Vertically aligned carbon nanofiber as nano-neuron interface for monitoring neural function.

PubMed

Yu, Zhe; McKnight, Timothy E; Ericson, M Nance; Melechko, Anatoli V; Simpson, Michael L; Morrison, Barclay

2012-05-01

Neural chips, which are capable of simultaneous multisite neural recording and stimulation, have been used to detect and modulate neural activity for almost thirty years. As neural interfaces, neural chips provide dynamic functional information for neural decoding and neural control. By improving sensitivity and spatial resolution, nano-scale electrodes may revolutionize neural detection and modulation at cellular and molecular levels as nano-neuron interfaces. We developed a carbon-nanofiber neural chip with lithographically defined arrays of vertically aligned carbon nanofiber electrodes and demonstrated its capability of both stimulating and monitoring electrophysiological signals from brain tissues in vitro and monitoring dynamic information of neuroplasticity. This novel nano-neuron interface may potentially serve as a precise, informative, biocompatible, and dual-mode neural interface for monitoring of both neuroelectrical and neurochemical activity at the single-cell level and even inside the cell. The authors demonstrate the utility of a neural chip with lithographically defined arrays of vertically aligned carbon nanofiber electrodes. The new device can be used to stimulate and/or monitor signals from brain tissue in vitro and for monitoring dynamic information of neuroplasticity both intracellularly and at the single cell level including neuroelectrical and neurochemical activities. Copyright © 2012 Elsevier Inc. All rights reserved.

Recent advances in neural dust: towards a neural interface platform.

PubMed

Neely, Ryan M; Piech, David K; Santacruz, Samantha R; Maharbiz, Michel M; Carmena, Jose M

2018-06-01

The neural dust platform uses ultrasonic power and communication to enable a scalable, wireless, and batteryless system for interfacing with the nervous system. Ultrasound offers several advantages over alternative wireless approaches, including a safe method for powering and communicating with sub mm-sized devices implanted deep in tissue. Early studies demonstrated that neural dust motes could wirelessly transmit high-fidelity electrophysiological data in vivo, and that theoretically, this system could be miniaturized well below the mm-scale. Future developments are focused on further minimization of the platform, better encapsulation methods as a path towards truly chronic neural interfaces, improved delivery mechanisms, stimulation capabilities, and finally refinements to enable deployment of neural dust in the central nervous system. Copyright © 2017. Published by Elsevier Ltd.

Functional and Histological Effects of Chronic Neural Electrode Implantation.

PubMed

Sahyouni, Ronald; Chang, David T; Moshtaghi, Omid; Mahmoodi, Amin; Djalilian, Hamid R; Lin, Harrison W

2017-04-01

Permanent injury to the cranial nerves can often result in a substantial reduction in quality of life. Novel and innovative interventions can help restore form and function in nerve paralysis, with bioelectric interfaces among the more promising of these approaches. The foreign body response is an important consideration for any bioelectric device as it influences the function and effectiveness of the implant. The purpose of this review is to describe tissue and functional effects of chronic neural implantation among the different categories of neural implants and highlight advances in peripheral and cranial nerve stimulation. Data Sources : PubMed, IEEE, and Web of Science literature search. Review Methods : A review of the current literature was conducted to examine functional and histologic effects of bioelectric interfaces for neural implants. Bioelectric devices can be characterized as intraneural, epineural, perineural, intranuclear, or cortical depending on their placement relative to nerves and neuronal cell bodies. Such devices include nerve-specific stimulators, neuroprosthetics, brainstem implants, and deep brain stimulators. Regardless of electrode location and interface type, acute and chronic histological, macroscopic and functional changes can occur as a result of both passive and active tissue responses to the bioelectric implant. A variety of chronically implantable electrodes have been developed to treat disorders of the peripheral and cranial nerves, to varying degrees of efficacy. Consideration and mitigation of detrimental effects at the neural interface with further optimization of functional nerve stimulation will facilitate the development of these technologies and translation to the clinic. 3.

Multi-scale, multi-modal analysis uncovers complex relationship at the brain tissue-implant neural interface: new emphasis on the biological interface

NASA Astrophysics Data System (ADS)

Michelson, Nicholas J.; Vazquez, Alberto L.; Eles, James R.; Salatino, Joseph W.; Purcell, Erin K.; Williams, Jordan J.; Cui, X. Tracy; Kozai, Takashi D. Y.

2018-06-01

Objective. Implantable neural electrode devices are important tools for neuroscience research and have an increasing range of clinical applications. However, the intricacies of the biological response after implantation, and their ultimate impact on recording performance, remain challenging to elucidate. Establishing a relationship between the neurobiology and chronic recording performance is confounded by technical challenges related to traditional electrophysiological, material, and histological limitations. This can greatly impact the interpretations of results pertaining to device performance and tissue health surrounding the implant. Approach. In this work, electrophysiological activity and immunohistological analysis are compared after controlling for motion artifacts, quiescent neuronal activity, and material failure of devices in order to better understand the relationship between histology and electrophysiological outcomes. Main results. Even after carefully accounting for these factors, the presence of viable neurons and lack of glial scarring does not convey single unit recording performance. Significance. To better understand the biological factors influencing neural activity, detailed cellular and molecular tissue responses were examined. Decreases in neural activity and blood oxygenation in the tissue surrounding the implant, shift in expression levels of vesicular transporter proteins and ion channels, axon and myelin injury, and interrupted blood flow in nearby capillaries can impact neural activity around implanted neural interfaces. Combined, these tissue changes highlight the need for more comprehensive, basic science research to elucidate the relationship between biology and chronic electrophysiology performance in order to advance neural technologies.

[Neural engineering and neural prostheses].

PubMed

Gao, Shang-Kai; Zhang, Zhi-Guang; Gao, Xiao-Rong; Hong, Bo; Yang, Fu-Sheng

2006-03-01

The motivation of the brain-computer interface (BCI) research and its potential applications are introduced in this paper. Some of the problems in BCI-based medical device developments are also discussed.

Integration of High-Charge-Injection-Capacity Electrodes onto Polymer Softening Neural Interfaces.

PubMed

Arreaga-Salas, David E; Avendaño-Bolívar, Adrian; Simon, Dustin; Reit, Radu; Garcia-Sandoval, Aldo; Rennaker, Robert L; Voit, Walter

2015-12-09

Softening neural interfaces are implanted stiff to enable precise insertion, and they soften in physiological conditions to minimize modulus mismatch with tissue. In this work, a high-charge-injection-capacity iridium electrode fabrication process is detailed. For the first time, this process enables integration of iridium electrodes onto softening substrates using photolithography to define all features in the device. Importantly, no electroplated layers are utilized, leading to a highly scalable method for consistent device fabrication. The iridium electrode is metallically bonded to the gold conductor layer, which is covalently bonded to the softening substrate via sulfur-based click chemistry. The resulting shape-memory polymer neural interfaces can deliver more than 2 billion symmetric biphasic pulses (100 μs/phase), with a charge of 200 μC/cm(2) and geometric surface area (GSA) of 300 μm(2). A transfer-by-polymerization method is used in combination with standard semiconductor processing techniques to fabricate functional neural probes onto a thiol-ene-based, thin film substrate. Electrical stability is tested under simulated physiological conditions in an accelerated electrical aging paradigm with periodic measurement of electrochemical impedance spectra (EIS) and charge storage capacity (CSC) at various intervals. Electrochemical characterization and both optical and scanning electron microscopy suggest significant breakdown of the 600 nm-thick parylene-C insulation, although no delamination of the conductors or of the final electrode interface was observed. Minor cracking at the edges of the thin film iridium electrodes was occasionally observed. The resulting devices will provide electrical recording and stimulation of the nervous system to better understand neural wiring and timing, to target treatments for debilitating diseases, and to give neuroscientists spatially selective and specific tools to interact with the body. This approach has uses for cochlear implants, nerve cuff electrodes, penetrating cortical probes, spinal stimulators, blanket electrodes for the gut, stomach, and visceral organs and a host of other custom nerve-interfacing devices.

Graphene-based carbon-layered electrode array technology for neural imaging and optogenetic applications

PubMed Central

Park, Dong-Wook; Schendel, Amelia A.; Mikael, Solomon; Brodnick, Sarah K.; Richner, Thomas J.; Ness, Jared P.; Hayat, Mohammed R.; Atry, Farid; Frye, Seth T.; Pashaie, Ramin; Thongpang, Sanitta; Ma, Zhenqiang; Williams, Justin C.

2014-01-01

Neural micro-electrode arrays that are transparent over a broad wavelength spectrum from ultraviolet to infrared could allow for simultaneous electrophysiology and optical imaging, as well as optogenetic modulation of the underlying brain tissue. The long-term biocompatibility and reliability of neural micro-electrodes also require their mechanical flexibility and compliance with soft tissues. Here we present a graphene-based, carbon-layered electrode array (CLEAR) device, which can be implanted on the brain surface in rodents for high-resolution neurophysiological recording. We characterize optical transparency of the device at >90% transmission over the ultraviolet to infrared spectrum and demonstrate its utility through optical interface experiments that use this broad spectrum transparency. These include optogenetic activation of focal cortical areas directly beneath electrodes, in vivo imaging of the cortical vasculature via fluorescence microscopy and 3D optical coherence tomography. This study demonstrates an array of interfacing abilities of the CLEAR device and its utility for neural applications. PMID:25327513

Nanomaterials at the neural interface.

PubMed

Scaini, Denis; Ballerini, Laura

2018-06-01

Interfacing the nervous system with devices able to efficiently record or modulate the electrical activity of neuronal cells represents the underlying foundation of future theranostic applications in neurology and of current openings in neuroscience research. These devices, usually sensing cell activity via microelectrodes, should be characterized by safe working conditions in the biological milieu together with a well-controlled operation-life. The stable device/neuronal electrical coupling at the interface requires tight interactions between the electrode surface and the cell membrane. This neuro-electrode hybrid represents the hyphen between the soft nature of neural tissue, generating electrical signals via ion motions, and the rigid realm of microelectronics and medical devices, dealing with electrons in motion. Efficient integration of these entities is essential for monitoring, analyzing and controlling neuronal signaling but poses significant technological challenges. Improving the cell/electrode interaction and thus the interface performance requires novel engineering of (nano)materials: tuning at the nanoscale electrode's properties may lead to engineer interfacing probes that better camouflaged with their biological target. In this brief review, we highlight the most recent concepts in nanotechnologies and nanomaterials that might help reducing the mismatch between tissue and electrode, focusing on the device's mechanical properties and its biological integration with the tissue. Copyright © 2017 Elsevier Ltd. All rights reserved.

This Neural Implant is designed to be implanted in the Human Central and Nervous System

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

A new class of neural implants being developed at the Livermore Lab are the first clinical quality devices capable of two-way conversations with the human nervous systems. Unlike existing interfaces that only sense or only stimulate, these devices are capable of stimulating and sensing using both electric and chemical signals.

This Neural Implant is designed to be implanted in the Human Central and Nervous System

ScienceCinema

None

2018-06-12

A new class of neural implants being developed at the Livermore Lab are the first clinical quality devices capable of two-way conversations with the human nervous systems. Unlike existing interfaces that only sense or only stimulate, these devices are capable of stimulating and sensing using both electric and chemical signals.

Elastomeric and soft conducting microwires for implantable neural interfaces

PubMed Central

Kolarcik, Christi L.; Luebben, Silvia D.; Sapp, Shawn A.; Hanner, Jenna; Snyder, Noah; Kozai, Takashi D.Y.; Chang, Emily; Nabity, James A.; Nabity, Shawn T.; Lagenaur, Carl F.; Cui, X. Tracy

2015-01-01

Current designs for microelectrodes used for interfacing with the nervous system elicit a characteristic inflammatory response that leads to scar tissue encapsulation, electrical insulation of the electrode from the tissue and ultimately failure. Traditionally, relatively stiff materials like tungsten and silicon are employed which have mechanical properties several orders of magnitude different from neural tissue. This mechanical mismatch is thought to be a major cause of chronic inflammation and degeneration around the device. In an effort to minimize the disparity between neural interface devices and the brain, novel soft electrodes consisting of elastomers and intrinsically conducting polymers were fabricated. The physical, mechanical and electrochemical properties of these materials were extensively characterized to identify the formulations with the optimal combination of parameters including Young’s modulus, elongation at break, ultimate tensile strength, conductivity, impedance and surface charge injection. Our final electrode has a Young’s modulus of 974 kPa which is five orders of magnitude lower than tungsten and significantly lower than other polymer-based neural electrode materials. In vitro cell culture experiments demonstrated the favorable interaction between these soft materials and neurons, astrocytes and microglia, with higher neuronal attachment and a two-fold reduction in inflammatory microglia attachment on soft devices compared to stiff controls. Surface immobilization of neuronal adhesion proteins on these microwires further improved the cellular response. Finally, in vivo electrophysiology demonstrated the functionality of the elastomeric electrodes in recording single unit activity in the rodent visual cortex. The results presented provide initial evidence in support of the use of soft materials in neural interface applications. PMID:25993261

A Wirelessly Powered Micro-Spectrometer for Neural Probe-Pin Device

NASA Technical Reports Server (NTRS)

Choi, Sang H.; Kim, Min Hyuck; Song, Kyo D.; Yoon, Hargsoon; Lee, Uhn

2015-01-01

Treatment of neurological anomalies, places stringent demands on device functionality and size. A micro-spectrometer has been developed for use as an implantable neural probe to monitor neuro-chemistry in synapses. The microspectrometer, based on a NASA-invented miniature Fresnel grating, is capable of differentiating the emission spectra from various brain tissues. The micro-spectrometer meets the size requirements, and is able to probe the neuro-chemistry and suppression voltage typically associated with a neural anomaly. This neural probe-pin device (PPD) is equipped with wireless power technology (WPT) enabling operation in a continuous manner without requiring an implanted battery. The implanted neural PPD, together with a neural electronics interface and WPT, allow real-time measurement and control/feedback for remediation of neural anomalies. The design and performance of the combined PPD/WPT device for monitoring dopamine in a rat brain will be presented to demonstrate the current level of development. Future work on this device will involve the addition of an embedded expert system capable of performing semi-autonomous management of neural functions through a routine of sensing, processing, and control.

A wirelessly powered microspectrometer for neural probe-pin device

NASA Astrophysics Data System (ADS)

Choi, Sang H.; Kim, Min H.; Song, Kyo D.; Yoon, Hargsoon; Lee, Uhn

2015-12-01

Treatment of neurological anomalies, whether done invasively or not, places stringent demands on device functionality and size. We have developed a micro-spectrometer for use as an implantable neural probe to monitor neuro-chemistry in synapses. The micro-spectrometer, based on a NASA-invented miniature Fresnel grating, is capable of differentiating the emission spectra from various brain tissues. The micro-spectrometer meets the size requirements, and is able to probe the neuro-chemistry and suppression voltage typically associated with a neural anomaly. This neural probe-pin device (PPD) is equipped with wireless power technology (WPT) to enable operation in a continuous manner without requiring an implanted battery. The implanted neural PPD, together with a neural electronics interface and WPT, enable real-time measurement and control/feedback for remediation of neural anomalies. The design and performance of the combined PPD/WPT device for monitoring dopamine in a rat brain will be presented to demonstrate the current level of development. Future work on this device will involve the addition of an embedded expert system capable of performing semi-autonomous management of neural functions through a routine of sensing, processing, and control.

Unlocking the brain's mysteries: Meet the bioengineers behind next-generation neural devices

ScienceCinema

Pannu, Sat; Shah, Kedar; Tolosa, Vanessa; Tooker, Angela

2018-01-16

Bioengineers in the Neural Technologies Group at Lawrence Livermore are creating the next generation of clinical- and research-quality neural interfaces. The goal is to gain a fundamental understanding of neuroscience, treat a variety of debilitating neurological disorders (such as Parkinson's, depression, and epilepsy), and restore lost neural functions such as sight, hearing, and mobility.

Unlocking the brain's mysteries: Meet the bioengineers behind next-generation neural devices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pannu, Sat; Shah, Kedar; Tolosa, Vanessa

Bioengineers in the Neural Technologies Group at Lawrence Livermore are creating the next generation of clinical- and research-quality neural interfaces. The goal is to gain a fundamental understanding of neuroscience, treat a variety of debilitating neurological disorders (such as Parkinson's, depression, and epilepsy), and restore lost neural functions such as sight, hearing, and mobility.

Strategies for improving neural signal detection using a neural-electronic interface.

PubMed

Szlavik, Robert B

2003-03-01

There have been various theoretical and experimental studies presented in the literature that focus on interfacing neurons with discrete electronic devices, such as transistors. From both a theoretical and experimental perspective, these studies have emphasized the variability in the characteristics of the detected action potential from the nerve cell. The demonstrated lack of reproducible fidelity of the nerve cell action potential at the device junction would make it impractical to implement these devices in any neural prosthetic application where reliable detection of the action potential was a prerequisite. In this study, the effects of several different physical parameters on the fidelity of the detected action potential at the device junction are investigated and discussed. The impact of variations in the extracellular resistivity, which directly affects the junction seal resistance, is studied along with the impact of variable nerve cell membrane capacitance and variations in the injected charge. These parameters are discussed in the context of their suitability to design manipulation for the purpose of improving the fidelity of the detected neural action potential. In addition to investigating the effects of variations in these parameters, the applicability of the linear equivalent circuit approach to calculating the junction potential is investigated.

