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IN VITRO AND IN VIVO CMOS-BASED MULTIELECTRODE ARRAY
TECHNOLOGY: A POTENTIAL CONTRIBUTER TO NEURAL PROSTHESES
Nadine Humphrey, [email protected], Mahboobin 4:00, Sneha Jeevan, [email protected], Mahboobin 10:00
Abstract — In recent years, complementary metal-oxidesemiconductors (CMOS) have been combined with
multielectrode array (MEA) technology to form high-density
electrode arrays that surpass its predecessors in terms of
signal accumulation, specificity and longevity. CMOS MEAs
integrate millions of circuit elements on a single silicon chip,
increasing density and selectivity when recording and
stimulating cell cultures.
Current and future applications of CMOS MEA
technology are extensive, but this paper will specifically
discuss research applications for neural recording, neural
stimulation and neural prostheses. With the recent
development of biocompatible CMOS integrated circuits,
these applications have great potential to succeed, as one of
the main previous limitations of CMOS multielectrode array
technology was the potential neuron-damaging toxicity due to
lack of biocompatibility.
CMOS multielectrode array technology is significant to
bioengineers because it makes available a relatively easy,
swift, and non-invasive method for recording and stimulating
neural activity. Furthermore, this paper will examine the
technical limitations and potential benefits of this
revolutionary technology. It will also discuss the challenges
between balancing affordability and commercial availability
with quality of life.
Key Words — CMOS, Complementary metal-oxide
semiconductor, Microelectrode Array (MEA), Multielectrode
Array (MEA), Neural Engineering, Neural Prostheses,
Neural Recording, Neural Stimulation
HOW CMOS MEA ARRAYS CONTRIBUTE
TO NEURAL PROSTHESES
Neural prostheses are a series of devices that can serve
as substitute motor, sensory, or cognitive modality that might
have been damaged from injury or disease. This type of
technology is critical to a number of the disabled population.
Limb amputation and spinal cord injuries (SCI) significantly
affect daily life. While the ability to function voluntarily may
be lost, the underlying neural circuitry in charge of sensing
and actualizing movement still exists. Prosthetic limbs have
made significant progression both in their complexity and
their prevalence. According to the National Spinal Cord
University of Pittsburgh Swanson School of Engineering
Submission Date 31.03.2017
1
Injury Statistical Center, there are approximately 17,000 new
SCI cases each year in the United States alone [1], excluding
those who do not survive the injury. For amputations, the
number is even higher, with approximately 185,000
amputations occurring the United States each year [2].
Because this is such a widespread issue, there are already
assistive devices on the market that range from non-invasive,
such as eye-tracking, to highly invasive, such as devices
implanted directly into the brain.
Multielectrode arrays (MEAs) are a rapidly advancing
technology that has widely been used to access
electrophysiological signals in in-vivo or in-vitro electrogenic
cell networks. MEAs were previously used in such noninvasive procedures to allow for long-term monitoring of
large neuronal cell assemblies. Researchers would be able to
investigate the fundamental properties of neuronal networks,
such as plasticity and memory, for extended periods of time
without causing harm to the neuron’s outer membrane.
However, one of the biggest issues involved with using
conceptual MEA systems is the number of electrodes
provided within the system could only give a partial view of
the network signaling.
When CMOS technology is integrated into the MEA
platforms, this issue along with other limitations from nonCMOS MEA technology, are resolved. In addition, CMOS
MEA technology would provide a great boon to the neural
prostheses community, as it has already done with the neural
recording and stimulation communities; by allowing for a
greater amount of data to be collected and processed, with the
hope that more data will give a clearer picture of how neural
cells function and how they can be stimulated to invoke
movement which can bypass the damaged spinal cord and
allow for a patient’s freedom of movement, once more.
