Cochlear Implants Stimulate Activity-Dependent CREB Pathway in the Deaf Auditory Cortex: Implications for Molecular Plasticity Induced by Neural Prosthetic Devices

AbstractFunctional outcomes with neural prosthetic devices, such as cochlear implants, are limited in part due to physical separation between the stimulating elements and the neurons they stimulate. One strategy to close this gap aims to precisely guide neurite regeneration to position the neurites in closer proximity to electrode arrays. Here, we explore the ability of micropatterned biochemical and topographic guidance cues, singly and in combination, to direct the growth of spiral ganglion neuron (SGN) neurites, the neurons targeted by cochlear implants. Photopolymerization of methacrylate monomers was used to form unidirectional topographical features of ridges and grooves in addition to multidirectional patterns with 90° angle turns. Microcontact printing was also used to create similar uni- and multi-directional patterns of peptides on polymer surfaces. Biochemical cues included peptides that facilitate (laminin, LN) or repel (EphA4-Fc) neurite growth. On flat surfaces, SGN neurites preferentially grew on LN-coated stripes and avoided EphA4-Fc-coated stripes. LN or EphA4-Fc was selectively adsorbed onto the ridges or grooves to test the neurite response to a combination of topographical and biochemical cues. Coating the ridges with EphA4-Fc and grooves with LN lead to enhanced SGN alignment to topographical patterns. Conversely, EphA4-Fc coating on the grooves or LN coating on the ridges tended to disrupt alignment to topographical patterns. SGN neurites respond to combinations of topographical and biochemical cues and surface patterning that leverages both cues enhance guided neurite growth.

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Public Understanding of Neural Prosthetics in Germany: Ethical, Social, and Cultural Challenges

Cambridge Quarterly of Healthcare Ethics ◽

10.1017/s0963180111000119 ◽

2011 ◽

Vol 20 (3) ◽

pp. 434-439 ◽

Cited By ~ 2

Author(s):

KATSIARYNA LARYIONAVA ◽

DOMINIK GROSS

Keyword(s):

Nervous System ◽

Cochlear Implants ◽

The Body ◽

Public Understanding ◽

Neural Prosthetics ◽

Prosthetic Devices ◽

Neural Prosthetic ◽

Cultural Challenges ◽

Sensory Motor ◽

Accepted Form

Since the development of the first neural prosthesis, that is, the cochlear implant in 1957, neural prosthetics have been one of the highly promising, yet most challenging areas of medicine, while having become a clinically accepted form of invasiveness into the human body. Neural prosthetic devices, of which at least one part is inserted into the body, interact directly with the nervous system to restore or replace lost or damaged sensory, motor, or cognitive functions. This field is not homogenous and encompasses a variety of technologies, which are in various stages of development. Some devices are well established in clinical practice and have become routine, such as cochlear implants. By comparison, other technologies are in experimental phases and still need to be further developed to achieve the desired results.

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Layered Nanocomposites from Gold Nanoparticles for Neural Prosthetic Devices

Nano Letters ◽

10.1021/nl3015632 ◽

2012 ◽

Vol 12 (7) ◽

pp. 3391-3398 ◽

Cited By ~ 56

Author(s):

Huanan Zhang ◽

Jimmy Shih ◽

Jian Zhu ◽

Nicholas A. Kotov

Keyword(s):

Gold Nanoparticles ◽

Prosthetic Devices ◽

Neural Prosthetic

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A Biomimetic Adaptive Algorithm and Micropower Circuit Architecture for Implantable Neural Decoders

Clinical Technologies ◽

10.4018/978-1-60960-561-2.ch223 ◽

2011 ◽

pp. 581-619

Author(s):

Benjamin I. Rapoport ◽

Rahul Sarpeshkar

Keyword(s):