Recent Advances in Neural Electrode-Tissue Interfaces.

PubMed

Woeppel, Kevin; Yang, Qianru; Cui, Xinyan Tracy

2017-12-01

Neurotechnology is facing an exponential growth in the recent decades. Neural electrode-tissue interface research has been well recognized as an instrumental component of neurotechnology development. While satisfactory long-term performance was demonstrated in some applications, such as cochlear implants and deep brain stimulators, more advanced neural electrode devices requiring higher resolution for single unit recording or microstimulation still face significant challenges in reliability and longevity. In this article, we review the most recent findings that contribute to our current understanding of the sources of poor reliability and longevity in neural recording or stimulation, including the material failure, biological tissue response and the interplay between the two. The newly developed characterization tools are introduced from electrophysiology models, molecular and biochemical analysis, material characterization to live imaging. The effective strategies that have been applied to improve the interface are also highlighted. Finally, we discuss the challenges and opportunities in improving the interface and achieving seamless integration between the implanted electrodes and neural tissue both anatomically and functionally.

An externally head-mounted wireless neural recording device for laboratory animal research and possible human clinical use.

PubMed

Yin, Ming; Li, Hao; Bull, Christopher; Borton, David A; Aceros, Juan; Larson, Lawrence; Nurmikko, Arto V

2013-01-01

In this paper we present a new type of head-mounted wireless neural recording device in a highly compact package, dedicated for untethered laboratory animal research and designed for future mobile human clinical use. The device, which takes its input from an array of intracortical microelectrode arrays (MEA) has ninety-seven broadband parallel neural recording channels and was integrated on to two custom designed printed circuit boards. These house several low power, custom integrated circuits, including a preamplifier ASIC, a controller ASIC, plus two SAR ADCs, a 3-axis accelerometer, a 48MHz clock source, and a Manchester encoder. Another ultralow power RF chip supports an OOK transmitter with the center frequency tunable from 3GHz to 4GHz, mounted on a separate low loss dielectric board together with a 3V LDO, with output fed to a UWB chip antenna. The IC boards were interconnected and packaged in a polyether ether ketone (PEEK) enclosure which is compatible with both animal and human use (e.g. sterilizable). The entire system consumes 17mA from a 1.2Ahr 3.6V Li-SOCl2 1/2AA battery, which operates the device for more than 2 days. The overall system includes a custom RF receiver electronics which are designed to directly interface with any number of commercial (or custom) neural signal processors for multi-channel broadband neural recording. Bench-top measurements and in vivo testing of the device in rhesus macaques are presented to demonstrate the performance of the wireless neural interface.

Conjugated Polymer Actuators for Articulating Neural Probes and Electrode Interfaces

NASA Astrophysics Data System (ADS)

Daneshvar, Eugene Dariush

This thesis investigated the potential use of polypyrrole (PPy) doped with dodecylbenzenesulfonate (DBS) to controllably articulate (bend or guide) flexible neural probes and electrodes. PPy(DBS) actuation performance was characterized in the ionic mixture and temperature found in the brain. Nearly all the ions in aCSF were exchanged into the PPy---the cations Na +, K+, Mg2+, Ca2+, as well as the anion PO43-; Cl- was not present. Nevertheless, deflections in aCSF were comparable to those in NaDBS and they were monotonic with oxidation level: strain increased upon reduction, with no reversal of motion despite the mixture of ionic charges and valences being exchanged. Actuation depended on temperature. Upon warming, the cyclic voltammograms showed additional peaks and an increase of 70% in the consumed charge. Actuation strain was monotonic under these conditions, demonstrating that conducting polymer actuators can indeed be used for neural interface and neural probe applications. In addition, a novel microelectro-mechanical system (MEMS) was developed to measure previously disregarded residual stress in a bilayer actuator. Residual stresses are a major concern for MEMS devices as that they can dramatically influence their yield and functionality. This device introduced a new technique to measure micro-scaled actuation forces that may be useful for characterization of other MEMS actuators. Finally, a functional movable parylene-based neural electrode prototype was developed. Employing PPy(DBS) actuators, electrode projections were successfully controlled to either remain flat or actuate out-of-plane and into a brain phantom during insertion. An electrode projection 800 microm long and 50 microm wide was able to deflect almost 800 microm away from the probe substrate. Applications that do not require insertion into tissue may also benefit from the electrode projections described here. Implantable neural interface devices are a critical component to a broad class of emerging neuroprosthetic and neurostimulation systems aimed to restore functionality, or abate symptoms related to physical impairments, loss of sensory abilities, and neurological disorders. The therapeutic outcome and performance of these systems hinge to a large degree on the proximity, size, and placement of the device or interface with respect to the targeted neurons or tissue.

Design and Evaluation of a Cable-Driven fMRI-Compatible Haptic Interface to Investigate Precision Grip Control

PubMed Central

Vigaru, Bogdan; Sulzer, James; Gassert, Roger

2016-01-01

Our hands and fingers are involved in almost all activities of daily living and, as such, have a disproportionately large neural representation. Functional magnetic resonance imaging investigations into the neural control of the hand have revealed great advances, but the harsh MRI environment has proven to be a challenge to devices capable of delivering a large variety of stimuli necessary for well-controlled studies. This paper presents a fMRI-compatible haptic interface to investigate the neural mechanisms underlying precision grasp control. The interface, located at the scanner bore, is controlled remotely through a shielded electromagnetic actuation system positioned at the end of the scanner bed and then through a high stiffness, low inertia cable transmission. We present the system design, taking into account requirements defined by the biomechanics and dynamics of the human hand, as well as the fMRI environment. Performance evaluation revealed a structural stiffness of 3.3 N/mm, renderable forces up to 94 N, and a position control bandwidth of at least 19 Hz. MRI-compatibility tests showed no degradation in the operation of the haptic interface or the image quality. A preliminary fMRI experiment during a pilot study validated the usability of the haptic interface, illustrating the possibilities offered by this device. PMID:26441454

Optimizing the Usability of Brain-Computer Interfaces.

PubMed

Zhang, Yin; Chase, Steve M

2018-05-01

Brain-computer interfaces are in the process of moving from the laboratory to the clinic. These devices act by reading neural activity and using it to directly control a device, such as a cursor on a computer screen. An open question in the field is how to map neural activity to device movement in order to achieve the most proficient control. This question is complicated by the fact that learning, especially the long-term skill learning that accompanies weeks of practice, can allow subjects to improve performance over time. Typical approaches to this problem attempt to maximize the biomimetic properties of the device in order to limit the need for extensive training. However, it is unclear if this approach would ultimately be superior to performance that might be achieved with a nonbiomimetic device once the subject has engaged in extended practice and learned how to use it. Here we approach this problem using ideas from optimal control theory. Under the assumption that the brain acts as an optimal controller, we present a formal definition of the usability of a device and show that the optimal postlearning mapping can be written as the solution of a constrained optimization problem. We then derive the optimal mappings for particular cases common to most brain-computer interfaces. Our results suggest that the common approach of creating biomimetic interfaces may not be optimal when learning is taken into account. More broadly, our method provides a blueprint for optimal device design in general control-theoretic contexts.

Neural control of cursor trajectory and click by a human with tetraplegia 1000 days after implant of an intracortical microelectrode array

NASA Astrophysics Data System (ADS)

Simeral, J. D.; Kim, S.-P.; Black, M. J.; Donoghue, J. P.; Hochberg, L. R.

2011-04-01

The ongoing pilot clinical trial of the BrainGate neural interface system aims in part to assess the feasibility of using neural activity obtained from a small-scale, chronically implanted, intracortical microelectrode array to provide control signals for a neural prosthesis system. Critical questions include how long implanted microelectrodes will record useful neural signals, how reliably those signals can be acquired and decoded, and how effectively they can be used to control various assistive technologies such as computers and robotic assistive devices, or to enable functional electrical stimulation of paralyzed muscles. Here we examined these questions by assessing neural cursor control and BrainGate system characteristics on five consecutive days 1000 days after implant of a 4 × 4 mm array of 100 microelectrodes in the motor cortex of a human with longstanding tetraplegia subsequent to a brainstem stroke. On each of five prospectively-selected days we performed time-amplitude sorting of neuronal spiking activity, trained a population-based Kalman velocity decoding filter combined with a linear discriminant click state classifier, and then assessed closed-loop point-and-click cursor control. The participant performed both an eight-target center-out task and a random target Fitts metric task which was adapted from a human-computer interaction ISO standard used to quantify performance of computer input devices. The neural interface system was further characterized by daily measurement of electrode impedances, unit waveforms and local field potentials. Across the five days, spiking signals were obtained from 41 of 96 electrodes and were successfully decoded to provide neural cursor point-and-click control with a mean task performance of 91.3% ± 0.1% (mean ± s.d.) correct target acquisition. Results across five consecutive days demonstrate that a neural interface system based on an intracortical microelectrode array can provide repeatable, accurate point-and-click control of a computer interface to an individual with tetraplegia 1000 days after implantation of this sensor.

Neural control of cursor trajectory and click by a human with tetraplegia 1000 days after implant of an intracortical microelectrode array

PubMed Central

Simeral, J D; Kim, S-P; Black, M J; Donoghue, J P; Hochberg, L R

2013-01-01

The ongoing pilot clinical trial of the BrainGate neural interface system aims in part to assess the feasibility of using neural activity obtained from a small-scale, chronically implanted, intracortical microelectrode array to provide control signals for a neural prosthesis system. Critical questions include how long implanted microelectrodes will record useful neural signals, how reliably those signals can be acquired and decoded, and how effectively they can be used to control various assistive technologies such as computers and robotic assistive devices, or to enable functional electrical stimulation of paralyzed muscles. Here we examined these questions by assessing neural cursor control and BrainGate system characteristics on five consecutive days 1000 days after implant of a 4 × 4 mm array of 100 microelectrodes in the motor cortex of a human with longstanding tetraplegia subsequent to a brainstem stroke. On each of five prospectively-selected days we performed time-amplitude sorting of neuronal spiking activity, trained a population-based Kalman velocity decoding filter combined with a linear discriminant click state classifier, and then assessed closed-loop point-and-click cursor control. The participant performed both an eight-target center-out task and a random target Fitts metric task which was adapted from a human-computer interaction ISO standard used to quantify performance of computer input devices. The neural interface system was further characterized by daily measurement of electrode impedances, unit waveforms and local field potentials. Across the five days, spiking signals were obtained from 41 of 96 electrodes and were successfully decoded to provide neural cursor point-and-click control with a mean task performance of 91.3% ± 0.1% (mean ± s.d.) correct target acquisition. Results across five consecutive days demonstrate that a neural interface system based on an intracortical microelectrode array can provide repeatable, accurate point-and-click control of a computer interface to an individual with tetraplegia 1000 days after implantation of this sensor. PMID:21436513

Ultrasmall implantable composite microelectrodes with bioactive surfaces for chronic neural interfaces

PubMed Central

Kozai, Takashi D. Yoshida; Langhals, Nicholas B.; Patel, Paras R.; Deng, Xiaopei; Zhang, Huanan; Smith, Karen L.; Lahann, Joerg; Kotov, Nicholas A.; Kipke, Daryl R.

2012-01-01

Implantable neural microelectrodes that can record extracellular biopotentials from small, targeted groups of neurons are critical for neuroscience research and emerging clinical applications including brain-controlled prosthetic devices. The crucial material-dependent problem is developing microelectrodes that record neural activity from the same neurons for years with high fidelity and reliability. Here, we report the development of an integrated composite electrode consisting of a carbon-fibre core, a poly(p-xylylene)-based thin-film coating that acts as a dielectric barrier and that is functionalized to control intrinsic biological processes, and a poly(thiophene)-based recording pad. The resulting implants are an order of magnitude smaller than traditional recording electrodes, and more mechanically compliant with brain tissue. They were found to elicit much reduced chronic reactive tissue responses and enabled single-neuron recording in acute and early chronic experiments in rats. This technology, taking advantage of new composites, makes possible highly selective and stealthy neural interface devices towards realizing long-lasting implants. PMID:23142839

Improving Neural Recording Technology at the Nanoscale

NASA Astrophysics Data System (ADS)

Ferguson, John Eric

Neural recording electrodes are widely used to study normal brain function (e.g., learning, memory, and sensation) and abnormal brain function (e.g., epilepsy, addiction, and depression) and to interface with the nervous system for neuroprosthetics. With a deep understanding of the electrode interface at the nanoscale and the use of novel nanofabrication processes, neural recording electrodes can be designed that surpass previous limits and enable new applications. In this thesis, I will discuss three projects. In the first project, we created an ultralow-impedance electrode coating by controlling the nanoscale texture of electrode surfaces. In the second project, we developed a novel nanowire electrode for long-term intracellular recordings. In the third project, we created a means of wirelessly communicating with ultra-miniature, implantable neural recording devices. The techniques developed for these projects offer significant improvements in the quality of neural recordings. They can also open the door to new types of experiments and medical devices, which can lead to a better understanding of the brain and can enable novel and improved tools for clinical applications.

High-Density Stretchable Electrode Grids for Chronic Neural Recording

PubMed Central

Tybrandt, Klas; Khodagholy, Dion; Dielacher, Bernd; Stauffer, Flurin; Renz, Aline F.; Buzsáki, György; Vörös, János

2018-01-01

Electrical interfacing with neural tissue is key to advancing diagnosis and therapies for neurological disorders, as well as providing detailed information about neural signals. A challenge for creating long-term stable interfaces between electronics and neural tissue is the huge mechanical mismatch between the systems. So far, materials and fabrication processes have restricted the development of soft electrode grids able to combine high performance, long-term stability, and high electrode density, aspects all essential for neural interfacing. Here, this challenge is addressed by developing a soft, high-density, stretchable electrode grid based on an inert, high-performance composite material comprising gold-coated titanium dioxide nanowires embedded in a silicone matrix. The developed grid can resolve high spatiotemporal neural signals from the surface of the cortex in freely moving rats with stable neural recording quality and preserved electrode signal coherence during 3 months of implantation. Due to its flexible and stretchable nature, it is possible to minimize the size of the craniotomy required for placement, further reducing the level of invasiveness. The material and device technology presented herein have potential for a wide range of emerging biomedical applications. PMID:29488263

Graphene-Based Interfaces Do Not Alter Target Nerve Cells.

PubMed

Fabbro, Alessandra; Scaini, Denis; León, Verónica; Vázquez, Ester; Cellot, Giada; Privitera, Giulia; Lombardi, Lucia; Torrisi, Felice; Tomarchio, Flavia; Bonaccorso, Francesco; Bosi, Susanna; Ferrari, Andrea C; Ballerini, Laura; Prato, Maurizio

2016-01-26

Neural-interfaces rely on the ability of electrodes to transduce stimuli into electrical patterns delivered to the brain. In addition to sensitivity to the stimuli, stability in the operating conditions and efficient charge transfer to neurons, the electrodes should not alter the physiological properties of the target tissue. Graphene is emerging as a promising material for neuro-interfacing applications, given its outstanding physico-chemical properties. Here, we use graphene-based substrates (GBSs) to interface neuronal growth. We test our GBSs on brain cell cultures by measuring functional and synaptic integrity of the emerging neuronal networks. We show that GBSs are permissive interfaces, even when uncoated by cell adhesion layers, retaining unaltered neuronal signaling properties, thus being suitable for carbon-based neural prosthetic devices.

Active Microelectronic Neurosensor Arrays for Implantable Brain Communication Interfaces

PubMed Central

Song, Y.-K.; Borton, D. A.; Park, S.; Patterson, W. R.; Bull, C. W.; Laiwalla, F.; Mislow, J.; Simeral, J. D.; Donoghue, J. P.; Nurmikko, A. V.

2010-01-01

We have built a wireless implantable microelectronic device for transmitting cortical signals transcutaneously. The device is aimed at interfacing a microelectrode array cortical to an external computer for neural control applications. Our implantable microsystem enables presently 16-channel broadband neural recording in a non-human primate brain by converting these signals to a digital stream of infrared light pulses for transmission through the skin. The implantable unit employs a flexible polymer substrate onto which we have integrated ultra-low power amplification with analog multiplexing, an analog-to-digital converter, a low power digital controller chip, and infrared telemetry. The scalable 16-channel microsystem can employ any of several modalities of power supply, including via radio frequency by induction, or infrared light via a photovoltaic converter. As of today, the implant has been tested as a sub-chronic unit in non-human primates (~ 1 month), yielding robust spike and broadband neural data on all available channels. PMID:19502132

Safe Direct Current Stimulator design for reduced power consumption and increased reliability.