THE DEVELOPMENT OF
MULTIELECTRODE ARRAYS
MEAs were primarily developed to observe and record
activity from cell cultures. They were first used to record
spontaneous electrophysiological activity from dissociated
spinal cord neurons. As the technology began to develop,
MEAs were found to be useful in various applications,
including in vivo and in vitro. MEA-chips are fabricated
devices that embed an array of metallic microelectrodes on a
Nadine Humphrey
Sneha Jeevan
glass or silicon substrate [3]. The typical microelectrode
diameter is in the range of 10µm-30µm and with a center-tocenter pitch of more than 100µm. Each microelectrode is
individually wired to a bond pad at the edge of the chip. As
seen in Figure 1 [4], multielectrode arrays have common
fabrication steps: metal patterning, insulation and electrode
opening [4].
tungsten and they can be used to estimate the position of
individual recorded neurons. Silicon-based microelectrode
arrays include two specific models: the Michigan and Utah
arrays. [4]
Michigan arrays allow a higher density of sensors for
implantation as well as a higher spatial resolution than
microwire MEAs. In contrast to Michigan arrays, Utah arrays
consist of 100 conductive silicon needles in a 3D model.
However, signals are only received from the tips of each
electrode, which limits the amount of information that can be
obtained at one time. Flexible arrays, made with polyimide,
parylene, or benzocyclobutene, provide an advantage over
rigid microelectrode arrays because they provide a closer
mechanical match to the brain tissue.
The use of cell-non-invasive extracellular MEAs for in
vitro recordings and for in vivo recordings largely attenuate
and temporally filter the electrical signals while enabling the
simultaneous recording and stimulation of large populations
of excitable cells for days and months without inflicting
mechanical damage to the neuron's plasma membranes. While
there are a multitude of benefits that come with using MEAs
for the recording and stimulation of neuronal cultures, there
are some limiting factors with this technology. One of the
largest setbacks with this technology, due to the limited
number of electrodes, is its inability to record electrical
signals over large active areas of brain tissue. This was an
issue for larger neuronal tissue cultures, as researchers were
not able to read signals over larger areas of brain tissue.
However, the integration of CMOS technology into MEA
platforms allow for the resolution of this issue.
Figure 1 [4]
Process of fabrication of a typical multielectrode array
In metal patterning, chromium and gold metal, called the
photoresist, is added onto a thin film of silicon wafer. The
compound is then patterned using a mask and then exposed to
UV radiation; those unexposed parts of the compound are
insulated and provide wells for the placement of electrodes.
Finally, in the last step, electrode opening, the mask is
removed after it is developed in the previous step, allowing
for the placement of electrodes on the chip. While these steps
are common for the development of most biosensors, it is
difficult to determine one method for the fabrication of
MEAs, simply because there are so many different types of
MEAs.
Integration of CMOS and MEA technology
CMOS technology integrated within the multielectrode
array platform allows to overcome the limitation with the
conventional MEA platforms, which prevented the reading of
signals over larger areas of brain tissues. by implementing
large and dense multi electrode arrays to map extracellular
signaling of entire cell networks in cultures and tissues.
Simple microfabrication technologies, such as the ones used
for conventional MEAs, are not sufficient to comply with the
increasing need of more electrodes in neuronal cell research.
Routing and interconnection complexities limit conventional
MEAs from scaling up the number of electrode channels to
more than a few hundreds. However, the miniaturization of
the MEAs goes with an increase of the electrodes impedance
and necessitates high input impedance neural amplifiers [5],
which lowers recording of signals.
Complementary Metal Oxide Semiconductor, or
CMOS, technology can bridge the gap between lowelectrode-counts MEA devices and high-resolution MEA
platforms. CMOS allows cost-efficient implementation of
electrodes and electronics onto one single silicium chip,
preventing the need for more complex interconnections.
Highly purified silicium substrates are microstructured and
processed with different doping elements and metals to form
At this point, the main method for studying neuronal
circuit-connectivity, physiology and pathology under in vitro
or in vivo conditions is by using substrate-integrated
microelectrode arrays. There are two general classes of
MEAs: implantable MEAs, used in vivo, and non-implantable
MEAs, used in vitro. [3] The standard type of in vitro MEA
comes in a pattern of 8x8 or 6x10 electrodes. These electrodes
are typically composed of indium tin oxide or titanium and
have diameters between 10 and 30 μm. These arrays are
normally used for single-cell cultures or acute brain slices.
The MEAs used in in vivo, however, are then classified into
three subsections: micro wire, silicon based and flexible.
Microwire MEAs are largely made of stainless steel or
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and integrate thousands up to billions of transistors within a
single chip.
