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JOURNAL OF MICROELECTROMECHANICAL SYSTEMS, VOL. 29, NO. 5, OCTOBER 2020

A 512-Channel Multi-Layer Polymer-Based
Neural Probe Array
Kee Scholten , Member, IEEE, Christopher E. Larson , Member, IEEE, Huijing Xu, Member, IEEE,
Dong Song , Senior Member, IEEE, and Ellis Meng , Fellow, IEEE

Abstract— We present for the first time the design, fabrication,and preliminary bench-top characterization of a high-density,polymer-based penetrating microelectrode array, developed forchronic, large-scale recording in the cortices and hippocampiof behaving rats. We present two architectures for these targeted brain regions, both featuring 512 Pt recording electrodes
patterned front-and-back on micromachined eight-shank arraysof thin-film Parylene C. These devices represent an orderof magnitude improvement in both number and density ofrecording electrodes compared with prior work on polymerbased microelectrode arrays. We present enabling advances inpolymer micro-machining related to lithographic resolution anda new method for back-side patterning of electrodes. In vitro
electrochemical data verifies suitable electrode function andsurface properties. Finally, we describe next steps toward theimplementation of these arrays in chronic, large-scale recording
studies in free-moving animal models.
[2020-0109]
Index Terms— Microelectrode array, brain machine interfaces,neural probe, Parylene, bioMEMS.

I. I NTRODUCTIONILICON microelectrode arrays (MEAs) featuring
hundreds to thousands of recording sites represent thestate-of-the-art in penetrating brain-machine interfaces [1], [2]however the significant mismatch between the mechanicalproperties of stiff silicon and soft brain tissue (Young’s modulus > 150 GPa and ∼1 kPa, respectively) presents a tremendous obstacle for chronic recording. Strain-induced tissue
damage at the tissue-implant interface can occur from normal
micromotion of the brain, exacerbating the chronic immune
response and leading to astrogliosis, scar encapsulation, neuronal migration and even neuronal death [3]–[5]. In both formal and anecdotal accounts, silicon MEAs are often associatedwith a drop in recording performance and prominent immune
response following 2-4 weeks post implantation [6]–[9].
Polymer-based MEAs have drawn increasing interest as apossible solution. Polymer MEAs can be up to 100× softer
than their silicon counterparts and offer additional benefits likeS

Manuscript received April 30, 2020; accepted May 24, 2020. Date of
publication June 11, 2020; date of current version October 7, 2020. This
work was supported in part by the National Institutes of Health through the
BRAIN Initiative under Award U01 NS099703 and in part by the Universityof Southern California Provost Fellowship. Subject Editor R. Sochol.
(Corresponding author: Ellis Meng.)
The authors are with the Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089-1111 USA (e-mail:ellis.meng@usc.edu).
Color versions of one or more of the figures in this article are available
online at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/JMEMS.2020.2999550

optical transparency, flexibility, and material biocompatibility.
However, polymer MEAs have lagged far behind silicon
devices in terms of electrode density and count, typicallyfeaturing just tens of electrodes across an array. Recent
breakthroughs have demonstrated the first large-scale polymer
MEAs, with high resolution micromachining of solvent-castpolymers (SU-8, polyimide) [10]–[12]. However, even thesedevices are limited to just 32 electrodes per penetratingshank, compared to hundreds for the state-of-the-art in silicon. Improvements in microlithographic processes on polymer
materials is required to achieve the resolution required to close
this gap.
Here we present a new approach for high-channel countpolymer MEAs, a dual-sided array built using vapor deposited
Parylene C. Our Parylene MEAs (Fig. 1) possess the highest
electrode count per probe (64) of any polymer neural probe
described to date. In this work we describe the design, fabrication, and initial testing of prototypes intended for both corticaland hippocampal chronic recording in rat models.
II. M ETHODS
A. Design
The overall design of the 512-channel Parylene C MEA
builds upon prior Parylene MEA architectures [13]–[15] andconsists of 8 polymer shanks, each supporting 64 platinum
electrodes (32 each on the front and back). Two layouts arepresented here (Fig. 2), one with 2 mm long shanks for cortical
recording in rat models, and one with 5.5 mm long shanks
for hippocampal recording. Shanks are tapered from 230 μm
down to 140 μm wide at the tip. The 8 shanks connect into asingle 12 mm long ribbon cable which terminates in a seriesof contact pads for connection to an electrode interface board
by way of a zero-insertion force (ZIF) connector.
Each electrode is 30 μm in diameter, with the outer 5 μm
insulated with Parylene C, such that the exposed electrode is
20 μm in diameter. Each electrode is individually addressedby a 2 μm wide platinum trace patterned on the same layer
as the corresponding electrode. No vias were used for theconstruction of these devices. Traces are spaced just 2 μm
apart to minimize shank width.
The devices are fabricated using multiple layers of vapor
deposited Parylene C and patterned thin-film platinum. Thebase layer is 2 μm of Parylene C, followed by the bottom
metal layer (containing back electrodes, traces and contact