PubMed

Fridman, Gene

2017-07-01

Current state of the art neural prosthetics, such as cochlear implants, spinal cord stimulators, and deep brain stimulators use implantable pulse generators (IPGs) to excite neural activity. Inhibition of neural firing is typically indirect and requires excitation of neurons that then have inhibitory projections downstream. Safe Direct Current Stimulator (SDCS) technology is designed to convert electronic pulses delivered to electrodes embedded within an implantable device to ionic direct current (iDC) at the output of the device. iDC from the device can then control neural extracellular potential with the intent of being able to not only excite, but also inhibit and sensitize neurons, thereby greatly expanding the possible applications of neuromodulation therapies and neural interface mechanisms. While the potential applications and proof of concept of this device have been the focus of previous work, the published descriptions of this technology leave significant room for power and reliability optimization. We describe and model a novel device construction designed to reduce power consumption by a factor of 12 and to improve its reliability by a factor of 8.

Lifetime assessment of atomic-layer-deposited Al2O3-Parylene C bilayer coating for neural interfaces using accelerated age testing and electrochemical characterization.

PubMed

Minnikanti, Saugandhika; Diao, Guoqing; Pancrazio, Joseph J; Xie, Xianzong; Rieth, Loren; Solzbacher, Florian; Peixoto, Nathalia

2014-02-01

The lifetime and stability of insulation are critical features for the reliable operation of an implantable neural interface device. A critical factor for an implanted insulation's performance is its barrier properties that limit access of biological fluids to the underlying device or metal electrode. Parylene C is a material that has been used in FDA-approved implantable devices. Considered a biocompatible polymer with barrier properties, it has been used as a substrate, insulation or an encapsulation for neural implant technology. Recently, it has been suggested that a bilayer coating of Parylene C on top of atomic-layer-deposited Al2O3 would provide enhanced barrier properties. Here we report a comprehensive study to examine the mean time to failure of Parylene C and Al2O3-Parylene C coated devices using accelerated lifetime testing. Samples were tested at 60°C for up to 3 months while performing electrochemical measurements to characterize the integrity of the insulation. The mean time to failure for Al2O3-Parylene C was 4.6 times longer than Parylene C coated samples. In addition, based on modeling of the data using electrical circuit equivalents, we show here that there are two main modes of failure. Our results suggest that failure of the insulating layer is due to pore formation or blistering as well as thinning of the coating over time. The enhanced barrier properties of the bilayer Al2O3-Parylene C over Parylene C makes it a promising candidate as an encapsulating neural interface. Copyright © 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Advances in neuroprosthetic learning and control.

PubMed

Carmena, Jose M

2013-01-01

Significant progress has occurred in the field of brain-machine interfaces (BMI) since the first demonstrations with rodents, monkeys, and humans controlling different prosthetic devices directly with neural activity. This technology holds great potential to aid large numbers of people with neurological disorders. However, despite this initial enthusiasm and the plethora of available robotic technologies, existing neural interfaces cannot as yet master the control of prosthetic, paralyzed, or otherwise disabled limbs. Here I briefly discuss recent advances from our laboratory into the neural basis of BMIs that should lead to better prosthetic control and clinically viable solutions, as well as new insights into the neurobiology of action.

Advances in Neuroprosthetic Learning and Control

PubMed Central

Carmena, Jose M.

2013-01-01

Significant progress has occurred in the field of brain–machine interfaces (BMI) since the first demonstrations with rodents, monkeys, and humans controlling different prosthetic devices directly with neural activity. This technology holds great potential to aid large numbers of people with neurological disorders. However, despite this initial enthusiasm and the plethora of available robotic technologies, existing neural interfaces cannot as yet master the control of prosthetic, paralyzed, or otherwise disabled limbs. Here I briefly discuss recent advances from our laboratory into the neural basis of BMIs that should lead to better prosthetic control and clinically viable solutions, as well as new insights into the neurobiology of action. PMID:23700383

Chronic multisite brain recordings from a totally implantable bidirectional neural interface: experience in 5 patients with Parkinson's disease.

PubMed

Swann, Nicole C; de Hemptinne, Coralie; Miocinovic, Svjetlana; Qasim, Salman; Ostrem, Jill L; Galifianakis, Nicholas B; Luciano, Marta San; Wang, Sarah S; Ziman, Nathan; Taylor, Robin; Starr, Philip A

2018-02-01

OBJECTIVE Dysfunction of distributed neural networks underlies many brain disorders. The development of neuromodulation therapies depends on a better understanding of these networks. Invasive human brain recordings have a favorable temporal and spatial resolution for the analysis of network phenomena but have generally been limited to acute intraoperative recording or short-term recording through temporarily externalized leads. Here, the authors describe their initial experience with an investigational, first-generation, totally implantable, bidirectional neural interface that allows both continuous therapeutic stimulation and recording of field potentials at multiple sites in a neural network. METHODS Under a physician-sponsored US Food and Drug Administration investigational device exemption, 5 patients with Parkinson's disease were implanted with the Activa PC+S system (Medtronic Inc.). The device was attached to a quadripolar lead placed in the subdural space over motor cortex, for electrocorticography potential recordings, and to a quadripolar lead in the subthalamic nucleus (STN), for both therapeutic stimulation and recording of local field potentials. Recordings from the brain of each patient were performed at multiple time points over a 1-year period. RESULTS There were no serious surgical complications or interruptions in deep brain stimulation therapy. Signals in both the cortex and the STN were relatively stable over time, despite a gradual increase in electrode impedance. Canonical movement-related changes in specific frequency bands in the motor cortex were identified in most but not all recordings. CONCLUSIONS The acquisition of chronic multisite field potentials in humans is feasible. The device performance characteristics described here may inform the design of the next generation of totally implantable neural interfaces. This research tool provides a platform for translating discoveries in brain network dynamics to improved neurostimulation paradigms. Clinical trial registration no.: NCT01934296 (clinicaltrials.gov).

Carbon nanotubes in neural interfacing applications

NASA Astrophysics Data System (ADS)

Voge, Christopher M.; Stegemann, Jan P.

2011-02-01

Carbon nanotubes (CNT) are remarkable materials with a simple and inert molecular structure that gives rise to a range of potentially valuable physical and electronic properties, including high aspect ratio, high mechanical strength and excellent electrical conductivity. This review summarizes recent research on the application of CNT-based materials to study and control cells of the nervous system. It includes the use of CNT as cell culture substrates, to create patterned surfaces and to study cell-matrix interactions. It also summarizes recent investigations of CNT toxicity, particularly as related to neural cells. The application of CNT-based materials to directing the differentiation of progenitor and stem cells toward neural lineages is also discussed. The emphasis is on how CNT surface chemistry and nanotopography can be altered, and how such changes can affect neural cell function. This knowledge can be applied to creating improved neural interfaces and devices, as well as providing new approaches to neural tissue engineering and regeneration.

High-Density Stretchable Electrode Grids for Chronic Neural Recording.

PubMed

Tybrandt, Klas; Khodagholy, Dion; Dielacher, Bernd; Stauffer, Flurin; Renz, Aline F; Buzsáki, György; Vörös, János

2018-04-01

Electrical interfacing with neural tissue is key to advancing diagnosis and therapies for neurological disorders, as well as providing detailed information about neural signals. A challenge for creating long-term stable interfaces between electronics and neural tissue is the huge mechanical mismatch between the systems. So far, materials and fabrication processes have restricted the development of soft electrode grids able to combine high performance, long-term stability, and high electrode density, aspects all essential for neural interfacing. Here, this challenge is addressed by developing a soft, high-density, stretchable electrode grid based on an inert, high-performance composite material comprising gold-coated titanium dioxide nanowires embedded in a silicone matrix. The developed grid can resolve high spatiotemporal neural signals from the surface of the cortex in freely moving rats with stable neural recording quality and preserved electrode signal coherence during 3 months of implantation. Due to its flexible and stretchable nature, it is possible to minimize the size of the craniotomy required for placement, further reducing the level of invasiveness. The material and device technology presented herein have potential for a wide range of emerging biomedical applications. © 2018 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An integrated interface for peripheral neural system recording and stimulation: system design, electrical tests and in-vivo results.

PubMed

Carboni, Caterina; Bisoni, Lorenzo; Carta, Nicola; Puddu, Roberto; Raspopovic, Stanisa; Navarro, Xavier; Raffo, Luigi; Barbaro, Massimo

2016-04-01

The prototype of an electronic bi-directional interface between the Peripheral Nervous System (PNS) and a neuro-controlled hand prosthesis is presented. The system is composed of 2 integrated circuits: a standard CMOS device for neural recording and a HVCMOS device for neural stimulation. The integrated circuits have been realized in 2 different 0.35μ m CMOS processes available from ams. The complete system incorporates 8 channels each including the analog front-end, the A/D conversion, based on a sigma delta architecture and a programmable stimulation module implemented as a 5-bit current DAC; two voltage boosters supply the output stimulation stage with a programmable voltage scalable up to 17V. Successful in-vivo experiments with rats having a TIME electrode implanted in the sciatic nerve were carried out, showing the capability of recording neural signals in the tens of microvolts, with a global noise of 7μ V r m s , and to selectively elicit the tibial and plantar muscles using different active sites of the electrode.

A primer on brain-machine interfaces, concepts, and technology: a key element in the future of functional neurorestoration.

PubMed

Lee, Brian; Liu, Charles Y; Apuzzo, Michael L J

2013-01-01

Conventionally, the practice of neurosurgery has been characterized by the removal of pathology, congenital or acquired. The emerging complement to the removal of pathology is surgery for the specific purpose of restoration of function. Advents in neuroscience, technology, and the understanding of neural circuitry are creating opportunities to intervene in disease processes in a reparative manner, thereby advancing toward the long-sought-after concept of neurorestoration. Approaching the issue of neurorestoration from a biomedical engineering perspective is the rapidly growing arena of implantable devices. Implantable devices are becoming more common in medicine and are making significant advancements to improve a patient's functional outcome. Devices such as deep brain stimulators, vagus nerve stimulators, and spinal cord stimulators are now becoming more commonplace in neurosurgery as we utilize our understanding of the nervous system to interpret neural activity and restore function. One of the most exciting prospects in neurosurgery is the technologically driven field of brain-machine interface, also known as brain-computer interface, or neuroprosthetics. The successful development of this technology will have far-reaching implications for patients suffering from a great number of diseases, including but not limited to spinal cord injury, paralysis, stroke, or loss of limb. This article provides an overview of the issues related to neurorestoration using implantable devices with a specific focus on brain-machine interface technology. Copyright © 2013 Elsevier Inc. All rights reserved.

A Brain-Machine-Muscle Interface for Restoring Hindlimb Locomotion after Complete Spinal Transection in Rats

PubMed Central

Alam, Monzurul; Chen, Xi; Zhang, Zicong; Li, Yan; He, Jufang

2014-01-01

A brain-machine interface (BMI) is a neuroprosthetic device that can restore motor function of individuals with paralysis. Although the feasibility of BMI control of upper-limb neuroprostheses has been demonstrated, a BMI for the restoration of lower-limb motor functions has not yet been developed. The objective of this study was to determine if gait-related information can be captured from neural activity recorded from the primary motor cortex of rats, and if this neural information can be used to stimulate paralysed hindlimb muscles after complete spinal cord transection. Neural activity was recorded from the hindlimb area of the primary motor cortex of six female Sprague Dawley rats during treadmill locomotion before and after mid-thoracic transection. Before spinal transection there was a strong association between neural activity and the step cycle. This association decreased after spinal transection. However, the locomotive state (standing vs. walking) could still be successfully decoded from neural recordings made after spinal transection. A novel BMI device was developed that processed this neural information in real-time and used it to control electrical stimulation of paralysed hindlimb muscles. This system was able to elicit hindlimb muscle contractions that mimicked forelimb stepping. We propose this lower-limb BMI as a future neuroprosthesis for human paraplegics. PMID:25084446

A brain-machine-muscle interface for restoring hindlimb locomotion after complete spinal transection in rats.

PubMed

Alam, Monzurul; Chen, Xi; Zhang, Zicong; Li, Yan; He, Jufang

2014-01-01

A brain-machine interface (BMI) is a neuroprosthetic device that can restore motor function of individuals with paralysis. Although the feasibility of BMI control of upper-limb neuroprostheses has been demonstrated, a BMI for the restoration of lower-limb motor functions has not yet been developed. The objective of this study was to determine if gait-related information can be captured from neural activity recorded from the primary motor cortex of rats, and if this neural information can be used to stimulate paralysed hindlimb muscles after complete spinal cord transection. Neural activity was recorded from the hindlimb area of the primary motor cortex of six female Sprague Dawley rats during treadmill locomotion before and after mid-thoracic transection. Before spinal transection there was a strong association between neural activity and the step cycle. This association decreased after spinal transection. However, the locomotive state (standing vs. walking) could still be successfully decoded from neural recordings made after spinal transection. A novel BMI device was developed that processed this neural information in real-time and used it to control electrical stimulation of paralysed hindlimb muscles. This system was able to elicit hindlimb muscle contractions that mimicked forelimb stepping. We propose this lower-limb BMI as a future neuroprosthesis for human paraplegics.

A chronic generalized bi-directional brain-machine interface.

PubMed

Rouse, A G; Stanslaski, S R; Cong, P; Jensen, R M; Afshar, P; Ullestad, D; Gupta, R; Molnar, G F; Moran, D W; Denison, T J

2011-06-01

A bi-directional neural interface (NI) system was designed and prototyped by incorporating a novel neural recording and processing subsystem into a commercial neural stimulator architecture. The NI system prototype leverages the system infrastructure from an existing neurostimulator to ensure reliable operation in a chronic implantation environment. In addition to providing predicate therapy capabilities, the device adds key elements to facilitate chronic research, such as four channels of electrocortigram/local field potential amplification and spectral analysis, a three-axis accelerometer, algorithm processing, event-based data logging, and wireless telemetry for data uploads and algorithm/configuration updates. The custom-integrated micropower sensor and interface circuits facilitate extended operation in a power-limited device. The prototype underwent significant verification testing to ensure reliability, and meets the requirements for a class CF instrument per IEC-60601 protocols. The ability of the device system to process and aid in classifying brain states was preclinically validated using an in vivo non-human primate model for brain control of a computer cursor (i.e. brain-machine interface or BMI). The primate BMI model was chosen for its ability to quantitatively measure signal decoding performance from brain activity that is similar in both amplitude and spectral content to other biomarkers used to detect disease states (e.g. Parkinson's disease). A key goal of this research prototype is to help broaden the clinical scope and acceptance of NI techniques, particularly real-time brain state detection. These techniques have the potential to be generalized beyond motor prosthesis, and are being explored for unmet needs in other neurological conditions such as movement disorders, stroke and epilepsy.

EDITORIAL: Special issue containing contributions from the 39th Neural Interfaces Conference Special issue containing contributions from the 39th Neural Interfaces Conference

NASA Astrophysics Data System (ADS)

Weiland, James D.

2011-07-01

Implantable neural interfaces provide substantial benefits to individuals with neurological disorders. That was the unequivocal message delivered by speaker after speaker from the podium of the 39th Neural Interfaces Conference (NIC2010) held in Long Beach, California, in June 2010. Giving benefit to patients is the most important measure for any biomedical technology, and myriad presentations at NIC2010 made clear that implantable neurostimulation technology has achieved this goal. Cochlear implants allow deaf people to communicate through speech. Deep brain stimulators give back mobility and dexterity necessary for so many daily tasks that are often taken for granted. Chronic pain can be alleviated through spinal cord stimulation. Motor prosthesis systems have been demonstrated in humans, through both reanimation of paralyzed limbs and neural control of robotic arms. Earlier this year, a retinal prosthesis was approved for sale in Europe, providing some hope for the blind. In sum, current clinical implants have been tremendously beneficial for today's patients and experimental systems that will be translated to the clinic promise to expand the number of people helped through bioelectronic therapies. Yet there are significant opportunities for improvement. For sensory prostheses, patients report an artificial sensation, clearly different from the natural sensation they remember. Neuromodulation systems, such as deep brain stimulation and pain stimulators, often have side effects that are tolerated as long as the side effects are less impactful than the disease. The papers published in the special issue from NIC2010 reflect the maturing and expanding field of neural interfaces. Our field has moved past proof-of-principle demonstrations and is now focusing on proving the longevity required for clinical implementation of new devices, extending existing approaches to new diseases and improving current devices for better outcomes. Closed-loop neuromodulation is a strategy that can potentially optimize dosing, reduce side effects and extend implant battery life. The article by Liang et al investigates methods for closed loop control of epilepsy, using neural recording to detect imminent seizures and stimulation to halt the aberrant neural activity leading to seizure. Liu et al report on a model of basal ganglia function that could lead to optimized, closed-loop stimulation to reduce symptoms of Parkinson's disease while avoiding side effects. Our laboratory, as described in Ray et al, is investigating the interface between stimulating microelectrodes and the retina, to inform the design of a high-resolution retinal prosthesis. Three contributions address the issue of long-term stability of cortical recording, which remains a major hurdle to implementation of neural recording systems. The Utah group reports on the in vitro testing of a completely implantable, wireless neural recording system, demonstrating almost one year of reliable performance under simulated implant conditions. Shenoy's laboratory at Stanford demonstrates that useful signals can be recorded from research animals for over 2.5 years. Lempka et al describe a modeling approach to analyzing intracortical microelectrode recordings. These findings represent real and significant progress towards overcoming the final barriers to implementation of a reliable cortical interface. Planning is well underway for the 40th Neural Interfaces Conference, which will be held in Salt Lake City, Utah, in June 2012. The conference promises to continue the NIC tradition of showcasing the latest results from clinical trials of neural interface therapies while providing ample time for dynamic exchange amongst the interdisciplinary audience of engineers, scientists and clinicians.