CMOS differential neural amplifiers interwoven within
the electrodes form a circuit within the chip that allow for the
amplification of signals to allow the technology to cover a
larger basis. An element consisting of a metallic electrode and
some local electronics for signal conditioning is referred to as
a pixel. Each pixel's output is switched to one single output at
a defined time. In this way, each pixel within an array is read
one after each other. They all have a precise timing
relationships that allows decreasing the number of effective
output channels. Therefore, one output channel contains the
multiplexed signals of many electrode channels and can be reordered and selected with the researcher's external hardware.
By enabling simultaneous measures from thousands of
microelectrodes, CMOS-integrated MEAs allow for largescale high resolution electrophysiological recordings in-vitro,
from cultures and brain tissues.
Synapses generally transmit signals in one direction and
can be electrical or chemical [6]. Electrical synapses exist at
the gap junctions between cells. Specialized proteins from
channels between the two neurons, allowing the current
though and the signal to be propagated. In chemical synapses,
once an AP reaches the end of the axon, it triggers the
secretion of neurotransmitters [6], chemicals that allow for
signal propagation, from the presynaptic neuron. The
neurotransmitters travel across the space between the two
neurons, called the synaptic cleft, and bind to the receptors on
the dendrite of the postsynaptic neuron. That generates
electrical signals in the postsynaptic neuron, which are
propagated through the dendrites and continue to the other
neurons until it reaches its proper destination. Now the we
have described neuron anatomy and physiology, we can
discuss how neurons and electrodes interact, specifically via
the neuron-electrode interface.
Neuron-Electrode Interface
RELATIONSHIP BETWEEN CMOS MEA
AND NEURAL CELLS
The neuron-electrode interface is formed from a neuron,
a gap between the neuron and the electrode substrate and the
electrode. These neurons adhere to MEA substrates via
electrochemical interactions between adhesion molecules of
neurons and the substrate molecules of the MEA platform [3].
There are two basic models, the point-contact model and the
area-contact circuits, which dictate that there be a tight seal
between neurons and electrodes to measure the extracellular
action potential (EAP), which is the voltage that a neuron
generates when it signals other cells [7]. It allows the MEAs
to be treated as an insulator – a material that does not let
electrical charges flow freely. This is possible because of its
high input impedance or resistance, allowing the electrodes to
detect the average voltage at its recording site.
Before this paper can address the relationships and
interactions between neurons and our CMOS MEA
technology, we must first explain what neuronal cells are and
how they function. Neuronal cells form most the nervous
system. In the human brain alone, there are about 10 12
neurons, each forming thousands of connections with
surrounding neurons, making one of the most complex
biological systems ever encountered [5]. There are different
neurons depending on their physiology, but all have the same
four distinguishing characteristics: the cell body, dendrites,
axon, and axon terminal. Figure 2 provides a graphic of the
anatomy of a typical neuron. The cell body houses the
nucleus, which is responsible for controlling the cell, and
produces neuronal proteins. The dendrites branch away from
the cell and function to receive incoming signals from other
neurons. They can number from one to over a hundred. On
the opposite end of the dendrites is the axon. Whereas a
neuron typically has multiple dendrites, it only ever has one
axon. The axon is specialized to conduct electrical pulses, also
called action potentials (AP), towards the axon terminal. The
axon terminal, also called a synapse, is where the AP transfers
from one neuron to another.
FIGURE 2 [6]
Schematic View of a Neuron
FIGURE 3 [3]
Spatial relationship between neuron and a substrateintegrated electrode
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considering the current and potential applications of CMOS
MEA technology. This technology gains its recognition
mainly through its applications to signal acquisition and
interpretation in neural recording and electrical stimulation
and interaction in neural stimulation.
One of the potential applications that we would like to
discuss is the use of CMOS MEA technology in neural
prostheses, which would benefit people with spinal cord
injuries and amputees with regaining mobility. The
implication of this application will be discussed in terms of
how neural recording and stimulation from CMOS MEA
contribute to its functionality.