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SCHOLTEN et al.: 512-CHANNEL MULTI-LAYER POLYMER-BASED NEURAL PROBE ARRAY1055

Fig. 3.
Cross-section view of polymer MEA fabrication process flow:(1) Parylene was deposited on Al release layer. (2) O2 etch created openings
for backside electrodes. (3) Electrodes, traces and contacts were deposited andpatterned. (4) Parylene was deposited followed by a second patterned metal
layer (5) Frontside electrodes were etched open with O2 plasma. (6) Al layer
was dissolved and devices released.

B. Fabrication

Fig. 1. Photograph of a large-scale, polymer-based brain-machine interface
designed to record from rat hippocampi. Magnified view (bottom) shows
256 visible electrodes matched by an equal number on the backside.

Fig. 2. Electrode layout and relevant dimensions of the cortical and hippocampal probe designs. The hippocampal probe electrodes are conformallyarranged to match the location of cell body layers.

pads, 200 nm thick). This layer is insulated in 8 μm of Parylene C, which also serves as the support for the top metal layer(200 nm). The top metal layer is insulated in a final 10 μm
of Parylene C. The total thickness is approximately 20 μm.
For the purposes of the experiments described here,
only 64 electrodes of the 512 total were addressable throughthe electrode interface board, although all electrodes areinferred to be functional. Future devices will integrate digital
multiplexing to allow connection to all electrodes without theneed for 512 analog connections exiting the board.

MEAs were fabricated using a low-temperature, batch-scale,multi-layer process summarized in Fig. 3. The final devices
consist of two metal layers sandwiched and insulated between
three layers of Parylene C. Processing was performed on
4-inch diameter silicon carrier wafers, which were coated ina 100 nm Al sacrificial layer with a 10 nm Ti adhesion layer.
The Al layer was chemically roughened with an 8 minuteetch in CR-7 (Transene Company, Danvers MA) to maintainadhesion of the base Parylene C layer during subsequent
processing. The base Parylene C layer was deposited by room
temperature chemical vapor deposition to a thickness of 2 μm.
An isotropic O2 reactive ion etch, masked by photopatterned
P4620 photoresist (Integrated Micro Materials, Argyle TX),
was used to open holes in this base layer for the backside
electrodes. Next, Pt was deposited and patterned, containing
the 256 back electrodes and associated traces and contact pads.
The metal layer pattern was created using a lift-off photoresist
mask (AZ5214, Integrated Micro Materials, Argyle TX), having a resolution of 2 μm. Then Pt was deposited by e-beam
evaporation to 200 nm total thickness, using four sequential
deposition steps of 50 nm with 30-minute cooling pauses in
between to reduce thermal stress. Next, an 8 μm conformal
insulating layer of Parylene C was deposited over this firstPt layer. A second layer of Pt electrodes, traces, and contact
pads was deposited and patterned in the same manner. This
layer was coated in a final 10 μm of Parylene C. Finally,
the Parylene C over the top electrodes was removed using a
deep reactive O2 ion etch across a P4620 photoresist mask,
and the outline of the MEAs was ‘cut-out’ using a second
etch step performed in the same manner.
Devices were released by dissolving the Al adhesion layer inwarm tetramethylammonium hydroxide. In a post-processing
step, individual devices were annealed at 200 ◦ C for 48 hours
under vacuum, while pressed flat between two Teflon sheets.
This step served both to reduce curvature in the final device
and to reduce pore sizes in the semi-crystalline Parylene C.
C. Characterization and Analysis
Electrode properties and end-to-end continuity were evaluated using cyclic voltammetry (CV) and electrochemical