Virtual reality interface devices in the reorganization of neural networks in the brain of patients with neurological diseases.

PubMed

Gatica-Rojas, Valeska; Méndez-Rebolledo, Guillermo

2014-04-15

Two key characteristics of all virtual reality applications are interaction and immersion. Systemic interaction is achieved through a variety of multisensory channels (hearing, sight, touch, and smell), permitting the user to interact with the virtual world in real time. Immersion is the degree to which a person can feel wrapped in the virtual world through a defined interface. Virtual reality interface devices such as the Nintendo® Wii and its peripheral nunchuks-balance board, head mounted displays and joystick allow interaction and immersion in unreal environments created from computer software. Virtual environments are highly interactive, generating great activation of visual, vestibular and proprioceptive systems during the execution of a video game. In addition, they are entertaining and safe for the user. Recently, incorporating therapeutic purposes in virtual reality interface devices has allowed them to be used for the rehabilitation of neurological patients, e.g., balance training in older adults and dynamic stability in healthy participants. The improvements observed in neurological diseases (chronic stroke and cerebral palsy) have been shown by changes in the reorganization of neural networks in patients' brain, along with better hand function and other skills, contributing to their quality of life. The data generated by such studies could substantially contribute to physical rehabilitation strategies.

Virtual reality interface devices in the reorganization of neural networks in the brain of patients with neurological diseases

PubMed Central

Gatica-Rojas, Valeska; Méndez-Rebolledo, Guillermo

2014-01-01

Two key characteristics of all virtual reality applications are interaction and immersion. Systemic interaction is achieved through a variety of multisensory channels (hearing, sight, touch, and smell), permitting the user to interact with the virtual world in real time. Immersion is the degree to which a person can feel wrapped in the virtual world through a defined interface. Virtual reality interface devices such as the Nintendo® Wii and its peripheral nunchuks-balance board, head mounted displays and joystick allow interaction and immersion in unreal environments created from computer software. Virtual environments are highly interactive, generating great activation of visual, vestibular and proprioceptive systems during the execution of a video game. In addition, they are entertaining and safe for the user. Recently, incorporating therapeutic purposes in virtual reality interface devices has allowed them to be used for the rehabilitation of neurological patients, e.g., balance training in older adults and dynamic stability in healthy participants. The improvements observed in neurological diseases (chronic stroke and cerebral palsy) have been shown by changes in the reorganization of neural networks in patients’ brain, along with better hand function and other skills, contributing to their quality of life. The data generated by such studies could substantially contribute to physical rehabilitation strategies. PMID:25206907

A Bidirectional Brain-Machine Interface Algorithm That Approximates Arbitrary Force-Fields

PubMed Central

Semprini, Marianna; Mussa-Ivaldi, Ferdinando A.; Panzeri, Stefano

2014-01-01

We examine bidirectional brain-machine interfaces that control external devices in a closed loop by decoding motor cortical activity to command the device and by encoding the state of the device by delivering electrical stimuli to sensory areas. Although it is possible to design this artificial sensory-motor interaction while maintaining two independent channels of communication, here we propose a rule that closes the loop between flows of sensory and motor information in a way that approximates a desired dynamical policy expressed as a field of forces acting upon the controlled external device. We previously developed a first implementation of this approach based on linear decoding of neural activity recorded from the motor cortex into a set of forces (a force field) applied to a point mass, and on encoding of position of the point mass into patterns of electrical stimuli delivered to somatosensory areas. However, this previous algorithm had the limitation that it only worked in situations when the position-to-force map to be implemented is invertible. Here we overcome this limitation by developing a new non-linear form of the bidirectional interface that can approximate a virtually unlimited family of continuous fields. The new algorithm bases both the encoding of position information and the decoding of motor cortical activity on an explicit map between spike trains and the state space of the device computed with Multi-Dimensional-Scaling. We present a detailed computational analysis of the performance of the interface and a validation of its robustness by using synthetic neural responses in a simulated sensory-motor loop. PMID:24626393

Ultrasoft microwire neural electrodes improve chronic tissue integration.

PubMed

Du, Zhanhong Jeff; Kolarcik, Christi L; Kozai, Takashi D Y; Luebben, Silvia D; Sapp, Shawn A; Zheng, Xin Sally; Nabity, James A; Cui, X Tracy

2017-04-15

Chronically implanted neural multi-electrode arrays (MEA) are an essential technology for recording electrical signals from neurons and/or modulating neural activity through stimulation. However, current MEAs, regardless of the type, elicit an inflammatory response that ultimately leads to device failure. Traditionally, rigid materials like tungsten and silicon have been employed to interface with the relatively soft neural tissue. The large stiffness mismatch is thought to exacerbate the inflammatory response. In order to minimize the disparity between the device and the brain, we fabricated novel ultrasoft electrodes consisting of elastomers and conducting polymers with mechanical properties much more similar to those of brain tissue than previous neural implants. In this study, these ultrasoft microelectrodes were inserted and released using a stainless steel shuttle with polyethyleneglycol (PEG) glue. The implanted microwires showed functionality in acute neural stimulation. When implanted for 1 or 8weeks, the novel soft implants demonstrated significantly reduced inflammatory tissue response at week 8 compared to tungsten wires of similar dimension and surface chemistry. Furthermore, a higher degree of cell body distortion was found next to the tungsten implants compared to the polymer implants. Our results support the use of these novel ultrasoft electrodes for long term neural implants. One critical challenge to the translation of neural recording/stimulation electrode technology to clinically viable devices for brain computer interface (BCI) or deep brain stimulation (DBS) applications is the chronic degradation of device performance due to the inflammatory tissue reaction. While many hypothesize that soft and flexible devices elicit reduced inflammatory tissue responses, there has yet to be a rigorous comparison between soft and stiff implants. We have developed an ultra-soft microelectrode with Young's modulus lower than 1MPa, closely mimicking the brain tissue modulus. Here, we present a rigorous histological comparison of this novel ultrasoft electrode and conventional stiff electrode with the same size, shape and surface chemistry, implanted in rat brains for 1-week and 8-weeks. Significant improvement was observed for ultrasoft electrodes, including inflammatory tissue reaction, electrode-tissue integration as well as mechanical disturbance to nearby neurons. A full spectrum of new techniques were developed in this study, from insertion shuttle to in situ sectioning of the microelectrode to automated cell shape analysis, all of which should contribute new methods to the field. Finally, we showed the electrical functionality of the ultrasoft electrode, demonstrating the potential of flexible neural implant devices for future research and clinical use. Copyright © 2017. Published by Elsevier Ltd.

pHEMA Encapsulated PEDOT-PSS-CNT Microsphere Microelectrodes for Recording Single Unit Activity in the Brain

PubMed Central

Castagnola, Elisa; Maggiolini, Emma; Ceseracciu, Luca; Ciarpella, Francesca; Zucchini, Elena; De Faveri, Sara; Fadiga, Luciano; Ricci, Davide

2016-01-01

The long-term reliability of neural interfaces and stability of high-quality recordings are still unsolved issues in neuroscience research. High surface area PEDOT-PSS-CNT composites are able to greatly improve the performance of recording and stimulation for traditional intracortical metal microelectrodes by decreasing their impedance and increasing their charge transfer capability. This enhancement significantly reduces the size of the implantable device though preserving excellent electrical performances. On the other hand, the presence of nanomaterials often rises concerns regarding possible health hazards, especially when considering a clinical application of the devices. For this reason, we decided to explore the problem from a new perspective by designing and testing an innovative device based on nanostructured microspheres grown on a thin tether, integrating PEDOT-PSS-CNT nanocomposites with a soft synthetic permanent biocompatible hydrogel. The pHEMA hydrogel preserves the electrochemical performance and high quality recording ability of PEDOT-PSS-CNT coated devices, reduces the mechanical mismatch between soft brain tissue and stiff devices and also avoids direct contact between the neural tissue and the nanocomposite, by acting as a biocompatible protective barrier against potential nanomaterial detachment. Moreover, the spherical shape of the electrode together with the surface area increase provided by the nanocomposite deposited on it, maximize the electrical contact and may improve recording stability over time. These results have a good potential to contribute to fulfill the grand challenge of obtaining stable neural interfaces for long-term applications. PMID:27147944

Neurofeedback Training for BCI Control

NASA Astrophysics Data System (ADS)

Neuper, Christa; Pfurtscheller, Gert

Brain-computer interface (BCI) systems detect changes in brain signals that reflect human intention, then translate these signals to control monitors or external devices (for a comprehensive review, see [1]). BCIs typically measure electrical signals resulting from neural firing (i.e. neuronal action potentials, Electroencephalogram (ECoG), or Electroencephalogram (EEG)). Sophisticated pattern recognition and classification algorithms convert neural activity into the required control signals. BCI research has focused heavily on developing powerful signal processing and machine learning techniques to accurately classify neural activity [2-4].

Listening to Brain Microcircuits for Interfacing With External World-Progress in Wireless Implantable Microelectronic Neuroengineering Devices: Experimental systems are described for electrical recording in the brain using multiple microelectrodes and short range implantable or wearable broadcasting units.

PubMed

Nurmikko, Arto V; Donoghue, John P; Hochberg, Leigh R; Patterson, William R; Song, Yoon-Kyu; Bull, Christopher W; Borton, David A; Laiwalla, Farah; Park, Sunmee; Ming, Yin; Aceros, Juan

2010-01-01

Acquiring neural signals at high spatial and temporal resolution directly from brain microcircuits and decoding their activity to interpret commands and/or prior planning activity, such as motion of an arm or a leg, is a prime goal of modern neurotechnology. Its practical aims include assistive devices for subjects whose normal neural information pathways are not functioning due to physical damage or disease. On the fundamental side, researchers are striving to decipher the code of multiple neural microcircuits which collectively make up nature's amazing computing machine, the brain. By implanting biocompatible neural sensor probes directly into the brain, in the form of microelectrode arrays, it is now possible to extract information from interacting populations of neural cells with spatial and temporal resolution at the single cell level. With parallel advances in application of statistical and mathematical techniques tools for deciphering the neural code, extracted populations or correlated neurons, significant understanding has been achieved of those brain commands that control, e.g., the motion of an arm in a primate (monkey or a human subject). These developments are accelerating the work on neural prosthetics where brain derived signals may be employed to bypass, e.g., an injured spinal cord. One key element in achieving the goals for practical and versatile neural prostheses is the development of fully implantable wireless microelectronic "brain-interfaces" within the body, a point of special emphasis of this paper.

Parietal neural prosthetic control of a computer cursor in a graphical-user-interface task

NASA Astrophysics Data System (ADS)

Revechkis, Boris; Aflalo, Tyson NS; Kellis, Spencer; Pouratian, Nader; Andersen, Richard A.

2014-12-01

Objective. To date, the majority of Brain-Machine Interfaces have been used to perform simple tasks with sequences of individual targets in otherwise blank environments. In this study we developed a more practical and clinically relevant task that approximated modern computers and graphical user interfaces (GUIs). This task could be problematic given the known sensitivity of areas typically used for BMIs to visual stimuli, eye movements, decision-making, and attentional control. Consequently, we sought to assess the effect of a complex, GUI-like task on the quality of neural decoding. Approach. A male rhesus macaque monkey was implanted with two 96-channel electrode arrays in area 5d of the superior parietal lobule. The animal was trained to perform a GUI-like ‘Face in a Crowd’ task on a computer screen that required selecting one cued, icon-like, face image from a group of alternatives (the ‘Crowd’) using a neurally controlled cursor. We assessed whether the crowd affected decodes of intended cursor movements by comparing it to a ‘Crowd Off’ condition in which only the matching target appeared without alternatives. We also examined if training a neural decoder with the Crowd On rather than Off had any effect on subsequent decode quality. Main results. Despite the additional demands of working with the Crowd On, the animal was able to robustly perform the task under Brain Control. The presence of the crowd did not itself affect decode quality. Training the decoder with the Crowd On relative to Off had no negative influence on subsequent decoding performance. Additionally, the subject was able to gaze around freely without influencing cursor position. Significance. Our results demonstrate that area 5d recordings can be used for decoding in a complex, GUI-like task with free gaze. Thus, this area is a promising source of signals for neural prosthetics that utilize computing devices with GUI interfaces, e.g. personal computers, mobile devices, and tablet computers.

Parietal neural prosthetic control of a computer cursor in a graphical-user-interface task.

PubMed

Revechkis, Boris; Aflalo, Tyson N S; Kellis, Spencer; Pouratian, Nader; Andersen, Richard A

2014-12-01

To date, the majority of Brain-Machine Interfaces have been used to perform simple tasks with sequences of individual targets in otherwise blank environments. In this study we developed a more practical and clinically relevant task that approximated modern computers and graphical user interfaces (GUIs). This task could be problematic given the known sensitivity of areas typically used for BMIs to visual stimuli, eye movements, decision-making, and attentional control. Consequently, we sought to assess the effect of a complex, GUI-like task on the quality of neural decoding. A male rhesus macaque monkey was implanted with two 96-channel electrode arrays in area 5d of the superior parietal lobule. The animal was trained to perform a GUI-like 'Face in a Crowd' task on a computer screen that required selecting one cued, icon-like, face image from a group of alternatives (the 'Crowd') using a neurally controlled cursor. We assessed whether the crowd affected decodes of intended cursor movements by comparing it to a 'Crowd Off' condition in which only the matching target appeared without alternatives. We also examined if training a neural decoder with the Crowd On rather than Off had any effect on subsequent decode quality. Despite the additional demands of working with the Crowd On, the animal was able to robustly perform the task under Brain Control. The presence of the crowd did not itself affect decode quality. Training the decoder with the Crowd On relative to Off had no negative influence on subsequent decoding performance. Additionally, the subject was able to gaze around freely without influencing cursor position. Our results demonstrate that area 5d recordings can be used for decoding in a complex, GUI-like task with free gaze. Thus, this area is a promising source of signals for neural prosthetics that utilize computing devices with GUI interfaces, e.g. personal computers, mobile devices, and tablet computers.

Implantable neurotechnologies: a review of integrated circuit neural amplifiers.

PubMed

Ng, Kian Ann; Greenwald, Elliot; Xu, Yong Ping; Thakor, Nitish V

2016-01-01

Neural signal recording is critical in modern day neuroscience research and emerging neural prosthesis programs. Neural recording requires the use of precise, low-noise amplifier systems to acquire and condition the weak neural signals that are transduced through electrode interfaces. Neural amplifiers and amplifier-based systems are available commercially or can be designed in-house and fabricated using integrated circuit (IC) technologies, resulting in very large-scale integration or application-specific integrated circuit solutions. IC-based neural amplifiers are now used to acquire untethered/portable neural recordings, as they meet the requirements of a miniaturized form factor, light weight and low power consumption. Furthermore, such miniaturized and low-power IC neural amplifiers are now being used in emerging implantable neural prosthesis technologies. This review focuses on neural amplifier-based devices and is presented in two interrelated parts. First, neural signal recording is reviewed, and practical challenges are highlighted. Current amplifier designs with increased functionality and performance and without penalties in chip size and power are featured. Second, applications of IC-based neural amplifiers in basic science experiments (e.g., cortical studies using animal models), neural prostheses (e.g., brain/nerve machine interfaces) and treatment of neuronal diseases (e.g., DBS for treatment of epilepsy) are highlighted. The review concludes with future outlooks of this technology and important challenges with regard to neural signal amplification.

Implantable neurotechnologies: a review of integrated circuit neural amplifiers

PubMed Central

Greenwald, Elliot; Xu, Yong Ping; Thakor, Nitish V.