Figure 3 depicts a simplified version of the spatial
configuration of the neuron and the MEA. The neuron surface
is separated into the junctional membrane that faces the
sensing pads of the electrode and the non-junctional
membrane of the substrate. Action potentials produce
extracellular current that flow between the junctional and
non-junctional membranes [3]. The cleft is filled with an ionic
solution that generates a resistance (the seal resistance). The
voltage over the seal voltage changes the charge dispersal
across a passive metal electrode. This differs slightly from the
actual electrochemical relationship that makes this interface
possible.
CMOS MEA in Neural Recording
Electrochemical interaction between CMOS MEA and
neurons
Neural recording is a method of measuring the
electrophysiological responses of a neuron (or multiple
neurons) using multielectrode array systems. Our focus in this
paper is on extracellular neural recording, which measures
extracellular action potentials from neurons. This is a widelyused technique in cognitive science, which they use to
observe neural reactions to different stimuli. This also has
applications in neural prostheses, which will be addressed in
a later section. The brain operates in such a way that any
decisions made being transported via a single activation of the
network. There is currently a great demand to be able to
acquire available information from individual network sites in
order to obtain a deeper understanding of the neural system
and how and when neurons interact with one another. Neural
cell culture recordings using CMOS MEAs monitor culture
activity with unprecedented detail at a large scale. This
enables the investigation of various hypotheses pertaining to
the cooperative effort among neurons in processing
information [8]. The increased spatiotemporal definition
provided by CMOS MEA technology also allows researchers
to discern between neural sources of recorded signals and
therefore, improve their capability to sort a greater number of
single neurons. These factors contribute to the ability to
reliably study neural network dynamics [8]. Knowledge of
how the neurons stimulate and collaborate to processes and
stores information would provide a deeper understand that
could be applied to obtaining and decoding acquired neural
signals and. The increased specificity in obtaining neural
‘spikes’ from action potential propagation could allow
researchers to identify when and where specific thoughts or
impulses are generated to let them triangulate irregularities in
patients with neural disorders or those suffering from injuries
to the nervous system.
Research using CMOS MEA technology in neural
recording has already uncovered a correlation between
primary neuronal cultures displaying spontaneous activities
as they mature and propagating waves of spiking activity
throughout the neural network. The cause of such waves had
been a great subject of debate among neuroscientists for
years, as these waves were ubiquitous throughout the brain,
before this discovery. While the function of these waves is
CMOS multielectrode array technologies are
electrochemically related neuronal cell cultures via electrical
coupling. A review on multielectrode array technologies for
neuroscience and cardiology defines electrical coupling
between neurons and electrodes as “the ratio between the
maximal voltages recorded by the device in response to the
maximal voltage generated by an excitable cell” [3]. This
essentially translates into the ratio of energy picked up by the
multielectrode array by the amount of energy produced.
The electrical coupling coefficient between cells and
MEA is heavily influenced by electric field potentials (FP),
voltages caused by stationary charges, also known as just
“field potentials”, and impedance of the sensing pad of the
electrode. The magnitude and shape of FPs are calculated by
multiplying the seal resistance with the current running across
it [3]. The effect of impedance on electrical coupling is caused
by the difference of currents through living cells and electrical
devices and is usually attributed to the layer of ions formed
between the ionic solution that the neurons reside in and the
MEA’s active region. The layer of ions forms a type of
blockade that resists the current flowing from the cells to the
electrode, lowering the maximal voltage that the electrode
collects. This voltage across the cell corresponds to the action
potential being sent down the neuron. There are a number of
applications for which this data can be used, which we will
address in the next section.
CURRENT AND FUTURE APPLICATIONS
OF CMOS MULTIELCTRODE ARRAY
TECHNOLOGY
The main advantages of using CMOS multielectrode
array technology are connectivity, signal quality and ease of
handling and use [6]. The user-friendly features are a critical
component to encourage neuroscientists and biologists to use
those systems. Current MEAs have neither the spatiotemporal
definition nor the sheer potential to collect massive amounts
of data in a feasible manner. These issues are important
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still up for debate, the use of CMOS MEA technology brought
about greater insight that may assist in finding the answer.
Potential of CMOS MEA for Neural Prostheses
CMOS-IC based MEA systems have a variety of uses,
like those described above. But one of the most influential for
our time is its use in in vitro neural prostheses. While the
actuation of neural prostheses is done in vivo, the insights
gained by in vitro approaches, combined with the lowered
costs to experiment and lowered safety risks, make it a topic
well worth discussion. There is not much literature on the
exact role that in vitro CMOS multielectrode arrays play in
neural prostheses. It is possible however, to elucidate how its
current applications could contribute to the topic.