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JOURNAL OF MICROELECTROMECHANICAL SYSTEMS, VOL. 29, NO. 5, OCTOBER 2020

impedance spectroscopy (EIS). MEAs were connected toa printed-circuit board using a 71 channel ZIF connector(FH43B-71S-0.2SHW, Hirose Electric Co, Tokyo) with a∼100 μm thick polyethylene terephthalate film backer for
structural support. The test board connected each of the64 addressable electrodes to an array of header pins, whichwere connected to a potentiostat (Reference 600, Gamry
Instruments, Philadelphia) for testing. CV was performed
in 0.05 M H2 SO4 in the potential range of −0.2–1.2 V versus
an Ag/AgCl reference and large Pt counter electrode. The
solution was purged with N2 prior to and during the CV.
Scan rate was 250 mV/s for 30 cycles. EIS was performed
in 1× phosphate-buffered saline (PBS) following CV cycling,also using Ag/AgCl and Pt as the reference and counter,
respectively. Impedance was measured across 1 Hz–1 MHz.
Trace-to-trace capacitance was estimated using finite
element modeling in LISA software. Parylene C was assumed
to be perfectly conformal in the intercalary space between
traces, with a relative permittivity coefficient of 3.1, taken fromliterature values [16]. Attempts to measure capacitance withavailable equipment (Keysight E4980AL) confirmed values ator below a noise floor of ∼1 pF.

Fig. 4. Micrograph of patterned Pt traces and electrodes on Parylene substratewith 2 μm pitch/width. Exposed electrode diameter is 20 μm.

III. R ESULTS
Several important observations were recorded during initialattempts to fabricate the MEAs. Unlike prior Parylene MEAs,a sacrificial Al layer was required to prevent the base Parylene
C layer from lifting off from the carrier wafer during processing as a result of etched openings in the base layer for theback electrodes. Parylene C exhibited very high adhesion to
sputtered Al, but almost no adhesion to evaporated Al, a result
we attribute to differences in surface roughness. Treating theevaporated Al with CR-7 (measured etch rate ∼6 nm/min)introduced the desired adhesion. The sacrificial layer also
proved necessary during the first Pt deposition step. When
fabrication was attempted without the adhesion layer, the base
Parylene C (2 μm) wrinkled following Pt evaporation, presumably from thermal stress. Presence of the Al eliminatedthis effect. Achieving the 2 μm resolution lift-off mask was
nontrivial and required tight control of all process parametersand strong Parylene-photoresist adhesion (Fig. 4). Parylene
C is not compatible with typical surface treatments such as
hexamethyldisilazane (HMDS). Instead, prior to photoresist
spinning, wafers were baked for 30 minutes at 60 ◦ C and
1/2 atm under a stream of dry N2 to remove moisture without
oxidizing the polymer film. Following this treatment, lithography was successful and repeatable, suggesting UV lithography
on Parylene C may be pushed to the optical limit.
Completed MEAs were functional and robust. The polymer
shanks were highly compliant despite the high density of metal
traces. Trace-to-trace capacitance was estimated as ∼0.2 pF
from finite element analysis and did not measurably increaseelectrode impedance. Electrical continuity of the backside
electrodes was confirmed with EIS and CV; Fig. 5 shows representative measurement data of an electrode following cyclic
voltammetric cycling. Impedance of the 20 μm electrodes was∼1 M at 1 kHz. This is consistent with impedance values

Fig. 5. Data characterizing the impedance and surface properties of thePt electrodes. (Top) EIS data showing magnitude (left) and phase (right) of arepresentative electrode in 1 × PBS. (Bottom) CV data of the same electrode,
after 30 cycles, showing characteristic hydrogen absorption/desorption andoxide formation and reduction.

