Totally Implantable Bidirectional Neural Prostheses: A Flexible Platform for Innovation in Neuromodulation.

Implantable neural prostheses are in widespread use for treating a variety of brain disorders. Until recently, most implantable brain devices have been unidirectional, either delivering neurostimulation without brain sensing, or sensing brain activity to drive external effectors without a stimulation component. Further, many neural interfaces that incorporate a sensing function have relied on hardwired connections, such that subjects are tethered to external computers and cannot move freely. A new generation of neural prostheses has become available, that are both bidirectional (stimulate as well as record brain activity) and totally implantable (no externalized connections). These devices provide an opportunity for discovering the circuit basis for neuropsychiatric disorders, and to prototype personalized neuromodulation therapies that selectively interrupt neural activity underlying specific signs and symptoms

TiO2 surfaces support neuron growth during electric field stimulation

The authors are grateful to Francisco Almendros and Ismael Santamaría for help in preparation of the TiO2 substrates. We acknowledge the European Project NERBIOS (NEST/STREP (FP6), 028473-2) for financial support. Maria Canillas acknowledges the JAE-CSIC program of her PhD scholarship. Berta Moreno acknowledges the Fondo Social Europeo and the CSIC for the funding of her JAE Doc contract. Ann Rajnicek acknowledges financial support from The Development Trust at the University of Aberdeen to the Aberdeen Spinal Research Group, including support from the Scottish Rugby Union.Peer reviewedPostprin

Electrolysis-based Parylene Balloon Actuators for Movable Neural Probes

In order to track a specific neuron and keep good sampling neural signals during chronic implantation, the neural probes are highly desired to have moving capability. This paper presents a novel electrolysis-based parylene balloon actuator fabricated with MEMS technology. The actuator is integrated with silicon probe to make it movable. A new fabrication technology has been developed to build a parylene balloon structure with silicon spring structure, electrolysis electrodes and electrolyte inside. By applying little current to electrolysis electrodes, high pressure is generated inside the parylene balloon by electrolysis. The spring structure is stretched with the parylene balloon expansion. Therefore the neural probe is moved by the actuation. The electrolysis actuator can generate large stain and pressure, requires modest electrical power and produces minimal heat. Due to the large volume expansion obtained via electrolysis, the small actuator can create a large force. The new electrolysis actuators for movable neural probes have been fabricated and validated

Analysis of current density and related parameters in spinal cord stimulation

A volume conductor model of the spinal cord and surrounding anatomical structures is used to calculate current (and current density) charge per pulse, and maximum charge density per pulse at the contact surface of the electrode in the dorsal epidural space, in the dorsal columns of the spinal cord and in the dorsal roots. The effects of various contact configurations (mono-, bi-, and tripole), contact area and spacing, pulsewidth and distance between contacts and spinal cord on these electrical parameters were investigated under conditions similar to those in clinical spinal cord stimulation. At the threshold stimulus of a large dorsal column fiber, current density and charge density per pulse at the contact surface were found to be highest (1.9·105 ¿A/cm2 and 39.1 ¿C/cm2 ·p, respectively) when the contact surface was only 0.7 mm 2. When stimulating with a pulse of 500 ¿s, highest charge per pulse (0.92 ¿C/p), and the largest charge density per pulse in the dorsal columns (1.59 ¿C/cm2·p) occurred. It is concluded that of all stimulation parameters that can be selected freely, only pulsewidth affects the charge and charge density per pulse in the nervous tissue, whereas both pulsewidth and contact area strongly affect these parameters in the nonnervous tissue neighboring the electrode contact

A perspective on the control of FES-supported standing

This special section is about the control of electrical stimulators to restore standing functions to paraplegics. It addresses several important topics regarding the interactions of the intact central nervous systems (CNS) with the artificial control system. The topics are as follows: how paraplegics use their arms to help themselves stand up with functional electrical stimulation (FES); the user-driven artificial control of FESsupported standing up; a controller which is promising for the control of sitting down; the application of reinforcement machine learning for the controllers of standing up; arms-free\ud standing with voluntary upper body balancing and artificially controlled ankle stiffness; and cognitive feedback in balancing. This Commentary introduces the papers in this section and relates them to earlier research