2016-01-01

Neural signal recording is critical in modern day neuroscience research and emerging neural prosthesis programs. Neural recording requires the use of precise, low-noise amplifier systems to acquire and condition the weak neural signals that are transduced through electrode interfaces. Neural amplifiers and amplifier-based systems are available commercially or can be designed in-house and fabricated using integrated circuit (IC) technologies, resulting in very large-scale integration or application-specific integrated circuit solutions. IC-based neural amplifiers are now used to acquire untethered/portable neural recordings, as they meet the requirements of a miniaturized form factor, light weight and low power consumption. Furthermore, such miniaturized and low-power IC neural amplifiers are now being used in emerging implantable neural prosthesis technologies. This review focuses on neural amplifier-based devices and is presented in two interrelated parts. First, neural signal recording is reviewed, and practical challenges are highlighted. Current amplifier designs with increased functionality and performance and without penalties in chip size and power are featured. Second, applications of IC-based neural amplifiers in basic science experiments (e.g., cortical studies using animal models), neural prostheses (e.g., brain/nerve machine interfaces) and treatment of neuronal diseases (e.g., DBS for treatment of epilepsy) are highlighted. The review concludes with future outlooks of this technology and important challenges with regard to neural signal amplification. PMID:26798055

Time to address the problems at the neural interface

NASA Astrophysics Data System (ADS)

Durand, Dominique M.; Ghovanloo, Maysam; Krames, Elliot

2014-04-01

Neural engineers have made significant, if not remarkable, progress in interfacing with the nervous system in the last ten years. In particular, neuromodulation of the brain has generated significant therapeutic benefits [1-5]. EEG electrodes can be used to communicate with patients with locked-in syndrome [6]. In the central nervous system (CNS), electrode arrays placed directly over or within the cortex can record neural signals related to the intent of the subject or patient [7, 8]. A similar technology has allowed paralyzed patients to control an otherwise normal skeletal system with brain signals [9, 10]. This technology has significant potential to restore function in these and other patients with neural disorders such as stroke [11]. Although there are several multichannel arrays described in the literature, the workhorse for these cortical interfaces has been the Utah array [12]. This 100-channel electrode array has been used in most studies on animals and humans since the 1990s and is commercially available. This array and other similar microelectrode arrays can record neural signals with high quality (high signal-to-noise ratio), but these signals fade and disappear after a few months and therefore the current technology is not reliable for extended periods of time. Therefore, despite these major advances in communicating with the brain, clinical translation cannot be implemented. The reasons for this failure are not known but clearly involve the interface between the electrode and the neural tissue. The Defense Advanced Research Project Agency (DARPA) as well as other federal funding agencies such as the National Science Foundation (NSF) and the National Institutes of Health have provided significant financial support to investigate this problem without much success. A recent funding program from DARPA was designed to establish the failure modes in order to generate a reliable neural interface technology and again was unsuccessful at producing a robust interface with the CNS. In 2013, two symposia were held independently to discuss this problem: one was held at the International Neuromodulation Society's 11th World Congress in Berlin and supported by the International Neuromodulation Society1 and the other at the 6th International Neural Engineering conference in San Diego2 and was supported by the NSF. Clearly, the neuromodulation and the neural engineering communities are keen to solve this problem. Experts from the field were assembled to discuss the problems and potential solutions. Although many important points were raised, few emerged as key issues. (1) The ability to access remotely and reliably internal neural signals . Although some of the technological problems have already been solved, this ability to access neural signals is still a significant problem since reliable and robust transcutaneous telemetry systems with large numbers of signals, each with wide bandwidth, are not readily available to researchers. (2) A translation strategy taking basic research to the clinic . The lack of understanding of the biological response to implanted constructs and the inability to monitor the sites and match the mechanical properties of the probe to the neural tissue properties continue to be an unsolved problem. In addition, the low levels of collaboration among neuroscientists, clinicians, patients and other stakeholders throughout different phases of research and development were considered to be significant impediments to progress. (3) Fundamental tools development procedures for neural interfacing . There are many laboratories testing various devices with different sets of criteria, but there is no consensus on the failure modes. The reliability, robustness of metrics and testing standards for such devices have not been established, either in academia or in industry. To start addressing this problem, the FDA has established a laboratory to test the reliability of some neural devices. Although the discussion was mostly centered on interfacing with the CNS, it has recently become clear that the peripheral nervous system (PNS) could be an important target for interfacing, perhaps even more accessible for interfacing than the CNS. A recent initiative called Bioelectronic Medicines3 is a step in that direction. A recent summit held in New York was organized to investigate novel and disruptive neural technologies to interface specifically with the PNS in order to restore health and biological function to organs. With significant interest in neurotechnology for neural interfacing (see footnotes 1, 2 and 3) and uncovering new ways to treat, prevent and cure brain disorders (President Obama's brain initiative4), it seems clear that the problems at the interface will not remain unsolved for long. Finding solutions to the problem at the neural interface for interacting with the nervous system (PNS and CNS) is crucial for understanding and restoring brain function. This would in turn have a significant impact on health care and quality of life for patients with neural disorders. References [1] Follett K A et al 2010 Pallidal versus subthalamic deep-brain stimulation for Parkinson's disease New Engl. J. Med. 362 2077-91 [2] Holtzheimer P E et al 2012 Subcallosal cingulate deep brain stimulation for treatment-resistant unipolar and bipolar depression Arch. Gen. Psychiatry 69 150 [3] Carron R, Chabardes S and Hammond C 2012 Mechanisms of action of high-frequency deep brain stimulation. A review of the literature and current concepts NeuroChirurgie 58 209-17 [4] Vidailhet M et al 2005 Bilateral deep-brain stimulation of the globus pallidus in primary generalized dystonia New Engl. J. Med. 352 459-67 [5] Theodore W H and Fisher R S 2004 Brain stimulation for epilepsy Lancet Neurol. 3 111-8 [6] Kübler A, Kotchoubey B, Kaiser J, Wolpaw J R and Birbaumer N 2001 Brain-computer communication: unlocking the locked Psychol. Bull. 127 358-75 [7] Schalk G, Miller K J, Anderson N R, Wilson J A, Smyth M D, Ojemann J G, Moran D W, Wolpaw J R and Leuthardt E C 2008 Two-dimensional movement control using electrocorticographic signals in humans J. Neural Eng. 5 75 [8] Serruya M D, Hatsopoulos N G, Paninski L, Fellows M R and Donoghue J P 2002 Brain-machine interface: instant neural control of a movement signal Nature 416 141-2 [9] Hochberg L R, Serruya M D, Friehs G M, Mukand J A, Saleh M, Caplan A H, Branner A, Chen D, Penn R D and Donoghue J P 2006 Neuronal ensemble control of prosthetic devices by a human with tetraplegia Nature 442 164-71 [10] Collinger J L et al 2013 High-performance neuroprosthetic control by an individual with tetraplegia Lancet 381 557-64 [11] Leuthardt E C, Schalk G, Wolpaw J R, Ojemann J G and Moran D W 2004 A brain-computer interface using electrocorticographic signals in humans J. Neural Eng. 1 63 [12] Maynard E M, Nordhausen C T and Normann R A 1997 The Utah intracortical electrode array: a recording structure for potential brain-computer interfaces Electroencephalogr. Clin. Neurophysiol. 102 228-39 1 www.neuromodulation.com/8-june-2013 2 http://neuro.embs.org/wp-content/uploads/sites/2/2013/05/SymposiumAdvert1.pdf 3 www.gsk.com/explore-gsk/how-we-do-r-and-d/bioelectronics.html 4 www.whitehouse.gov/share/brain-initiative

Implantable brain computer interface: challenges to neurotechnology translation.

PubMed

Konrad, Peter; Shanks, Todd

2010-06-01

This article reviews three concepts related to implantable brain computer interface (BCI) devices being designed for human use: neural signal extraction primarily for motor commands, signal insertion to restore sensation, and technological challenges that remain. A significant body of literature has occurred over the past four decades regarding motor cortex signal extraction for upper extremity movement or computer interface. However, little is discussed regarding postural or ambulation command signaling. Auditory prosthesis research continues to represent the majority of literature on BCI signal insertion. Significant hurdles continue in the technological translation of BCI implants. These include developing a stable neural interface, significantly increasing signal processing capabilities, and methods of data transfer throughout the human body. The past few years, however, have provided extraordinary human examples of BCI implant potential. Despite technological hurdles, proof-of-concept animal and human studies provide significant encouragement that BCI implants may well find their way into mainstream medical practice in the foreseeable future.

Neural networks for simultaneous classification and parameter estimation in musical instrument control

NASA Astrophysics Data System (ADS)

Lee, Michael; Freed, Adrian; Wessel, David

1992-08-01

In this report we present our tools for prototyping adaptive user interfaces in the context of real-time musical instrument control. Characteristic of most human communication is the simultaneous use of classified events and estimated parameters. We have integrated a neural network object into the MAX language to explore adaptive user interfaces that considers these facets of human communication. By placing the neural processing in the context of a flexible real-time musical programming environment, we can rapidly prototype experiments on applications of adaptive interfaces and learning systems to musical problems. We have trained networks to recognize gestures from a Mathews radio baton, Nintendo Power GloveTM, and MIDI keyboard gestural input devices. In one experiment, a network successfully extracted classification and attribute data from gestural contours transduced by a continuous space controller, suggesting their application in the interpretation of conducting gestures and musical instrument control. We discuss network architectures, low-level features extracted for the networks to operate on, training methods, and musical applications of adaptive techniques.

Micromachined devices for interfacing neurons

NASA Astrophysics Data System (ADS)

Stieglitz, Thomas; Beutel, Hansjoerg; Blau, Cornelia; Meyer, Joerg-Uwe

1998-07-01

Micromachining technologies were established to fabricate microelectrode arrays and devices for interfacing parts of the central or peripheral nervous system. The devices were part of a neural prosthesis that allows simultaneous multichannel recording and multisite stimulation of neurons. Overcoming the brittle mechanics of silicon devices and challenging housing demands close to the nerve we established a process technology to fabricate light-weighted and highly flexible polyimide based devices. Platinum and iridium thin-film electrodes were embedded in the polyimide. With reactive ion etching we got the possibility to simply integrate interconnections and to form nearly arbitrary outer shapes of the devices. We designed multichannel devices with up to 24 electrodes in the shape of plates, hooks and cuffs for different applications. In vitro tests exhibited stable electrode properties and no cytotoxicity of the materials and the devices. Sieve electrodes were chronically implanted in rats to interface the regenerating sciatic nerve. After six months, recordings and stimulation of the nerve via electrodes on the micro-device proved functional reinnervation of the limb. Concentric circular structures were designed for a retina implant for the blind. In preliminary studies in rabbits, evoked potentials in the visual cortex corresponded to stimulation sites of the implant.

Keeping Disability in Mind: A Case Study in Implantable Brain-Computer Interface Research.

PubMed

Sullivan, Laura Specker; Klein, Eran; Brown, Tim; Sample, Matthew; Pham, Michelle; Tubig, Paul; Folland, Raney; Truitt, Anjali; Goering, Sara

2018-04-01

Brain-Computer Interface (BCI) research is an interdisciplinary area of study within Neural Engineering. Recent interest in end-user perspectives has led to an intersection with user-centered design (UCD). The goal of user-centered design is to reduce the translational gap between researchers and potential end users. However, while qualitative studies have been conducted with end users of BCI technology, little is known about individual BCI researchers' experience with and attitudes towards UCD. Given the scientific, financial, and ethical imperatives of UCD, we sought to gain a better understanding of practical and principled considerations for researchers who engage with end users. We conducted a qualitative interview case study with neural engineering researchers at a center dedicated to the creation of BCIs. Our analysis generated five themes common across interviews. The thematic analysis shows that participants identify multiple beneficiaries of their work, including other researchers, clinicians working with devices, device end users, and families and caregivers of device users. Participants value experience with device end users, and personal experience is the most meaningful type of interaction. They welcome (or even encourage) end-user input, but are skeptical of limited focus groups and case studies. They also recognize a tension between creating sophisticated devices and developing technology that will meet user needs. Finally, interviewees espouse functional, assistive goals for their technology, but describe uncertainty in what degree of function is "good enough" for individual end users. Based on these results, we offer preliminary recommendations for conducting future UCD studies in BCI and neural engineering.

Integration of active devices on smart polymers for neural interfaces

NASA Astrophysics Data System (ADS)

Avendano-Bolivar, Adrian Emmanuel

The increasing ability to ever more precisely identify and measure neural interactions and other phenomena in the central and peripheral nervous systems is revolutionizing our understanding of the human body and brain. To facilitate further understanding, more sophisticated neural devices, perhaps using microelectronics processing, must be fabricated. Materials often used in these neural interfaces, while compatible with these fabrication processes, are not optimized for long-term use in the body and are often orders of magnitude stiffer than the tissue with which they interact. Using the smart polymer substrates described in this work, suitability for processing as well as chronic implantation is demonstrated. We explore how to integrate reliable circuitry onto these flexible, biocompatible substrates that can withstand the aggressive environment of the body. To increase the capabilities of these devices beyond individual channel sensing and stimulation, active electronics must also be included onto our systems. In order to add this functionality to these substrates and explore the limits of these devices, we developed a process to fabricate single organic thin film transistors with mobilities up to 0.4 cm2/Vs and threshold voltages close to 0V. A process for fabricating organic light emitting diodes on flexible substrates is also addressed. We have set a foundation and demonstrated initial feasibility for integrating multiple transistors onto thin-film flexible devices to create new applications, such as matrix addressable functionalized electrodes and organic light emitting diodes. A brief description on how to integrate waveguides for their use in optogenetics is addressed. We have built understanding about device constraints on mechanical, electrical and in vivo reliability and how various conditions affect the electronics' lifetime. We use a bi-layer gate dielectric using an inorganic material such as HfO 2 combined with organic Parylene-c. A study of reliability of widely used Parylene-c encapsulation for in vivo conditions for thin film transistors is presented. These various inquiries, taken in their entirety, facilitate understanding of fundamental problems for biocompatible, chronic electronic device implants in the body, leading to a new set of tools and devices that will help understand complex problems in neuroscience and materials research.

Brain-machine interfaces: electrophysiological challenges and limitations.

PubMed

Lega, Bradley C; Serruya, Mijail D; Zaghloul, Kareem A

2011-01-01

Brain-machine interfaces (BMI) seek to directly communicate with the human nervous system in order to diagnose and treat intrinsic neurological disorders. While the first generation of these devices has realized significant clinical successes, they often rely on gross electrical stimulation using empirically derived parameters through open-loop mechanisms of action that are not yet fully understood. Their limitations reflect the inherent challenge in developing the next generation of these devices. This review identifies lessons learned from the first generation of BMI devices (chiefly deep brain stimulation), identifying key problems for which the solutions will aid the development of the next generation of technologies. Our analysis examines four hypotheses for the mechanism by which brain stimulation alters surrounding neurophysiologic activity. We then focus on motor prosthetics, describing various approaches to overcoming the problems of decoding neural signals. We next turn to visual prosthetics, an area for which the challenges of signal coding to match neural architecture has been partially overcome. Finally, we close with a review of cortical stimulation, examining basic principles that will be incorporated into the design of future devices. Throughout the review, we relate the issues of each specific topic to the common thread of BMI research: translating new knowledge of network neuroscience into improved devices for neuromodulation.

Microfabrication, characterization and in vivo MRI compatibility of diamond microelectrodes array for neural interfacing.

PubMed

Hébert, Clément; Warnking, Jan; Depaulis, Antoine; Garçon, Laurie Amandine; Mermoux, Michel; Eon, David; Mailley, Pascal; Omnès, Franck

2015-01-01

Neural interfacing still requires highly stable and biocompatible materials, in particular for in vivo applications. Indeed, most of the currently used materials are degraded and/or encapsulated by the proximal tissue leading to a loss of efficiency. Here, we considered boron doped diamond microelectrodes to address this issue and we evaluated the performances of a diamond microelectrode array. We described the microfabrication process of the device and discuss its functionalities. We characterized its electrochemical performances by cyclic voltammetry and impedance spectroscopy in saline buffer and observed the typical diamond electrode electrochemical properties, wide potential window and low background current, allowing efficient electrochemical detection. The charge storage capacitance and the modulus of the electrochemical impedance were found to remain in the same range as platinum electrodes used for standard commercial devices. Finally we observed a reduced Magnetic Resonance Imaging artifact when the device was implanted on a rat cortex, suggesting that boron doped-diamond is a very promising electrode material allowing functional imaging. Copyright © 2014 Elsevier B.V. All rights reserved.

In vivo performance of a microelectrode neural probe with integrated drug delivery

PubMed Central

Rohatgi, Pratik; Langhals, Nicholas B.; Kipke, Daryl R.; Patil, Parag G.

2014-01-01

Object The availability of sophisticated neural probes is a key prerequisite in the development of future brain machine interfaces (BMI). In this study, we developed and validated a neural probe design capable of simultaneous drug delivery and electrophysiology recordings in vivo. Focal drug delivery has promise to dramatically extend the recording lives of neural probes, a limiting factor to clinical adoption of BMI technology. Methods To form the multifunctional neural probe, we affixed a 16-channel microfabricated silicon electrode array to a fused silica catheter. Three experiments were conducted to characterize the performance of the device. Experiment 1 examines cellular damage from probe insertion and the drug distribution in tissue. Experiment 2 measures the effects of saline infusions delivered through the probe on concurrent electrophysiology. Experiment 3 demonstrates that a physiologically relevant amount of drug can be delivered in a controlled fashion. For these experiments, Hoechst and propidium iodide were used to assess insertion trauma and the tissue distribution of the infusate. Artificial cerebral spinal fluid and tetrodotoxin were injected to determine the efficacy of drug delivery. Results The newly developed multifunctional neural probes were successfully inserted into rat cortex and were able to deliver fluids and drugs that resulted in the expected electrophysiological and histological responses. The damage from insertion of the device into brain tissue was substantially less than the volume of drug dispersion in tissue. Electrophysiological activity, including both individual spikes as well as local field potentials, was successfully recorded with this device during real-time drug delivery. No significant changes were seen in response to delivery of artificial cerebral spinal fluid as a control experiment, whereas delivery of tetrodotoxin produced the expected result of suppressing all spiking activity in the vicinity of the catheter outlet. Conclusions Multifunctional neural probes such as the ones developed and validated within this study have great potential to help further understand the design space and criteria for the next generation of neural probe technology. By incorporating integrated drug delivery functionality into the probes, new treatment options for neurological disorders and regenerative neural interfaces utilizing localized and feedback controlled delivery of drugs can be realized in the near future. PMID:19569896

Using synthetic biology to interface with physical micro and nano-sized sensors (Conference Presentation)

NASA Astrophysics Data System (ADS)

Hanson, Russell; Fuller, Jason; Cheng, Andrew

2017-05-01

This talk will discuss the current goals and efforts of point of care and personal health monitoring systems: what they can do now and what is in the works. These interfaces can be used in a precision medicine context—making diagnoses and getting the right drugs to the right patients at the right time. Many of the same sensors and engineering are being prototyped now for neural interfaces and recording devices with applications in visual, auditory, and motor cortex, allowing basic research along with preliminary applications in actuation and sensing. While miniaturization and electronics development using established manufacturing protocols can provide the current engineering foundations, novel biochemical ligands and molecular detectors can provide the needed flexibility for next-generation devices.