from larger electrodes (30 μm diameter; 0.5-0.6 M at 1 kHz)produced on a prior Parylene C-based device [14].
IV. D ISCUSSION
The fine microlithographic resolution achieved here,combined with the multi-layer design, increased electrodedensity while minimizing width of each flexible polymer
shank. Smaller pitch and spacing for microtraces on a polymer
MEA have been reported [12], [17], but using electron-beamlithography, which is a low throughput, serial process that
substantially increases fabrication cost. UV lithography was

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SCHOLTEN et al.: 512-CHANNEL MULTI-LAYER POLYMER-BASED NEURAL PROBE ARRAY

achieved at batch-scale and is amenable to mass production
with lower costs and higher yield.
EIS and CV measurements confirmed the required electrochemical properties for neural recording and validated ourapproach for via-less front and back electrodes. Impedancevalues were consistent with the exposed electrode diameter,suggesting the dominant driver of impedance was electrodesurface area. As trace size for neural interfaces continues
to shrink, there is a risk that trace impedance or capacitive
coupling will drive up impedance, and therefore signal noise.
However, the results here suggest there is room for further
miniaturization, allowing polymer MEAs to approach thechannel density of silicon devices. The impedance valuesof these electrodes (1 M at 1 kHz) may impede highquality recordings but can be coated with a high surface area
platinum-iridium alloy [18], an approach we have demonstrated with similar Parylene C MEAs in an unpublishedstudy.
The next steps are to obtain successful electrophysiologicalrecordings in rats using these MEAs and from two different
brain regions. Implantation of long, flexible polymer probes
can be challenging, as they are likely to buckle during insertion. In prior work we demonstrated a simple insertion methodwith similar Parylene C MEAs [14] that does not require use of
an introducer tool or stiffening agent. Instead, the probe shanks
will be partially encased by a brace made of polyethylene
glycol, leaving a short section of the tips exposed. By reducing
the effective length of the probes in this way, the bucklingforce increases significantly, allowing the bare probes to be
gradually inserted as the remaining brace dissolves in saline.
This allows for insertion without introducing any material but
the Parylene C probes into the brain.
The most significant challenge in developing this technology
is addressing all 512 electrodes. Current ZIF connectors do
not extend to this size, and so the same connection scheme(common to polymer MEAs) would require a split ribbon cableand multiple connectors. Analog output connectors similarly
are not available with 512 channels, in a size suitable forfree-moving animal experiments. The most plausible pathforward will require integration of multiplexing ASICs directly
into the ribbon cable. We recently developed a novel ultrasonicbonding method for direct packaging of ASIC to Parylene C
devices [19]. This approach will allow us to forgo both theneed for a ZIF connector and analog output, while reducing
the density of contact pads.
With respect to application, the high-density polymer-basedneural probe described here is developed in the context of
performing animal studies on long-term synaptic plasticities, which requires high-quality, stable recordings of unitary activities for long periods of time [20]. Such a probe
also has the potential to be used as a therapeutic device inclinical applications such as closed-loop deep brain stimulation (DBS) [21], [22] and cortical prostheses [23], [24]for treating neurological disorders, where high biocompatibility and fine spatio-temporal resolution become critical. One
important future direction is to add stimulation capability
to the polymer-based neural probes to achieve bi-directional
communication between the device and the neural tissue.