Utilizing Brain-computer Interfacing to Control Neuroprosthetic Devices

Advances in neuroprosthetics in recent years have made an enormous impact on the quality of life for many people with disabilities, helping them regain the functionality of damaged or impaired abilities. One of the main hurdles to regaining full functionality regarding neuroprosthetics is the integration between the neural prosthetic device and the method in which the neural prosthetic device is controlled or manipulated to function correctly and efficiently. One of the most promising methods for integrating neural prosthetics to an efficient method of control is through Brian-computer Interfacing (BCI). With this method, the neuroprosthetic device is integrated into the human brain through the use of a specialized computer, which allows for users of neuroprosthetic devices to control the devices in the same way that they would control a normally working human function- with their mind. There are both invasive and non-invasive methods to implement Brain-computer Interfacing, both of which involve the process of acquiring a brain signal, processing the signal, and finally providing a usable device output. There are several examples of integration between Brain-computer Interfacing and neural prosthetics that are currently being researched. Many challenges must be overcome before a widespread clinical application of integration between Brain-computer Interfaces and neural prosthetics becomes a reality, but current research continues to provide promising advancement toward making this technology available as a means for people to regain lost functionality

Getting Better Signals Out of the Brain:Decoding Algorithms and Autonomous Electrodes

Summary form only given. This talk summarized our efforts to develop new technologies whose aim is to improve the quality and quantity of the information derived from extracellular recordings. This work is motivated by ongoing activities at Caltech to develop neural prostheses based on the brain's parietal reach region (PRR). The talk first reviewed our progress towards developing a functioning neural prosthesis in order to motivate the need to develop long-lasting chronic interfaces between electrodes and neurons. The second half of the talk focuses on our efforts to develop a new class of "movable" electrodes that autonomously isolate a neural cell so as to optimize the recorded signal quality, and then maintain optimal signal quality using feedback. Such devices are likely to improve the reliability and robustness of future chronic neural prosthetic systems. We also summarized current research in neural decoding algorithms, whose aim is to extract the maximum information content from the recorded signals

Optimal control of ankle joint moment: Toward unsupported standing in paraplegia

This paper considers part of the problem of how to provide unsupported standing for paraplegics by feedback control. In this work our overall objective is to stabilize the subject by stimulation only of his ankle joints while the other joints are braced, Here, we investigate the problem of ankle joint moment control. The ankle plantarflexion muscles are first identified with pseudorandom binary sequence (PRBS) signals, periodic sinusoidal signals, and twitches. The muscle is modeled in Hammerstein form as a static recruitment nonlinearity followed by a linear transfer function. A linear-quadratic-Gaussian (LQG)-optimal controller design procedure for ankle joint moment was proposed based on the polynomial equation formulation, The approach was verified by experiments in the special Wobbler apparatus with a neurologically intact subject, and these experimental results are reported. The controller structure is formulated in such a way that there are only two scalar design parameters, each of which has a clear physical interpretation. This facilitates fast controller synthesis and tuning in the laboratory environment. Experimental results show the effects of the controller tuning parameters: the control weighting and the observer response time, which determine closed-loop properties. Using these two parameters the tradeoff between disturbance rejection and measurement noise sensitivity can be straightforwardly balanced while maintaining a desired speed of tracking. The experimentally measured reference tracking, disturbance rejection, and noise sensitivity are good and agree with theoretical expectations

Dual-side and three-dimensional microelectrode arrays fabricated from ultra-thin silicon substrates

A method for fabricating planar implantable microelectrode arrays was demonstrated using a process that relied on ultra-thin silicon substrates, which ranged in thickness from 25 to 50 µm. The challenge of handling these fragile materials was met via a temporary substrate support mechanism. In order to compensate for putative electrical shielding of extracellular neuronal fields, separately addressable electrode arrays were defined on each side of the silicon device. Deep reactive ion etching was employed to create sharp implantable shafts with lengths of up to 5 mm. The devices were flip-chip bonded onto printed circuit boards (PCBs) by means of an anisotropic conductive adhesive film. This scalable assembly technique enabled three-dimensional (3D) integration through formation of stacks of multiple silicon and PCB layers. Simulations and measurements of microelectrode noise appear to suggest that low impedance surfaces, which could be formed by electrodeposition of gold or other materials, are required to ensure an optimal signal-to-noise ratio as well a low level of interchannel crosstalk