Comparison of Mono-, Bi-, and Tripolar Configurations for Stimulation and Recording With an Interfascicular Interface.

PubMed

Nielsen, Thomas N; Sevcencu, Cristian; Struijk, Johannes J

2014-01-01

Previous studies have indicated that electrodes placed between fascicles can provide nerve recruitment with high topological selectivity if the areas of interest in the nerve are separated with passive elements. In this study, we investigated if this separation of fascicles also can provide topologically selective nerve recordings and compared the performance of mono-, bi-, and tripolar configurations for stimulation and recording with an intra-neural interface. The interface was implanted in the sciatic nerve of 10 rabbits and achieved a median selectivity of Ŝ=0.98-0.99 for all stimulation configurations, while recording selectivity configurations was in the range of Ŝ=0.70-0.80 with the monopolar configuration providing the lowest and the average reference configuration the highest recording selectivity. Interfascicular electrodes could provide an interesting addition to the bulk of peripheral nerve interfaces available for neural prosthetic devices. The separation of the nerve into chambers by the passive elements of the electrode could ensure a higher selectivity than comparable cuff electrodes and the intra-neural location could provide an option of targeting mainly central fascicles. Further studies are, however, still required to develop biocompatible electrodes and test their stability and safety in chronic experiments.

Glove-talk II - a neural-network interface which maps gestures to parallel formant speech synthesizer controls.

PubMed

Fels, S S; Hinton, G E

1997-01-01

Glove-Talk II is a system which translates hand gestures to speech through an adaptive interface. Hand gestures are mapped continuously to ten control parameters of a parallel formant speech synthesizer. The mapping allows the hand to act as an artificial vocal tract that produces speech in real time. This gives an unlimited vocabulary in addition to direct control of fundamental frequency and volume. Currently, the best version of Glove-Talk II uses several input devices, a parallel formant speech synthesizer, and three neural networks. The gesture-to-speech task is divided into vowel and consonant production by using a gating network to weight the outputs of a vowel and a consonant neural network. The gating network and the consonant network are trained with examples from the user. The vowel network implements a fixed user-defined relationship between hand position and vowel sound and does not require any training examples from the user. Volume, fundamental frequency, and stop consonants are produced with a fixed mapping from the input devices. With Glove-Talk II, the subject can speak slowly but with far more natural sounding pitch variations than a text-to-speech synthesizer.

Development of closed-loop neural interface technology in a rat model: combining motor cortex operant conditioning with visual cortex microstimulation.

PubMed

Marzullo, Timothy Charles; Lehmkuhle, Mark J; Gage, Gregory J; Kipke, Daryl R

2010-04-01

Closed-loop neural interface technology that combines neural ensemble decoding with simultaneous electrical microstimulation feedback is hypothesized to improve deep brain stimulation techniques, neuromotor prosthetic applications, and epilepsy treatment. Here we describe our iterative results in a rat model of a sensory and motor neurophysiological feedback control system. Three rats were chronically implanted with microelectrode arrays in both the motor and visual cortices. The rats were subsequently trained over a period of weeks to modulate their motor cortex ensemble unit activity upon delivery of intra-cortical microstimulation (ICMS) of the visual cortex in order to receive a food reward. Rats were given continuous feedback via visual cortex ICMS during the response periods that was representative of the motor cortex ensemble dynamics. Analysis revealed that the feedback provided the animals with indicators of the behavioral trials. At the hardware level, this preparation provides a tractable test model for improving the technology of closed-loop neural devices.

A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder.

PubMed

Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

2016-01-01

Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive.

A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder

PubMed Central

Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

2016-01-01

Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive. PMID:28018162

Neural feedback for instantaneous spatiotemporal modulation of afferent pathways in bi-directional brain-machine interfaces.

PubMed

Liu, Jianbo; Khalil, Hassan K; Oweiss, Karim G

2011-10-01

In bi-directional brain-machine interfaces (BMIs), precisely controlling the delivery of microstimulation, both in space and in time, is critical to continuously modulate the neural activity patterns that carry information about the state of the brain-actuated device to sensory areas in the brain. In this paper, we investigate the use of neural feedback to control the spatiotemporal firing patterns of neural ensembles in a model of the thalamocortical pathway. Control of pyramidal (PY) cells in the primary somatosensory cortex (S1) is achieved based on microstimulation of thalamic relay cells through multiple-input multiple-output (MIMO) feedback controllers. This closed loop feedback control mechanism is achieved by simultaneously varying the stimulation parameters across multiple stimulation electrodes in the thalamic circuit based on continuous monitoring of the difference between reference patterns and the evoked responses of the cortical PY cells. We demonstrate that it is feasible to achieve a desired level of performance by controlling the firing activity pattern of a few "key" neural elements in the network. Our results suggest that neural feedback could be an effective method to facilitate the delivery of information to the cortex to substitute lost sensory inputs in cortically controlled BMIs.

Ultrasoft microwire neural electrodes improve chronic tissue integration

PubMed Central

Du, Zhanhong Jeff; Kolarcik, Christi L.; Kozai, Takashi D.Y.; Luebben, Silvia D.; Sapp, Shawn A.; Zheng, Xin Sally; Nabity, James A.; Cui, X. Tracy

2017-01-01

Chronically implanted neural multi-electrode arrays (MEA) are an essential technology for recording electrical signals from neurons and/or modulating neural activity through stimulation. However, current MEAs, regardless of the type, elicit an inflammatory response that ultimately leads to device failure. Traditionally, rigid materials like tungsten and silicon have been employed to interface with the relatively soft neural tissue. The large stiffness mismatch is thought to exacerbate the inflammatory response. In order to minimize the disparity between the device and the brain, we fabricated novel ultrasoft electrodes consisting of elastomers and conducting polymers with mechanical properties much more similar to those of brain tissue than previous neural implants. In this study, these ultrasoft microelectrodes were inserted and released using a stainless steel shuttle with polyethyleneglycol (PEG) glue. The implanted microwires showed functionality in acute neural stimulation. When implanted for 1 or 8 weeks, the novel soft implants demonstrated significantly reduced inflammatory tissue response at week 8 compared to tungsten wires of similar dimension and surface chemistry. Furthermore, a higher degree of cell body distortion was found next to the tungsten implants compared to the polymer implants. Our results support the use of these novel ultrasoft electrodes for long term neural implants. PMID:28185910

A method for compression of intra-cortically-recorded neural signals dedicated to implantable brain-machine interfaces.

PubMed

Shaeri, Mohammad Ali; Sodagar, Amir M

2015-05-01

This paper proposes an efficient data compression technique dedicated to implantable intra-cortical neural recording devices. The proposed technique benefits from processing neural signals in the Discrete Haar Wavelet Transform space, a new spike extraction approach, and a novel data framing scheme to telemeter the recorded neural information to the outside world. Based on the proposed technique, a 64-channel neural signal processor was designed and prototyped as a part of a wireless implantable extra-cellular neural recording microsystem. Designed in a 0.13- μ m standard CMOS process, the 64-channel neural signal processor reported in this paper occupies ∼ 0.206 mm(2) of silicon area, and consumes 94.18 μW when operating under a 1.2-V supply voltage at a master clock frequency of 1.28 MHz.

Evaluating the in vivo glial response to miniaturized parylene cortical probes coated with an ultra-fast degrading polymer to aid insertion.

PubMed

Lo, Meng-Chen; Wang, Shuwu; Singh, Sagar; Damodaran, Vinod B; Ahmed, Ijaz; Coffey, Kevin; Barker, David; Saste, Kshitij; Kals, Karanvir; Kaplan, Hilton M; Kohn, Joachim; Shreiber, David I; Zahn, Jeffrey D

2018-06-01

Despite the feasibility of short-term neural recordings using implantable microelectrodes, attaining reliable, chronic recordings remains a challenge. Most neural recording devices suffer from a long-term tissue response, including gliosis, at the device-tissue interface. It was hypothesized that smaller, more flexible intracortical probes would limit gliosis by providing a better mechanical match with surrounding tissue. This paper describes the in vivo evaluation of flexible parylene microprobes designed to improve the interface with the adjacent neural tissue to limit gliosis and thereby allow for improved recording longevity. The probes were coated with an ultrafast degrading tyrosine-derived polycarbonate (E5005(2K)) polymer that provides temporary mechanical support for device implantation, yet degrades within 2 h post-implantation. A parametric study of probes of varying dimensions and polymer coating thicknesses were implanted in rat brains. The glial tissue response and neuronal loss were assessed from 72 h to 24 weeks post-implantation via immunohistochemistry. Experimental results suggest that both probe and polymer coating sizes affect the extent of gliosis. When an appropriate sized coating dimension (100 µm  ×  100 µm) and small probe (30 µm  ×  5 µm) was implanted, a minimal post-implantation glial response was observed. No discernible gliosis was detected when compared to tissue where a sham control consisting of a solid degradable polymer shuttle of the same dimensions was inserted. A larger polymer coating (200 µm  ×  200 µm) device induced a more severe glial response at later time points, suggesting that the initial insertion trauma can affect gliosis even when the polymer shuttle degrades rapidly. A larger degree of gliosis was also observed when comparing a larger sized probe (80 µm  ×  5 µm) to a smaller probe (30 µm  ×  5 µm) using the same polymer coating size (100 µm  ×  100 µm). There was no significant neuronal loss around the implantation sites for most device candidates except the group with largest polymer coating and probe sizes. These results suggest that: (1) the degree of mechanical trauma at device implantation and mechanical mismatches at the probe-tissue interface affect long term gliosis; (2) smaller, more flexible probes may minimize the glial response to provide improved tissue biocompatibility when used for chronic neural signal recording; and (3) some degree of glial scarring did not significantly affect neuronal distribution around the probe.

Wireless microsensor network solutions for neurological implantable devices

NASA Astrophysics Data System (ADS)

Abraham, Jose K.; Whitchurch, Ashwin; Varadan, Vijay K.

2005-05-01

The design and development of wireless mocrosensor network systems for the treatment of many degenerative as well as traumatic neurological disorders is presented in this paper. Due to the advances in micro and nano sensors and wireless systems, the biomedical sensors have the potential to revolutionize many areas in healthcare systems. The integration of nanodevices with neurons that are in communication with smart microsensor systems has great potential in the treatment of many neurodegenerative brain disorders. It is well established that patients suffering from either Parkinson"s disease (PD) or Epilepsy have benefited from the advantages of implantable devices in the neural pathways of the brain to alter the undesired signals thus restoring proper function. In addition, implantable devices have successfully blocked pain signals and controlled various pelvic muscles in patients with urinary and fecal incontinence. Even though the existing technology has made a tremendous impact on controlling the deleterious effects of disease, it is still in its infancy. This paper presents solutions of many problems of today's implantable and neural-electronic interface devices by combining nanowires and microelectronics with BioMEMS and applying them at cellular level for the development of a total wireless feedback control system. The only device that will actually be implanted in this research is the electrodes. All necessary controllers will be housed in accessories that are outside the body that communicate with the implanted electrodes through tiny inductively-coupled antennas. A Parkinson disease patient can just wear a hat-system close to the implantable neural probe so that the patient is free to move around, while the sensors continually monitor, record, transmit all vital information to health care specialist. In the event of a problem, the system provides an early warning to the patient while they are still mobile thus providing them the opportunity to react and trigger the feed back system or contact a point-of-care office that can remotely control the implantable system. The remote monitoring technology can be adaptable to EEG monitoring of children with epilepsy, implantable cardioverters/defibrillators, pacemakers, chronic pain management systems, treatment for sleep disorders, patients with implantable devices for diabetes. In addition, the development of a wireless neural electronics interface to detect, transmit and analyze neural signals could help patients with spinal injuries to regain some semblance of mobile activity.

Automatic Speech Recognition from Neural Signals: A Focused Review.

PubMed

Herff, Christian; Schultz, Tanja

2016-01-01

Speech interfaces have become widely accepted and are nowadays integrated in various real-life applications and devices. They have become a part of our daily life. However, speech interfaces presume the ability to produce intelligible speech, which might be impossible due to either loud environments, bothering bystanders or incapabilities to produce speech (i.e., patients suffering from locked-in syndrome). For these reasons it would be highly desirable to not speak but to simply envision oneself to say words or sentences. Interfaces based on imagined speech would enable fast and natural communication without the need for audible speech and would give a voice to otherwise mute people. This focused review analyzes the potential of different brain imaging techniques to recognize speech from neural signals by applying Automatic Speech Recognition technology. We argue that modalities based on metabolic processes, such as functional Near Infrared Spectroscopy and functional Magnetic Resonance Imaging, are less suited for Automatic Speech Recognition from neural signals due to low temporal resolution but are very useful for the investigation of the underlying neural mechanisms involved in speech processes. In contrast, electrophysiologic activity is fast enough to capture speech processes and is therefor better suited for ASR. Our experimental results indicate the potential of these signals for speech recognition from neural data with a focus on invasively measured brain activity (electrocorticography). As a first example of Automatic Speech Recognition techniques used from neural signals, we discuss the Brain-to-text system.

Recording nerve signals in canine sciatic nerves with a flexible penetrating microelectrode array

NASA Astrophysics Data System (ADS)

Byun, Donghak; Cho, Sung-Joon; Lee, Byeong Han; Min, Joongkee; Lee, Jong-Hyun; Kim, Sohee

2017-08-01

Objective. Previously, we presented the fabrication and characterization of a flexible penetrating microelectrode array (FPMA) as a neural interface device. In the present study, we aim to prove the feasibility of the developed FPMA as a chronic intrafascicular recording tool for peripheral applications. Approach. For recording from the peripheral nerves of medium-sized animals, the FPMA was integrated with an interconnection cable and other parts that were designed to fit canine sciatic nerves. The uniformity of tip exposure and in vitro electrochemical properties of the electrodes were characterized. The capability of the device to acquire in vivo electrophysiological signals was evaluated by implanting the FPMA assembly in canine sciatic nerves acutely as well as chronically for 4 weeks. We also examined the histology of implanted tissues to evaluate the damage caused by the device. Main results. Throughout recording sessions, we observed successful multi-channel recordings (up to 73% of viable electrode channels) of evoked afferent and spontaneous nerve unit spikes with high signal quality (SNR  >  4.9). Also, minor influences of the device implantation on the morphology of nerve tissues were found. Significance. The presented results demonstrate the viability of the developed FPMA device in the peripheral nerves of medium-sized animals, thereby bringing us a step closer to human applications. Furthermore, the obtained data provide a driving force toward a further study for device improvements to be used as a bidirectional neural interface in humans.

Improved head direction command classification using an optimised Bayesian neural network.

PubMed

Nguyen, Son T; Nguyen, Hung T; Taylor, Philip B; Middleton, James

2006-01-01

Assistive technologies have recently emerged to improve the quality of life of severely disabled people by enhancing their independence in daily activities. Since many of those individuals have limited or non-existing control from the neck downward, alternative hands-free input modalities have become very important for these people to access assistive devices. In hands-free control, head movement has been proved to be a very effective user interface as it can provide a comfortable, reliable and natural way to access the device. Recently, neural networks have been shown to be useful not only for real-time pattern recognition but also for creating user-adaptive models. Since multi-layer perceptron neural networks trained using standard back-propagation may cause poor generalisation, the Bayesian technique has been proposed to improve the generalisation and robustness of these networks. This paper describes the use of Bayesian neural networks in developing a hands-free wheelchair control system. The experimental results show that with the optimised architecture, classification Bayesian neural networks can detect head commands of wheelchair users accurately irrespective to their levels of injuries.

A review on mechanical considerations for chronically-implanted neural probes

NASA Astrophysics Data System (ADS)

Lecomte, Aziliz; Descamps, Emeline; Bergaud, Christian

2018-06-01

This review intends to present a comprehensive analysis of the mechanical considerations for chronically-implanted neural probes. Failure of neural electrical recordings or stimulation over time has shown to arise from foreign body reaction and device material stability. It seems that devices that match most closely with the mechanical properties of the brain would be more likely to reduce the mechanical stress at the probe/tissue interface, thus improving body acceptance. The use of low Young’s modulus polymers instead of hard substrates is one way to enhance this mechanical mimetism, though compliance can be achieved through a variety of means. The reduction of probe width and thickness in comparison to a designated length, the use of soft hydrogel coatings and the release in device tethering to the skull, can also improve device compliance. Paradoxically, the more compliant the device, the more likely it will fail during the insertion process in the brain. Strategies have multiplied this past decade to offer partial or temporary stiffness to the device to overcome this buckling effect. A detailed description of the probe insertion mechanisms is provided to analyze potential sources of implantation failure and the need for a mechanically-enhancing structure. This leads us to present an overview of the strategies that have been put in place over the last ten years to overcome buckling issues. Particularly, great emphasis is put on bioresorbable polymers and their assessment for neural applications. Finally, a discussion is provided on some of the key features for the design of mechanically-reliable, polymer-based next generation of chronic neuroprosthetic devices.