Neural prostheses are made possible by the brainmachine interface, which acquires and interprets neuron
signals and processes them using algorithms depending on
what is to be interpreted. These algorithms sort through the
signals and search for specific patterns that the body interprets
as movement. For example, a 2016 research group study
collected neural signals from the brain of the study
participants and applied machine-learning algorithms to
decode the neuronal activity and control activation of the
participant’s forearm muscles through a custom-built highresolution neuromuscular electrical stimulation system [10].
It delivered electrical stimulation to his paralyzed right
arm using a- 130-electrode array in a flexible sleeve wrapped
around his arm. The participant attended 3 weekly session for
about 15 months after implantation of the system for the use
of his wrist and hand. In terms of accuracy, sensitivity, and
specificity, the patient had improved wrist and hand function
by 70.4%, 81.9%, and 94.8% respectively [10]. Through this
process the patient gained wrist and hand function. More
importantly, for the first time, a human with quadriplegia was
able to regain volitional, function movement through
recorded signals limited to neuromuscular stimulation in real
time.
Research from CMOS MEA could help to uncover even
more techniques for machine learning, allowing signal
decoding to go smoother and more profound. Using CMOS,
based MEA technology would increase signal acquisition and
lower the signal to noise ratio, leaving the computer
algorithms with less to sort through and reducing the chance
of recording artifacts, which could potentially allow for
smoother limb movement and a greater range of motion. The
density of electrodes would provide a greater range of data
collected per unit of area for one chip, and the longevity of
CMOS-based MEA make it safer for human use, as the
chance of degradation is significantly lowered. This also
serves to be cost effective if or when implemented in clinical
settings.
CMOS MEA in Neural Stimulation
On their own CMOS-IC based systems have a limited
ability to stimulate spatiotemporal patterns in arbitrary
subsets of electrodes. Most are restricted to one to a few
electrodes all using the same stimulation protocol. While
there have been significant improvements made to modern
MEA technology, few have taken advantage of CMOS
technology to generate complex arbitrary defined activity
patterns in large numbers of neurons [9]. An additional
common problem in simultaneous electrical stimulation is
stimulation artifacts, or errors resulting from human or
technical mistakes. This makes extracting and amplifying
neural activity extremely difficult, a challenge that has
frustrated those in the electrophysiology and neuroscience
fields. Neural signals typically have low amplitudes. To have
devices that can pick up these low signals, these devices must
create low noise [4]. However, most devices send out larger
electrical signals than they receive from the neurons
themselves [9]. This saturation of recording amplitude means
that it is difficult to detect if the signal is even present, let
alone its location.
A collaboration between two researchers from Osaka
University and Hokkaido University in Japan designed a
CMOS IC-based MEA system that was capable of both
stimulating and recording neurons, allowing for adjustable
frequency ranges for Aps and local FPs. This includes an
application-specific integrated circuit (ASIC) deigned for
multisite electrical stimulation via MEAs [9]. This newly
developed system is intended for applications in systems that
require simultaneous stimulation and recording of neural
signals. The ACIS system contains 64 independent
stimulation channels, which can generate defined bipolar
voltage pulses below an amplitude of 2.5 volts with 5-bit
resolution. The ACIS system is also equipped with
stimulation artifact suppressors controlled in real-time,
reducing the dead time between stimulation pulse and
recording [9]. The structure of the MEA is such that users can
select an arbitrary set of electrodes for stimulation, with
individually different stimulus waveforms or with al 64
channels on the same waveform, consisting of a series of
mono- and bi-polar pulse trains.
Practical applications for this system include retinal
prosthetics for the blind and cochlear implants for those with
hearing disabilities. It also shows promise for developing
machine learning which is a kind of artificial intelligence
where the machine can operate without being programmed.
The hope for this paper is to explain how this design will
impact the development of neural prosthetics, which differs
from the previously mentioned applications. This next section
will discuss how they differ, as well as how neural
stimulation, as well as neural recording.