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V. C ONCLUSION
A Parylene C based MEA for cortical and subcorticalneural recording in free-moving rats was fabricated, bench-top
evaluated and tested. A novel microfabrication approach was
designed to allow for high-resolution patterning on the flexible polymer base that enables front and back patterning ofelectrodes on either side of a 140-230 μm wide Parylene C
probe shank. A key fabrication improvement was the additionof a chemically roughened Al adhesion layer, that ensured the
Parylene C did not wrinkle or lift-off from the carrier wafer
and could be easily removed at the end of fabrication. The
devices presented here represent the highest channel countper shank among polymer MEAs and among the highest
total channel count for a polymer MEA. The flexible, softcomposition of the probe array is expected to allow for chronic
recording in free-moving animals by mitigating tissue trauma.
The designs and method presented here pave the way forpolymer MEAs to match channel density of the state-of-the-art
in silicon devices.
ACKNOWLEDGMENT
The authors would like to thank Dr. Donghai Zhu and the
USC Keck Photonics Cleanroom for assistance in device fabrication, and Xuechun Wang for assistance in electrochemicalmeasurements.
R EFERENCES[1] J. J. Jun et al., “Fully integrated silicon probes for high-density recordingof neural activity,” Nature, vol. 551, no. 7679, pp. 232–236, Nov. 2017,
doi: 10.1038/nature24636.
[2] G. Rios, E. V. Lubenov, D. Chi, M. L. Roukes, and A. G. Siapas,“Nanofabricated neural probes for dense 3-D recordings of brain activity,” Nano Lett., vol. 16, no. 11, pp. 6857–6862, Nov. 2016, doi:
10.1021/acs.nanolett.6b02673.
[3] H. C. Lee et al., “Histological evaluation of flexible neural implants;
flexibility limit for reducing the tissue response?” J. Neural Eng., vol. 14,
no. 3, p. 36026, 2017.
[4] R. Biran, D. C. Martin, and P. A. Tresco, “Neuronal cell loss accompanies the brain tissue response to chronically implanted silicon microelectrode arrays,” Exp. Neurol., vol. 195, no. 1, pp. 115–126, Sep. 2005,
doi: 10.1016/j.expneurol.2005.04.020.
[5] R. Biran, D. C. Martin, and P. A. Tresco, “The brain tissue response
to implanted silicon microelectrode arrays is increased when the device
is tethered to the skull,” J. Biomed. Mater. Res. A, vol. 82A, no. 1,
pp. 169–178, Jul. 2007, doi: 10.1002/jbm.a.31138.
[6] N. F. Nolta, M. B. Christensen, P. D. Crane, J. L. Skousen, and
P. A. Tresco, “BBB leakage, astrogliosis, and tissue loss correlatewith silicon microelectrode array recording performance,” Biomaterials, vol. 53, pp. 753–762, Jun. 2015, doi: 10.1016/j.biomaterials.
2015.02.081.
[7] M. P. Ward, P. Rajdev, C. Ellison, and P. P. Irazoqui, “Toward a comparison of microelectrodes for acute and chronic recordings,” Brain Res.,
vol. 1282, pp. 183–200, Jul. 2009, doi: 10.1016/j.brainres.2009.05.052.
[8] H. C. Lee, J. Gaire, B. Roysam, and K. J. Otto, “Placing sites on
the edge of planar silicon microelectrodes enhances chronic recording
functionality,” IEEE Trans. Biomed. Eng., vol. 65, no. 6, pp. 1245–1255,
Jun. 2018, doi: 10.1109/TBME.2017.2715811.
[9] R. J. Vetter, J. C. Williams, J. F. Hetke, E. A. Nunamaker, and
D. R. Kipke, “Chronic neural recording using silicon-substrate microelectrode arrays implanted in cerebral cortex,” IEEE Trans. Biomed. Eng., vol. 51, no. 6, pp. 896–904, Jun. 2004, doi: 10.1109/
TBME.2004.826680.
[10] E. Musk and Neuralink, “An integrated brain-machine interface platform
with thousands of channels,” J. Med. Internet Res., vol. 21, no. 10,
Oct. 2019, Art. no. e16194, doi: 10.2196/16194.
[11] J. E. Chung et al., “High-density, long-lasting, and multi-region
electrophysiological recordings using polymer electrode arrays,” Neuron, vol. 101, no. 1, pp. 21.e5–31.e5, Jan. 2019, doi: 10.1016/j.
neuron.2018.11.002.

Authorized licensed use limited to: University of Southern California. Downloaded on October 18,2020 at 02:13:35 UTC from IEEE Xplore. Restrictions apply.