Neural recording and modulation technologies

NASA Astrophysics Data System (ADS)

Chen, Ritchie; Canales, Andres; Anikeeva, Polina

2017-01-01

In the mammalian nervous system, billions of neurons connected by quadrillions of synapses exchange electrical, chemical and mechanical signals. Disruptions to this network manifest as neurological or psychiatric conditions. Despite decades of neuroscience research, our ability to treat or even to understand these conditions is limited by the capability of tools to probe the signalling complexity of the nervous system. Although orders of magnitude smaller and computationally faster than neurons, conventional substrate-bound electronics do not recapitulate the chemical and mechanical properties of neural tissue. This mismatch results in a foreign-body response and the encapsulation of devices by glial scars, suggesting that the design of an interface between the nervous system and a synthetic sensor requires additional materials innovation. Advances in genetic tools for manipulating neural activity have fuelled the demand for devices that are capable of simultaneously recording and controlling individual neurons at unprecedented scales. Recently, flexible organic electronics and bio- and nanomaterials have been developed for multifunctional and minimally invasive probes for long-term interaction with the nervous system. In this Review, we discuss the design lessons from the quarter-century-old field of neural engineering, highlight recent materials-driven progress in neural probes and look at emergent directions inspired by the principles of neural transduction.

Hybrid Thin Film Organosilica Sol-Gel Coatings To Support Neuronal Growth and Limit Astrocyte Growth.

PubMed

Capeletti, Larissa Brentano; Cardoso, Mateus Borba; Dos Santos, João Henrique Zimnoch; He, Wei

2016-10-07

Thin films of silica prepared by a sol-gel process are becoming a feasible coating option for surface modification of implantable neural sensors without imposing adverse effects on the devices' electrical properties. In order to advance the application of such silica-based coatings in the context of neural interfacing, the characteristics of silica sol-gel are further tailored to gain active control of interactions between cells and the coating materials. By incorporating various readily available organotrialkoxysilanes carrying distinct organic functional groups during the sol-gel process, a library of hybrid organosilica coatings is developed and investigated. In vitro neural cultures using PC12 cells and primary cortical neurons both reveal that, among these different types of hybrid organosilica, the introduction of aminopropyl groups drastically transforms the silica into robust neural permissive substrate, supporting neuron adhesion and neurite outgrowth. Moreover, when this organosilica is cultured with astrocytes, a key type of glial cells responsible for glial scar response toward neural implants, such cell growth promoting effect is not observed. These findings highlight the potential of organo-group-bearing silica sol-gel to function as advanced coating materials to selectively modulate cell response and promote neural integration with implantable sensing devices.

Implantable optoelectronic probes for in vivo optogenetics.

PubMed

Iseri, Ege; Kuzum, Duygu

2017-06-01

More than a decade has passed since optics and genetics came together and lead to the emerging technologies of optogenetics. The advent of light-sensitive opsins made it possible to optically trigger the neurons into activation or inhibition by using visible light. The importance of spatiotemporally isolating a segment of a neural network and controlling nervous signaling in a precise manner has driven neuroscience researchers and engineers to invest great efforts in designing high precision in vivo implantable devices. These efforts have focused on delivery of sufficient power to deep brain regions, while monitoring neural activity with high resolution and fidelity. In this review, we report the progress made in the field of hybrid optoelectronic neural interfaces that combine optical stimulation with electrophysiological recordings. Different approaches that incorporate optical or electrical components on implantable devices are discussed in detail. Advantages of various different designs as well as practical and fundamental limitations are summarized to illuminate the future of neurotechnology development.

Implantable optoelectronic probes for in vivo optogenetics

NASA Astrophysics Data System (ADS)

Iseri, Ege; Kuzum, Duygu

2017-06-01

More than a decade has passed since optics and genetics came together and lead to the emerging technologies of optogenetics. The advent of light-sensitive opsins made it possible to optically trigger the neurons into activation or inhibition by using visible light. The importance of spatiotemporally isolating a segment of a neural network and controlling nervous signaling in a precise manner has driven neuroscience researchers and engineers to invest great efforts in designing high precision in vivo implantable devices. These efforts have focused on delivery of sufficient power to deep brain regions, while monitoring neural activity with high resolution and fidelity. In this review, we report the progress made in the field of hybrid optoelectronic neural interfaces that combine optical stimulation with electrophysiological recordings. Different approaches that incorporate optical or electrical components on implantable devices are discussed in detail. Advantages of various different designs as well as practical and fundamental limitations are summarized to illuminate the future of neurotechnology development.

Glove-TalkII--a neural-network interface which maps gestures to parallel formant speech synthesizer controls.

PubMed

Fels, S S; Hinton, G E

1998-01-01

Glove-TalkII is a system which translates hand gestures to speech through an adaptive interface. Hand gestures are mapped continuously to ten control parameters of a parallel formant speech synthesizer. The mapping allows the hand to act as an artificial vocal tract that produces speech in real time. This gives an unlimited vocabulary in addition to direct control of fundamental frequency and volume. Currently, the best version of Glove-TalkII uses several input devices (including a Cyberglove, a ContactGlove, a three-space tracker, and a foot pedal), a parallel formant speech synthesizer, and three neural networks. The gesture-to-speech task is divided into vowel and consonant production by using a gating network to weight the outputs of a vowel and a consonant neural network. The gating network and the consonant network are trained with examples from the user. The vowel network implements a fixed user-defined relationship between hand position and vowel sound and does not require any training examples from the user. Volume, fundamental frequency, and stop consonants are produced with a fixed mapping from the input devices. One subject has trained to speak intelligibly with Glove-TalkII. He speaks slowly but with far more natural sounding pitch variations than a text-to-speech synthesizer.

Optimizing the performance of neural interface devices with hybrid poly(3,4-ethylene dioxythiophene) (PEDOT)

NASA Astrophysics Data System (ADS)

Kuo, Chin-chen

This thesis describes methods for improving the performance of poly(3,4-ethylenedioxythiophene) (PEDOT) as a direct neural interfacing material. The chronic foreign body response is always a challenge for implanted bionic devices. After long-term implantation (typically 2-4 weeks), insulating glial scars form around the devices, inhibiting signal transmission, which ultimately leads to device failure. The mechanical mismatch at the device-tissue interface is one of the issues that has been associated with chronic foreign body response. Another challenge for using PEDOT as a neural interface material is its mechanical failure after implantation. We observed cracking and delamination of PEDOT coatings on devices after extended implantations. In the first part of this thesis, we present a novel method for directly measuring the mechanical properties of a PEDOT thin film. Before investigating methods to improve the mechanical behavior of PEDOT, a comprehensive understanding of the mechanical properties of PEDOT thin film is required. A PEDOT thin film was machined into a dog-bone shape specimen with a dual beam FIB-SEM. With an OmniProbe, this PEDOT specimen could be attached onto a force sensor, while the other side was attached to OmniProbe. By moving the OmniProbe, the specimen could be deformed in tension, and a force sensor recorded the applied load on the sample simultaneously. Mechanical tensile tests were conducted in the FIB-SEM chamber along with in situ observation. With precise force measurement from the force sensor and the corresponding high resolution SEM images, we were able to convert the data to a stress-strain curve for further analysis. By analyzing these stress-strain curves, we were able to obtain information about PEDOT including the Young's modulus, strength of failure, strain to failure, and toughness (energy to failure). This information should be useful for future material selection and molecular design for specific applications. The second section of this thesis is mainly focused on developing a soft and conductive material by in situ PEDOT polymerization into soft matrix. First, PEDOT was in situ polymerized into extracellular matrix (ECM) as a conductive, soft, and bioactive material for neural interfacing. ECM is basically a matrix of proteins which provides biological cues with the potential to promote neural attachment. We modified the electrode to a needle shape, which could be inserted into the ECM film. The limited surface area on the electrode and the close contact with ECM made it possible to polymerize PEDOT into the ECM more easily. The conductivity of PEDOT-ECM was confirmed to be similar to intrinsic PEDOT. A cell adhesion test using the PC12 cell line was used to evaluate its biocompatibility. PEDOT-ECM shows improved cell adhesion for PC12 cells, as compared either bare metal electrodes or PEDOT coated surfaces. In the future this approach may be elevated to an " autologous" concept, where the ECM could be derived from the host patients themselves to further reduce the foreign body response. Second, low modulus hydrogels were used as templates for PEDOT polymerization. EDOT monomers were premixed into agarose hydrogels. The electrochemical polymerization was typically conducted in potentiostatic (constant voltage) mode with working voltage of 2 V. After 0.8 C/cm2 charge density, a significant dark blue cloud was observed indicating that PEDOT was in situ polymerized into hydrogel matrix. A series of studies was conducted to confirm the improved mechanical properties, electrical properties and biocompatibility of the PEDOT-gel as compared to the typical solid PEDOT. Animal studies were conducted to evaluate the performance of PEDOT-gel coated electrode in vivo. Rats were used as the animal model with 3 rats in each group of bare electrode, PEDOT-coated, and PEDOT-gel coated electrode (n=9). The in vivo impedance was used to confirm the performance of the implanted electrodes. The results showed that the impedance had a significant increase after 4 weeks with the bare and solid PEDOT-coated electrode. This is consistent with the typical glial scar encapsulation around the electrode leading to an impedance increase. PEDOT-gel presents consistently low impedance along with 10 weeks implantation implying there was much less reactive response around the insertion site. These in vivo experiments on PEDOT-gels suggest that PEDOT-gels are promising neural interfacing materials for patients clinically.

A TinyOS-enabled MICA2-based wireless neural interface.

PubMed

Farshchi, Shahin; Nuyujukian, Paul H; Pesterev, Aleksey; Mody, Istvan; Judy, Jack W

2006-07-01

Existing approaches used to develop compact low-power multichannel wireless neural recording systems range from creating custom-integrated circuits to assembling commercial-off-the-shelf (COTS) PC-based components. Custom-integrated-circuit designs yield extremely compact and low-power devices at the expense of high development and upgrade costs and turn-around times, while assembling COTS-PC-technology yields high performance at the expense of large system size and increased power consumption. To achieve a balance between implementing an ultra-compact custom-fabricated neural transceiver and assembling COTS-PC-technology, an overlay of a neural interface upon the TinyOS-based MICA2 platform is described. The system amplifies, digitally encodes, and transmits neural signals real-time at a rate of 9.6 kbps, while consuming less than 66 mW of power. The neural signals are received and forwarded to a client PC over a serial connection. This data rate can be divided for recording on up to 6 channels, with a resolution of 8 bits/sample. This work demonstrates the strengths and limitations of the TinyOS-based sensor technology as a foundation for chronic remote biological monitoring applications and, thus, provides an opportunity to create a system that can leverage from the frequent networking and communications advancements being made by the global TinyOS-development community.

Unscented Kalman Filter for Brain-Machine Interfaces

PubMed Central

Li, Zheng; O'Doherty, Joseph E.; Hanson, Timothy L.; Lebedev, Mikhail A.; Henriquez, Craig S.; Nicolelis, Miguel A. L.

2009-01-01

Brain machine interfaces (BMIs) are devices that convert neural signals into commands to directly control artificial actuators, such as limb prostheses. Previous real-time methods applied to decoding behavioral commands from the activity of populations of neurons have generally relied upon linear models of neural tuning and were limited in the way they used the abundant statistical information contained in the movement profiles of motor tasks. Here, we propose an n-th order unscented Kalman filter which implements two key features: (1) use of a non-linear (quadratic) model of neural tuning which describes neural activity significantly better than commonly-used linear tuning models, and (2) augmentation of the movement state variables with a history of n-1 recent states, which improves prediction of the desired command even before incorporating neural activity information and allows the tuning model to capture relationships between neural activity and movement at multiple time offsets simultaneously. This new filter was tested in BMI experiments in which rhesus monkeys used their cortical activity, recorded through chronically implanted multielectrode arrays, to directly control computer cursors. The 10th order unscented Kalman filter outperformed the standard Kalman filter and the Wiener filter in both off-line reconstruction of movement trajectories and real-time, closed-loop BMI operation. PMID:19603074

Evaluating the in vivo glial response to miniaturized parylene cortical probes coated with an ultra-fast degrading polymer to aid insertion

NASA Astrophysics Data System (ADS)

Lo, Meng-chen; Wang, Shuwu; Singh, Sagar; Damodaran, Vinod B.; Ahmed, Ijaz; Coffey, Kevin; Barker, David; Saste, Kshitij; Kals, Karanvir; Kaplan, Hilton M.; Kohn, Joachim; Shreiber, David I.; Zahn, Jeffrey D.

2018-06-01

Objective. Despite the feasibility of short-term neural recordings using implantable microelectrodes, attaining reliable, chronic recordings remains a challenge. Most neural recording devices suffer from a long-term tissue response, including gliosis, at the device–tissue interface. It was hypothesized that smaller, more flexible intracortical probes would limit gliosis by providing a better mechanical match with surrounding tissue. Approach. This paper describes the in vivo evaluation of flexible parylene microprobes designed to improve the interface with the adjacent neural tissue to limit gliosis and thereby allow for improved recording longevity. The probes were coated with an ultrafast degrading tyrosine-derived polycarbonate (E5005(2K)) polymer that provides temporary mechanical support for device implantation, yet degrades within 2 h post-implantation. A parametric study of probes of varying dimensions and polymer coating thicknesses were implanted in rat brains. The glial tissue response and neuronal loss were assessed from 72 h to 24 weeks post-implantation via immunohistochemistry. Main results. Experimental results suggest that both probe and polymer coating sizes affect the extent of gliosis. When an appropriate sized coating dimension (100 µm  ×  100 µm) and small probe (30 µm  ×  5 µm) was implanted, a minimal post-implantation glial response was observed. No discernible gliosis was detected when compared to tissue where a sham control consisting of a solid degradable polymer shuttle of the same dimensions was inserted. A larger polymer coating (200 µm  ×  200 µm) device induced a more severe glial response at later time points, suggesting that the initial insertion trauma can affect gliosis even when the polymer shuttle degrades rapidly. A larger degree of gliosis was also observed when comparing a larger sized probe (80 µm  ×  5 µm) to a smaller probe (30 µm  ×  5 µm) using the same polymer coating size (100 µm  ×  100 µm). There was no significant neuronal loss around the implantation sites for most device candidates except the group with largest polymer coating and probe sizes. Significance. These results suggest that: (1) the degree of mechanical trauma at device implantation and mechanical mismatches at the probe-tissue interface affect long term gliosis; (2) smaller, more flexible probes may minimize the glial response to provide improved tissue biocompatibility when used for chronic neural signal recording; and (3) some degree of glial scarring did not significantly affect neuronal distribution around the probe.

Development of regenerative peripheral nerve interfaces for motor control of neuroprosthetic devices

NASA Astrophysics Data System (ADS)

Kemp, Stephen W. P.; Urbanchek, Melanie G.; Irwin, Zachary T.; Chestek, Cynthia A.; Cederna, Paul S.

2017-05-01

Traumatic peripheral nerve injuries suffered during amputation commonly results in debilitating neuropathic pain in the affected limb. Modern prosthetic technologies allow for intuitive, simultaneous control of multiple degrees of freedom. However, these state-of-the-art devices require separate, independent control signals for each degree of freedom, which is currently not possible. As a result, amputees reject up to 75% of myoelectric devices preferring instead to use body-powered artificial limbs which offer subtle sensory feedback. Without meaningful and intuitive sensory feedback, even the most advanced myoelectric prostheses remain insensate, burdensome, and are associated with enormous cognitive demand and mental fatigue. The ideal prosthetic device is one which is capable of providing intuitive somatosensory feedback essential for interaction with the environment. Critical to the design of such a bioprosthetic device is the development of a reliable biologic interface between human and machine. This ideal patient-prosthetic interface allows for transmission of both afferent somatosensory information and efferent motor signals for a closed-loop feedback system of neural control. Our lab has developed the Regenerative Peripheral Nerve Interface (RPNI) as a biologic nerve interface designed for stable integration of a prosthetic device with transected peripheral nerves in a residual limb. The RPNI is constructed by surgically implanting the distal end of a transected peripheral nerve into an autogenous muscle graft. Animal experiments in our lab have shown recording of motor signals from RPNI's implanted into both rodents and monkeys. Here, we achieve high amplitude EMG signals with a high signal to noise (SNR) ratio.

Implementation of neuromorphic systems: from discrete components to analog VLSI chips (testing and communication issues).