IMPACT OF CMOS MULTIELECTRODE
ARRAY TECHNOLOGY
Although CMOS multielectrode array technology is still
a relatively new form of technology, the biosensor has been
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Sneha Jeevan
popular in the field of neuroscience research. CMOS is
currently the dominant technology used worldwide in
intracellular products, and it is therefore of no surprise that
CMOS-integrated MEA technology has also been widely
used. The usage of the CMOS MEA platform in research has
been constantly growing, enabling unprecedented functional
imaging in networks of electrogenic cells, and in neuronal
networks in particular. With the rapid growth of such a new
technology provided a multitude of benefits in this area of
research, there are still several possible challenges in
furthering this technology as the convention. Despite some of
the current challenges with the technology, it is interesting to
investigate the future of this technology, specifically in the
area of neural prostheses.
aluminum itself to degrade, which contributes to the general
toxicity of such biosensors. [7]. This is not a major
complication on its own, however if this technology could
potentially be implanted into a patient’s brain to facilitate
neuron stimulation and movement, this is a critical challenge
to overcome.
However, a solution has been proposed to offset the
dangers that the aluminum surface brings by electroplating
the electrode with platinum using 1.5 V to a counter-electrode
in a platinizing solution [9]. Platinum is nontoxic to cells and
decreases electrode impedance, granting enhanced voltage
readings from electrodes. Another study from the University
of Bath and King’s College London noted that coating planar
electrodes in platinum-black decreased its impedance by
increasing its effective surface area [7].
Current Challenges in using CMOS MEA Technology
Potential Benefits in using CMOS MEA Technology
While CMOS MEA technology does have significant
advantages over other MEA technology, there are still some
serious issues that need to be worked out before this
technology can be commercialized for widespread use. One
of the most prevalent challenges with using CMOS
technology is that it generally requires additional postfabrication to be compatible with the target subject, in this
case neurons. Even within the process of researching of this
paper, there have been several articles that propose wildly
varying post-fabrication methods that have made it difficult
to pin down what and how CMOS technology, in general,
integrates with MEAs to study neural functions. As so
eloquently stated in a review discussing the
commercialization
of
CMOS
MEA
technology,
“Constructing an overall picture of biosensor research is
impeded by the large quantity of published articles and
patents combined with the diversity of the technologies and
applications” [7]. However, there has been a commonly
reported use of electrochemical transducers for standard
CMOS fabrication since electrodes in contact with the
analyte (in this case, neurons) can be used in tandem with
different types of biosensors and multielectrode array
technology.
There are also severe challenges in biocompatibility. For
a CMOS electrode to be successfully integrate to an MEA for
applications in neural recording and stimulation, or to be in
contact with any biological organism, it must be
biocompatible. An article on the potential commercialization
of CMOS MEA technology defines something to be
sufficiently biocompatible if it does not change the function
of the substance its analyzing or must be nontoxic to all the
biological components of the system [7]. Without
modification, almost all CMOS technology has an aluminum
coated surface. For the most part, these aluminum coated
surfaces are safe to use in cell cultures. Despite aluminum
being the most often used surface material in CMOS
electrodes, there are some serious potential dangers to the
surrounding cells. Defects in the oxide film of the electrode
can allow aluminum ions to leak into the body or for the
Currently, CMOS MEA technology exists more for
research than for the public. However, there are some
companies who are interested in expanding its use. One such
company, called 3-Brain, manufactures and sells CMOS MEA biochips that focus on in vitro electrophysiology and
extracellular signals from electrogenic cells, such as neurons.
3-Brain offers a series of CMOS integrated MEA chips that
allow researchers to select the level of resolution they require
for their readings, as well as additional hardware that can
translate and organize the multitude of signals coming into the
amplifier.
With such a technology in place, it is possible for it to
be integrated commercially into the public, specifically in the
treatment of spinal cord injuries. Due to the non-invasiveness
of the chips, it would be possible for patients with spinal cord
injuries, who would normally have to pay thousands of dollars
for bulky, debilitating treatments [p], to use such a device in
order to eliminate the need of invasive procedures. While
some may argue the ethics of integrating such biosensors into
patient treatments, as the technology could have the potential
to regulate signaling such that a person could extend their
lifespan, we will focus more on the increasing of the quality
of the life of the patient rather than increasing their lifespan.