1058

JOURNAL OF MICROELECTROMECHANICAL SYSTEMS, VOL. 29, NO. 5, OCTOBER 2020[12] X. Wei et al., “Nanofabricated ultraflexible electrode arrays for highdensity intracortical recording,” Adv. Sci., vol. 5, no. 6, Jun. 2018,
Art. no. 1700625, doi: 10.1002/advs.201700625.
[13] A. W. Hirschberg, H. Xu, K. Scholien, T. W. Berger, D. Song,and E. Meng, “Development of an anatomically conformal parylene
neural probe array for multi-region hippocampal recordings,” in Proc.
IEEE 30th Int. Conf. Micro Electro Mech. Syst. (MEMS), Jan. 2017,
pp. 129–132, doi: 10.1109/MEMSYS.2017.7863357.
[14] H. Xu, A. W. Hirschberg, K. Scholten, T. W. Berger, D. Song, and
E. Meng, “Acute in vivo testing of a conformal polymer microelectrodearray for multi-region hippocampal recordings,” J. Neural Eng., vol. 15,
no. 1, p. 16017, 2018.
[15] B. J. Kim et al., “3D parylene sheath neural probe for chronic recordings,” J. Neural Eng., vol. 10, no. 4, May 2013, Art. no. 045002, doi:
10.1088/1741-2560/10/4/045002.
[16] (2016). SCS Parylene Properties. Accessed: Apr. 28, 2020. [Online].
Available: https://scscoatings.com/wp-content/uploads/2017/09/02-SCSParylene-Properties-1016.pdf[17] K. Scholten and E. Meng, “Electron-beam lithography for polymer
bioMEMS with submicron features,” Microsyst. Nanoeng., vol. 2, no. 1,
pp. 1–7, Nov. 2016, doi: 10.1038/micronano.2016.53.
[18] A. Petrossians, J. J. Whalen, J. D. Weiland, and F. Mansfeld, “Surface
modification of neural stimulating/recording electrodes with high surface area platinum-iridium alloy coatings,” in Proc. Annu. Int. Conf.
IEEE Eng. Med. Biol. Soc. (EMBS), Aug. 2011, pp. 3001–3004, doi:
10.1109/IEMBS.2011.6090823.
[19] J. J. Yoo and E. Meng, “Fine-pitch bonding methods for integrating ASICs with flexible polymer MEMS,” in Proc. 20th Int. Conf.
Solid-State Sens., Actuators Microsyst. Eurosensors (TRANSDUCERSEUROSENSORS), Jun. 2019, pp. 1623–1626, doi: 10.1109/TRANSDUCERS.2019.8808219.
[20] D. Song et al., “Identification of functional synaptic plasticity fromspiking activities using nonlinear dynamical modeling,” J. Neurosci.
Methods, vol. 244, pp. 123–135, Apr. 2015, doi: 10.1016/j.jneumeth.
2014.09.023.
[21] J. S. Perlmutter and J. W. Mink, “Deep brain stimulation,” Annu. Rev.
Neurosci., vol. 29, no. 1, pp. 229–257, Jul. 2006, doi: 10.1146/annurev.
neuro.29.051605.112824.
[22] A. Ramirez-Zamora et al., “Evolving applications, technological challenges and future opportunities in neuromodulation: Proceedings of thefifth annual deep brain stimulation think tank,” Frontiers Neurosci.,
vol. 11, p. 734, Jan. 2018, doi: 10.3389/fnins.2017.00734.
[23] D. Song, B. S. Robinson, R. E. Hampson, V. Z. Marmarelis,
S. A. Deadwyler, and T. W. Berger, “Sparse large-scale nonlinear
dynamical modeling of human hippocampus for memory prostheses,”IEEE Trans. Neural Syst. Rehabil. Eng., vol. 26, no. 2, pp. 272–280,
Feb. 2018, doi: 10.1109/TNSRE.2016.2604423.
[24] R. E. Hampson et al., “Developing a hippocampal neural prosthetic tofacilitate human memory encoding and recall,” J. Neural Eng., vol. 15,
no. 3, p. 36014, 2018.