Real Time ◽

Analog Circuit ◽

Decoding Algorithm ◽

Prosthetic Devices ◽

Neural Prosthetic ◽

Neural Data ◽

Time Operation ◽

Real Time Operation ◽

Synaptic Dynamics ◽

Cell Ensemble

Algorithmically and energetically efficient computational architectures that operate in real time are essential for clinically useful neural prosthetic devices. Such architectures decode raw neural data to obtain direct motor control signals for external devices. They can also perform data compression and vastly reduce the bandwidth and consequently power expended in wireless transmission of raw data from implantable brain–machine interfaces. We describe a biomimetic algorithm and micropower analog circuit architecture for decoding neural cell ensemble signals. The decoding algorithm implements a continuous-time artificial neural network, using a bank of adaptive linear filters with kernels that emulate synaptic dynamics. The filters transform neural signal inputs into control-parameter outputs, and can be tuned automatically in an on-line learning process. We demonstrate that the algorithm is suitable for decoding both local field potentials and mean spike rates. We also provide experimental validation of our system, decoding discrete reaching decisions from neuronal activity in the macaque parietal cortex, and decoding continuous head direction trajectories from cell ensemble activity in the rat thalamus. We further describe a method of mapping the algorithm to a highly parallel circuit architecture capable of continuous learning and real-time operation. Circuit simulations of a subthreshold analog CMOS instantiation of the architecture reveal that its performance is comparable to the predicted performance of our decoding algorithm for a system decoding three control parameters from 100 neural input channels at microwatt levels of power consumption. While the algorithm and decoding architecture are suitable for analog or digital implementation, we indicate how a micropower analog system trades some algorithmic programmability for reductions in power and area consumption that could facilitate implantation of a neural decoder within the brain. We also indicate how our system can compress neural data more than 100,000-fold, greatly reducing the power needed for wireless telemetry of neural data.

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Stability Performance Analysis of Various Packaging Materials and Coating Strategies for Chronic Neural Implants under Accelerated, Reactive Aging Tests

Micromachines ◽

10.3390/mi11090810 ◽

2020 ◽

Vol 11 (9) ◽

pp. 810

Author(s):

Yan Gong ◽

Wentai Liu ◽

Runyu Wang ◽

Matthew Harris Brauer ◽

Kristine Zheng ◽

...

Keyword(s):

Packaging Materials ◽

Neural Implants ◽

Three Solutions ◽

Parylene C ◽

Prosthetic Devices ◽

Neural Prosthetic ◽

Stability Performance ◽

Interface Delamination ◽

The Stability ◽

Phosphate Buffered Saline

Reliable packaging for implantable neural prosthetic devices in body fluids is a long-standing challenge for devices’ chronic applications. This work studied the stability of Parylene C (PA), SiO2, and Si3N4 packages and coating strategies on tungsten wires using accelerated, reactive aging tests in three solutions: pH 7.4 phosphate-buffered saline (PBS), PBS + 30 mM H2O2, and PBS + 150 mM H2O2. Different combinations of coating thicknesses and deposition methods were studied at various testing temperatures. Analysis of the preliminary data shows that the pinholes/defects, cracks, and interface delamination are the main attributes of metal erosion and degradation in reactive aging solutions. Failure at the interface of package and metal is the dominating factor in the wire samples with open tips.

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Controlling cellular reactive responses around neural prosthetic devices using peripheral and local intervention strategies

IEEE Transactions on Neural Systems and Rehabilitation Engineering ◽

10.1109/tnsre.2003.814800 ◽

2003 ◽

Vol 11 (2) ◽

pp. 186-188 ◽

Cited By ~ 169

Author(s):

W. Shain ◽

L. Spataro ◽

J. Dilgen ◽

K. Haverstick ◽

S. Retterer ◽

...

Keyword(s):

Intervention Strategies ◽

Prosthetic Devices ◽

Neural Prosthetic

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Activity-dependent structural plasticity after aversive experiences in amygdala and auditory cortex pyramidal neurons

Neuroscience ◽

10.1016/j.neuroscience.2016.04.045 ◽

2016 ◽

Vol 328 ◽

pp. 157-164 ◽

Cited By ~ 9

Author(s):

Tina Gruene ◽

Katelyn Flick ◽

Sam Rendall ◽

Jin Hyung Cho ◽

Jesse Gray ◽

...

Keyword(s):

Auditory Cortex ◽

Pyramidal Neurons ◽

Structural Plasticity ◽

Activity Dependent

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Typical somatomotor physiology of the hand is preserved in a patient with an amputated arm

10.1101/2021.02.12.430936 ◽

2021 ◽

Author(s):

Max van den Boom ◽

Kai J. Miller ◽

Nicholas M. Gregg ◽

Gabriela Ojeda ◽

Kendall H. Lee ◽

...

