. (A) The white circle (a) indicates a clear electrode used for stimulation. Activation profiles captured after delivering single pulses of current intensity of 0.5, 0.3, and 0.25 mA. (B) Duplicate of experiment in (A) with a pulse train of five pulses at 500 Hz. (C) Comparison of spatial activation spreading due to different stimulation settings. The spatial extent of activity was evaluated by the number of pixels above threshold. A, anterior; L, lateral. Scale bar, 1.0 mm. Reprinted with permission from Reference [50].

**Figure 4**
The representative equivalent model of a µECoG electrode. WE, working electrode; CE, counter electrode; Z_CPE, constant phase element; Z_W, Warburg impedance; R_CT, charge transfer resistance; R_S, solution resistance.

**Figure 5**
(a) Illustration depicting experimental ensemble combining optical stimulation with µECoG in a mouse model. (b) Optical illumination and stimulation spatially control over the mouse brain and µECoG via an optical fiber. (c) Spatial mapping of local field potentials obtained from a graphene µECoG throughout an optically evoked potential on the cortex of a channel rhodopsin positive mouse; x-scale bars represent 50 ms, y-scale bars represent 100 μV. (d) Post-mortem control depicting photo-electric artefact generated during blue-light optical stimulation; x-scale bar, 50 ms; y-scale bars, 100 μV. Reprinted with permission from Reference [44].

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Progress in the Field of Micro-Electrocorticography

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Progress in the Field of Micro-Electrocorticography

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