Kee Scholten (Member, IEEE) was born in Adelaide, SA, Australia, in 1987. He received the B.S.
degree in applied physics from the California Institute of Technology (Caltech) in 2009 and the Ph.D.
degree in applied physics from the University ofMichigan in 2014. He is currently the Director of thePolymer Implantable Electrode Foundry, Universityof Southern California, Los Angeles. His researchinterests include implantable and wearable microsensors, ubiquitous chemical and biomedical sensing,and flexible MEMS and nanoelectronics.

Christopher E. Larson (Member, IEEE) was bornin St. Paul, MN, USA, in 1987. He received the
B.M. degree in music composition from Biola University in 2009 and the B.S. degree in biomedical
engineering from the University of Southern California (USC) in 2015, where he is currently pursuing
the Ph.D. degree with the Biomedical Microsystems Laboratory, developing polymer MEMS-basedneural interfaces and other implantable medical
devices.

Huijing Xu (Member, IEEE) received the B.S.
degree in biomedical engineering from Shanghai
Jiao Tong University and the Ph.D. degree in biomedical engineering from the University of Southern
California in 2019. She continued studying biomedical engineering at USC and developed her interests in neural engineering and cortical prostheses.
In 2011, she joined the Center for Neural Engineering (CNE), where she works under the direction ofProf. T. W. Berger and Prof. D. Song. Her research
focuses on the development of novel neural interfacing techniques and the understanding of the function of the hippocampus inmemory processing. In specific, she works on the design and development ofconformal multi-electrode arrays that can record neural activities from multiple sub-regions of the hippocampus simultaneously from behaving animals
and to conduct behavioral experiments to study the information transformation
within the hippocampus tri-synaptic circuit.

Dong Song (Senior Member, IEEE) received the
B.S. degree in biophysics from the University of Science and Technology of China in 1994 and the Ph.D.
degree in biomedical engineering from the University of Southern California in 2004. He becamea Research Assistant Professor and a Research
Associate Professor at the Department of Biomedical Engineering, University of Southern California(USC), in 2006 and 2013, respectively. He is the
Co-Director of the Center for Neural Engineering,
USC. His research is supported by the DARPA,
NSF, and NIH. His research interests include nonlinear dynamical modelingof the nervous system, hippocampal memory prosthesis, neural interface
technologies, and the development of novel modeling strategies incorporating
both statistical and mechanistic modeling methods. He is a member ofthe American Statistical Association, the Biomedical Engineering Society,
the Society for Neuroscience, the Society for Brain Mapping and Therapeutics,
Organization for Computational Neurosciences, and the National Academy ofInventors. He received the James H. Zumberge Individual Award from the
USC in 2008, the Outstanding Paper Award of the IEEE T RANSACTIONSON N EURAL S YSTEMS AND R EHABILITATION E NGINEERING in 2013, andthe Society for Brain Mapping and Therapeutics Young Investigator Awardin 2018.

Ellis Meng (Fellow, IEEE) received the B.S. degree
in engineering and applied science and the M.S.
and Ph.D. degrees in electrical engineering fromthe California Institute of Technology (Caltech),
Pasadena, in 1997, 1998, and 2003, respectively.
She is a Professor of Biomedical Engineering andthe Vice Dean of Technology Innovation and Entrepreneurship with the Viterbi School of Engineering,
University of Southern California, Los Angeles. She
also holds a joint appointment with the Ming Hsieh
Department of Electrical and Computer Engineering.
Her research interests include bioMEMS, implantable biomedical microdevices, microfluidics, multimodality integrated microsystems, and packaging.
She is a fellow of the ASME, BMES, AIMBE, and NAI. She held the Viterbi
Early Career Chair and the Gabilan Distinguished Professorship in Scienceand Engineering, and was the Department Chair from 2015 to 2018. Her
honors include the NSF CAREER and Wallace H. Coulter Foundation Early
Career Translational Research Awards, the 2009 TR35 Young Innovator under
35, the ASEE Curtis W. McGraw Research Award, the 2018 IEEE Engineeringin Medicine and Biology Society Technical Achievement Award, and the2019 IEEE Sensors Council Technical Achievement Award.

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