Keyword(s):

Frequency Band ◽

Sensorimotor Cortex ◽

Hand Movement ◽

Phantom Limb Pain ◽

Phantom Limb ◽

Support Vector ◽

Finger Movements ◽

Prosthetic Devices ◽

Neural Prosthetic ◽

Brainstem Stroke

AbstractElectrophysiological signals in the human motor system may change in different ways after deafferentation, with some studies emphasizing reorganization while others propose retained physiology. Understanding whether motor electrophysiology is retained over longer periods of time can be invaluable for patients with paralysis (e.g. ALS or brainstem stroke) when signals from sensorimotor areas may be used for communication or control over neural prosthetic devices. In addition, a maintained electrophysiology can potentially benefit the treatment of phantom limb pains through prolonged use of these signals in a brain-machine interface (BCI).Here, we were presented with the unique opportunity to investigate the physiology of the sensorimotor cortex in a patient with an amputated arm using electrocorticographic (ECoG) measurements. While implanted with an ECoG grid for clinical evaluation of electrical stimulation for phantom limb pain, the patient performed attempted finger movements with the contralateral (lost) hand and executed finger movements with the ipsilateral (healthy) hand.The electrophysiology of the sensorimotor cortex contralateral to the amputated hand remained very similar to that of hand movement in healthy people, with a spatially focused increase of high-frequency band (65-175Hz; HFB) power over the hand region and a distributed decrease in low-frequency band (15-28Hz; LFB) power. The representation of the three different fingers (thumb, index and little) remained intact and HFB patterns could be decoded using support vector learning at single-trial classification accuracies of >90%, based on the first 1-3s of the HFB response. These results demonstrate that hand representations are largely retained in the motor cortex. The intact physiological response of the amputated hand, the high distinguishability of the fingers and fast temporal peak are encouraging for neural prosthetic devices that target the sensorimotor cortex.

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Turning Neural Prosthetics Into Viable Products

Frontiers in Robotics and AI ◽

10.3389/frobt.2021.754114 ◽

2021 ◽

Vol 8 ◽

Author(s):

Gerald E. Loeb ◽

Frances J. Richmond

Keyword(s):

Intellectual Property ◽

De Novo ◽

Class Iii ◽

Prosthetic Devices ◽

Neural Prosthetic ◽

Novel Treatments ◽

Track Record ◽

Computer Interfaces ◽

Guidance Documents ◽

Novel Applications

Academic researchers concentrate on the scientific and technological feasibility of novel treatments. Investors and commercial partners, however, understand that success depends even more on strategies for regulatory approval, reimbursement, marketing, intellectual property protection and risk management. These considerations are critical for technologically complex and highly invasive treatments that entail substantial costs and risks in small and heterogeneous patient populations. Most implanted neural prosthetic devices for novel applications will be in FDA Device Class III, for which guidance documents have been issued recently. Less invasive devices may be eligible for the recently simplified “de novo” submission routes. We discuss typical timelines and strategies for integrating the regulatory path with approval for reimbursement, securing intellectual property and funding the enterprise, particularly as they might apply to implantable brain-computer interfaces for sensorimotor disabilities that do not yet have a track record of approved products.

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Advanced Prosthetics, Neuroprosthetics, and Artificial Limbs

Enhancing the Human Experience through Assistive Technologies and E-Accessibility - Advances in Medical Technologies and Clinical Practice ◽

10.4018/978-1-4666-6130-1.ch005 ◽

2014 ◽

pp. 63-77

Keyword(s):

Cochlear Implants ◽

Artificial Limbs ◽

Artificial Retina ◽

Prosthetic Devices ◽

Artificial Hand ◽

And Robotics

An area of research that is very close to invasive BCI presented earlier is the area of neuroprosthetics. This involves the use of invasive BCI systems aiming to control prosthetic devices (i.e. an artificial hand) or help in rehabilitation of human senses such as seeing and hearing. The most well-known advances in neuroprosthetics are in the area of seeing, the case of the artificial retina, the case of cochlear implants for hearing, and the use of thought-controlled artificial limbs. Building upon knowledge and developments presented in the previous chapters about BCI and robotics, this chapter combines these technologies and discusses advances and challenges to be met in the areas of advanced prosthetics, neuroprosthetics, and artificial limbs.

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