Using CMOS MEA technology in more general applications
will allow those with brain based injuries to gain their life
back again after facing such terrible injuries.
FUTURE DIRECTIONS
With the development of such a new technology, there
are exciting applications of CMOS MEAs in the future. The
embedding of this technology into neural cultures could allow
for its establishment in the field of in vitro neural prostheses.
In these last sections, we will discuss the sustainability of
CMOS MEAs in the medical field, as well as the possible
future applications of this technology in helping patients with
brain diseases and injuries.
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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4193337/
[10] C.E. Bouton et al. “Restoring cortical control of functional
movement in a human with quadriplegia.” Nature. 05.12.2016.
Accessed
03.03.2017.
http://www.nature.com/nature/journal/v533/n7602/full/nature1743
5.html
Sustainability of CMOS MEA Technology
While sustainability is not emphasized in the medical
field as much as it is in business practices, medical devices
that consider sustainability have a much greater advantage
over those who do not. Because the materials that are used to
make the CMOS MEAs are not particularly toxic on their
own, the focus of sustainability will be its’ affordability in
perspective with the quality of care it will provide patients.
The application of the MEAs in the treatment of brain injuries
should provide the most effective means of care for the patient
at a low cost. The average lifetime costs of a patient's
treatment for a traumatic brain injury are estimated to run
from $85,000 to $3 million. [4] Even with these huge costs,
patients are prone to living a terrible quality of life, as the
bulky external technology that these patients need to survive
greatly decrease their mobility.
With the implantation of CMOS based MEA technology
into brain injury treatment, patients would be able to gain the
autonomy they previously had without the need for bulky,
debilitating technology. However, as this technology is new,
it is difficult to determine the cost of such technology in
accordance to the quality of life. As the technology continues
to grow, companies should ensure that CMOS MEAs will
provide a balance between cost and quality of care that will
allow brain injury patients proper treatment without
overtaking the price of normal treatment.
Future Applications of CMOS MEA Technology
We see that with the embedding of CMOS MEA
technology into neuronal cultures, one of the most influential
applications of the technology being in its use in in
vitro neural prostheses. the future of CMOS MEA technology
lies within neural prostheses.
While the actuation of neural prostheses is done in
vivo, the insights gained by in vitro approaches, combined
with the lowered costs to experiment and lowered safety risks,
make it a topic well worth discussion. In the future, it is our
hope that studies made with in vitro CMOS-based MEA are
implemented in vivo and that strides are made such that
implanting devices are not required to acquire and process
signals from neurons. That, however, is a very far off goal.
For now, it is safe to say that the strides made by using
CMOS-based MEA technology in vitro will be applied to aid
those who suffer from injuries or diseases that render them
incapable of voluntary function. The ultimate goal of this
process is to bring them one step closer to the autonomy they
had previously.
ADDITIONAL SOURCES
H. Amin, A. Maccione. S. Zordan, T Nieus, L. Berdondini.
"High-density MEAs reveal lognormal firing patterns in
neuronal networks for short and long term recordings."
Neural Engineering. 04.23.2015. Accessed 01.25.2017.
http://ieeexplore.ieee.org/document/7146795/
D. Perruchoud, I. Pisotta, S. Carda, M. Murray, S. Ionta.
"Biomimetic rehabilitation engineering: the importance of
somatosensory feedback for brain–machine interfaces."
Journal of Neural Engineering, 13(4), 041001. 2016.
SOURCES
[1] “Spinal Cord Injury (SCI) Facts and Figures at a Glance.”
National Spinal Cord Injury Statistics Center. 2016. Accessed
03.03.2017.
https://www.nscisc.uab.edu/Public/Facts%202016.pdf
7
Nadine Humphrey
Sneha Jeevan
Accessed
01.10.2017.
https://www.ncbi.nlm.nih.gov/pubmed/27221469
ACKNOWLEDGMENTS
Our group would like to acknowledge our writing
instructor, Professor Beth Bateman Newborg, for her help in
the entire process of forming this editing the abstract and
formulating a cohesive outline. We would also like to
acknowledge the engineering librarians for their help with
finding appropriate and substantive sources.
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