PubMed

Dante, V; Del Giudice, P; Mattia, M

2001-01-01

We review a series of implementations of electronic devices aiming at imitating to some extent structure and function of simple neural systems, with particular emphasis on communication issues. We first provide a short overview of general features of such "neuromorphic" devices and the implications of setting up "tests" for them. We then review the developments directly related to our work at the Istituto Superiore di Sanità (ISS): a pilot electronic neural network implementing a simple classifier, autonomously developing internal representations of incoming stimuli; an output network, collecting information from the previous classifier and extracting the relevant part to be forwarded to the observer; an analog, VLSI (very large scale integration) neural chip implementing a recurrent network of spiking neurons and plastic synapses, and the test setup for it; a board designed to interface the standard PCI (peripheral component interconnect) bus of a PC with a special purpose, asynchronous bus for communication among neuromorphic chips; a short and preliminary account of an application-oriented device, taking advantage of the above communication infrastructure.

Optimal input selection for neural machine interfaces predicting multiple non-explicit outputs.

PubMed

Krepkovich, Eileen T; Perreault, Eric J

2008-01-01

This study implemented a novel algorithm that optimally selects inputs for neural machine interface (NMI) devices intended to control multiple outputs and evaluated its performance on systems lacking explicit output. NMIs often incorporate signals from multiple physiological sources and provide predictions for multidimensional control, leading to multiple-input multiple-output systems. Further, NMIs often are used with subjects who have motor disabilities and thus lack explicit motor outputs. Our algorithm was tested on simulated multiple-input multiple-output systems and on electromyogram and kinematic data collected from healthy subjects performing arm reaches. Effects of output noise in simulated systems indicated that the algorithm could be useful for systems with poor estimates of the output states, as is true for systems lacking explicit motor output. To test efficacy on physiological data, selection was performed using inputs from one subject and outputs from a different subject. Selection was effective for these cases, again indicating that this algorithm will be useful for predictions where there is no motor output, as often is the case for disabled subjects. Further, prediction results generalized for different movement types not used for estimation. These results demonstrate the efficacy of this algorithm for the development of neural machine interfaces.

[Neural prostheses and neuromodulation : Research and clinical practice in therapy and rehabilitation].

PubMed

Stieglitz, T

2010-08-01

Stimulation of the nervous system with the aid of electrical active implants has changed the therapy of neurological diseases and rehabilitation of lost functions and has expanded clinical practice within the last few years. Alleviation of effects of neurodegenerative diseases, therapy of psychiatric diseases, the functional restoration of hearing as well as other applications have been transferred successfully into clinical practice. Other approaches are still under development in preclinical and clinical trials. The restoration of sight by implantable electronic systems that interface with the retina in the eye is an example how technological progress promotes novel medical devices. The idea of using the electrical signal of the brain to control technical devices and (neural) prostheses is driving current research in the field of brain-computer interfaces. The benefit for the patient always has to be balanced with the risks and side effects of those implants in comparison to medicinal and surgical treatments. How these and other developments become established in practice depends finally on their acceptance by the patients and the reimbursement of their costs.

A lysinated thiophene-based semiconductor as a multifunctional neural bioorganic interface.

PubMed

Bonetti, Simone; Pistone, Assunta; Brucale, Marco; Karges, Saskia; Favaretto, Laura; Zambianchi, Massimo; Posati, Tamara; Sagnella, Anna; Caprini, Marco; Toffanin, Stefano; Zamboni, Roberto; Camaioni, Nadia; Muccini, Michele; Melucci, Manuela; Benfenati, Valentina

2015-06-03

Lysinated molecular organic semiconductors are introduced as valuable multifunctional platforms for neural cells growth and interfacing. Cast films of quaterthiophene (T4) semiconductor covalently modified with lysine-end moieties (T4Lys) are fabricated and their stability, morphology, optical/electrical, and biocompatibility properties are characterized. T4Lys films exhibit fluorescence and electronic transport as generally observed for unsubstituted oligothiophenes combined to humidity-activated ionic conduction promoted by the charged lysine-end moieties. The Lys insertion in T4 enables adhesion of primary culture of rat dorsal root ganglion (DRG), which is not achievable by plating cells on T4. Notably, on T4Lys, the number on adhering neurons/area is higher and displays a twofold longer neurite length than neurons plated on glass coated with poly-l-lysine. Finally, by whole-cell patch-clamp, it is shown that the biofunctionality of neurons cultured on T4Lys is preserved. The present study introduces an innovative concept for organic material neural interface that combines optical and iono-electronic functionalities with improved biocompatibility and neuron affinity promoted by Lys linkage and the softness of organic semiconductors. Lysinated organic semiconductors could set the scene for the fabrication of simplified bioorganic devices geometry for cells bidirectional communication or optoelectronic control of neural cells biofunctionality. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System

PubMed Central

Milde, Moritz B.; Blum, Hermann; Dietmüller, Alexander; Sumislawska, Dora; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia

2017-01-01

Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware. PMID:28747883

Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System.

PubMed

Milde, Moritz B; Blum, Hermann; Dietmüller, Alexander; Sumislawska, Dora; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia

2017-01-01

Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware.

Dissolvable films of silk fibroin for ultrathin conformal bio-integrated electronics.

PubMed

Kim, Dae-Hyeong; Viventi, Jonathan; Amsden, Jason J; Xiao, Jianliang; Vigeland, Leif; Kim, Yun-Soung; Blanco, Justin A; Panilaitis, Bruce; Frechette, Eric S; Contreras, Diego; Kaplan, David L; Omenetto, Fiorenzo G; Huang, Yonggang; Hwang, Keh-Chih; Zakin, Mitchell R; Litt, Brian; Rogers, John A

2010-06-01

Electronics that are capable of intimate, non-invasive integration with the soft, curvilinear surfaces of biological tissues offer important opportunities for diagnosing and treating disease and for improving brain/machine interfaces. This article describes a material strategy for a type of bio-interfaced system that relies on ultrathin electronics supported by bioresorbable substrates of silk fibroin. Mounting such devices on tissue and then allowing the silk to dissolve and resorb initiates a spontaneous, conformal wrapping process driven by capillary forces at the biotic/abiotic interface. Specialized mesh designs and ultrathin forms for the electronics ensure minimal stresses on the tissue and highly conformal coverage, even for complex curvilinear surfaces, as confirmed by experimental and theoretical studies. In vivo, neural mapping experiments on feline animal models illustrate one mode of use for this class of technology. These concepts provide new capabilities for implantable and surgical devices.

Dissolvable Films of Silk Fibroin for Ultrathin, Conformal Bio-Integrated Electronics

PubMed Central

Kim, Dae-Hyeong; Viventi, Jonathan; Amsden, Jason J.; Xiao, Jianliang; Vigeland, Leif; Kim, Yun-Soung; Blanco, Justin A.; Panilaitis, Bruce; Frechette, Eric S.; Contreras, Diego; Kaplan, David L.; Omenetto, Fiorenzo G.; Huang, Yonggang; Hwang, Keh-Chih; Zakin, Mitchell R.; Litt, Brian; Rogers, John A.

2011-01-01

Electronics that are capable of intimate, non-invasive integration with the soft, curvilinear surfaces of biological tissues offer important opportunities for diagnosing and treating disease and for improving brain-machine interfaces. This paper describes a material strategy for a type of bio-interfaced system that relies on ultrathin electronics supported by bioresorbable substrates of silk fibroin. Mounting such devices on tissue and then allowing the silk to dissolve and resorb initiates a spontaneous, conformal wrapping process driven by capillary forces at the biotic/abiotic interface. Specialized mesh designs and ultrathin forms for the electronics ensure minimal stresses on the tissue and highly conformal coverage, even for complex curvilinear surfaces, as confirmed by experimental and theoretical studies. In vivo, neural mapping experiments on feline animal models illustrate one mode of use for this class of technology. These concepts provide new capabilities for implantable or surgical devices. PMID:20400953

Dissolvable films of silk fibroin for ultrathin conformal bio-integrated electronics

NASA Astrophysics Data System (ADS)

Kim, Dae-Hyeong; Viventi, Jonathan; Amsden, Jason J.; Xiao, Jianliang; Vigeland, Leif; Kim, Yun-Soung; Blanco, Justin A.; Panilaitis, Bruce; Frechette, Eric S.; Contreras, Diego; Kaplan, David L.; Omenetto, Fiorenzo G.; Huang, Yonggang; Hwang, Keh-Chih; Zakin, Mitchell R.; Litt, Brian; Rogers, John A.

2010-06-01

Electronics that are capable of intimate, non-invasive integration with the soft, curvilinear surfaces of biological tissues offer important opportunities for diagnosing and treating disease and for improving brain/machine interfaces. This article describes a material strategy for a type of bio-interfaced system that relies on ultrathin electronics supported by bioresorbable substrates of silk fibroin. Mounting such devices on tissue and then allowing the silk to dissolve and resorb initiates a spontaneous, conformal wrapping process driven by capillary forces at the biotic/abiotic interface. Specialized mesh designs and ultrathin forms for the electronics ensure minimal stresses on the tissue and highly conformal coverage, even for complex curvilinear surfaces, as confirmed by experimental and theoretical studies. In vivo, neural mapping experiments on feline animal models illustrate one mode of use for this class of technology. These concepts provide new capabilities for implantable and surgical devices.

An intensive insulinotherapy mobile phone application built on artificial intelligence techniques.

PubMed

Curran, Kevin; Nichols, Eric; Xie, Ermai; Harper, Roy

2010-01-01

Software to help control diabetes is currently an embryonic market with the main activity to date focused mainly on the development of noncomputerized solutions, such as cardboard calculators or computerized solutions that use "flat" computer models, which are applied to each person without taking into account their individual lifestyles. The development of true, mobile device-driven health applications has been hindered by the lack of tools available in the past and the sheer lack of mobile devices on the market. This has now changed, however, with the availability of pocket personal computer handsets. This article describes a solution in the form of an intelligent neural network running on mobile devices, allowing people with diabetes access to it regardless of their location. Utilizing an easy to learn and use multipanel user interface, people with diabetes can run the software in real time via an easy to use graphical user interface. The neural network consists of four neurons. The first is glucose. If the user's current glucose level is within the target range, the glucose weight is then multiplied by zero. If the glucose level is high, then there will be a positive value multiplied to the weight, resulting in a positive amount of insulin to be injected. If the user's glucose level is low, then the weights will be multiplied by a negative value, resulting in a decrease in the overall insulin dose. A minifeasibility trial was carried out at a local hospital under a consultant endocrinologist in Belfast. The short study ran for 2 weeks with six patients. The main objectives were to investigate the user interface, test the remote sending of data over a 3G network to a centralized server at the university, and record patient data for further proofing of the neural network. We also received useful feedback regarding the user interface and the feasibility of handing real-world patients a new mobile phone. Results of this short trial confirmed to a large degree that our approach (which also can be known as intensive insulinotherapy) has value and perhaps that our neural network approach has implications for future intelligent insulin pumps. Currently, there is no software available to tell people with diabetes how much insulin to inject in accordance with their lifestyle and individual inputs, which leads to adjustments in software predictions on the amount of insulin to inject. We have taken initial steps to supplement the knowledge and skills of health care professionals in controlling insulin levels on a daily basis using a mobile device for people who are less able to manage their disease, especially children and young adults. 2010 Diabetes Technology Society.

An Intensive Insulinotherapy Mobile Phone Application Built on Artificial Intelligence Techniques

PubMed Central

Curran, Kevin; Nichols, Eric; Xie, Ermai; Harper, Roy

2010-01-01

Background Software to help control diabetes is currently an embryonic market with the main activity to date focused mainly on the development of noncomputerized solutions, such as cardboard calculators or computerized solutions that use “flat” computer models, which are applied to each person without taking into account their individual lifestyles. The development of true, mobile device-driven health applications has been hindered by the lack of tools available in the past and the sheer lack of mobile devices on the market. This has now changed, however, with the availability of pocket personal computer handsets. Method This article describes a solution in the form of an intelligent neural network running on mobile devices, allowing people with diabetes access to it regardless of their location. Utilizing an easy to learn and use multipanel user interface, people with diabetes can run the software in real time via an easy to use graphical user interface. The neural network consists of four neurons. The first is glucose. If the user's current glucose level is within the target range, the glucose weight is then multiplied by zero. If the glucose level is high, then there will be a positive value multiplied to the weight, resulting in a positive amount of insulin to be injected. If the user's glucose level is low, then the weights will be multiplied by a negative value, resulting in a decrease in the overall insulin dose. Results A minifeasibility trial was carried out at a local hospital under a consultant endocrinologist in Belfast. The short study ran for 2 weeks with six patients. The main objectives were to investigate the user interface, test the remote sending of data over a 3G network to a centralized server at the university, and record patient data for further proofing of the neural network. We also received useful feedback regarding the user interface and the feasibility of handing real-world patients a new mobile phone. Results of this short trial confirmed to a large degree that our approach (which also can be known as intensive insulinotherapy) has value and perhaps that our neural network approach has implications for future intelligent insulin pumps. Conclusions Currently, there is no software available to tell people with diabetes how much insulin to inject in accordance with their lifestyle and individual inputs, which leads to adjustments in software predictions on the amount of insulin to inject. We have taken initial steps to supplement the knowledge and skills of health care professionals in controlling insulin levels on a daily basis using a mobile device for people who are less able to manage their disease, especially children and young adults. PMID:20167186

An integrated neuro-robotic interface for stroke rehabilitation using the NASA X1 powered lower limb exoskeleton.

PubMed

He, Yongtian; Nathan, Kevin; Venkatakrishnan, Anusha; Rovekamp, Roger; Beck, Christopher; Ozdemir, Recep; Francisco, Gerard E; Contreras-Vidal, Jose L

2014-01-01

Stroke remains a leading cause of disability, limiting independent ambulation in survivors, and consequently affecting quality of life (QOL). Recent technological advances in neural interfacing with robotic rehabilitation devices are promising in the context of gait rehabilitation. Here, the X1, NASA's powered robotic lower limb exoskeleton, is introduced as a potential diagnostic, assistive, and therapeutic tool for stroke rehabilitation. Additionally, the feasibility of decoding lower limb joint kinematics and kinetics during walking with the X1 from scalp electroencephalographic (EEG) signals--the first step towards the development of a brain-machine interface (BMI) system to the X1 exoskeleton--is demonstrated.

A novel asynchronous access method with binary interfaces

PubMed Central

2008-01-01

Background Traditionally synchronous access strategies require users to comply with one or more time constraints in order to communicate intent with a binary human-machine interface (e.g., mechanical, gestural or neural switches). Asynchronous access methods are preferable, but have not been used with binary interfaces in the control of devices that require more than two commands to be successfully operated. Methods We present the mathematical development and evaluation of a novel asynchronous access method that may be used to translate sporadic activations of binary interfaces into distinct outcomes for the control of devices requiring an arbitrary number of commands to be controlled. With this method, users are required to activate their interfaces only when the device under control behaves erroneously. Then, a recursive algorithm, incorporating contextual assumptions relevant to all possible outcomes, is used to obtain an informed estimate of user intention. We evaluate this method by simulating a control task requiring a series of target commands to be tracked by a model user. Results When compared to a random selection, the proposed asynchronous access method offers a significant reduction in the number of interface activations required from the user. Conclusion This novel access method offers a variety of advantages over traditionally synchronous access strategies and may be adapted to a wide variety of contexts, with primary relevance to applications involving direct object manipulation. PMID:18959797

Vertically aligned carbon nanofiber as nano-neuron interface for monitoring neural function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ericson, Milton Nance; McKnight, Timothy E; Melechko, Anatoli Vasilievich

2012-01-01

Neural chips, which are capable of simultaneous, multi-site neural recording and stimulation, have been used to detect and modulate neural activity for almost 30 years. As a neural interface, neural chips provide dynamic functional information for neural decoding and neural control. By improving sensitivity and spatial resolution, nano-scale electrodes may revolutionize neural detection and modulation at cellular and molecular levels as nano-neuron interfaces. We developed a carbon-nanofiber neural chip with lithographically defined arrays of vertically aligned carbon nanofiber electrodes and demonstrated its capability of both stimulating and monitoring electrophysiological signals from brain tissues in vitro and monitoring dynamic information ofmore » neuroplasticity. This novel nano-neuron interface can potentially serve as a precise, informative, biocompatible, and dual-mode neural interface for monitoring of both neuroelectrical and neurochemical activity at the single cell level and even inside the cell.« less

A polymer optoelectronic interface restores light sensitivity in blind rat retinas

NASA Astrophysics Data System (ADS)

Ghezzi, Diego; Antognazza, Maria Rosa; Maccarone, Rita; Bellani, Sebastiano; Lanzarini, Erica; Martino, Nicola; Mete, Maurizio; Pertile, Grazia; Bisti, Silvia; Lanzani, Guglielmo; Benfenati, Fabio

2013-05-01

Interfacing organic electronics with biological substrates offers new possibilities for biotechnology by taking advantage of the beneficial properties exhibited by organic conducting polymers. These polymers have been used for cellular interfaces in several applications, including cellular scaffolds, neural probes, biosensors and actuators for drug release. Recently, an organic photovoltaic blend has been used for neuronal stimulation via a photo-excitation process. Here, we document the use of a single-component organic film of poly(3-hexylthiophene) (P3HT) to trigger neuronal firing upon illumination. Moreover, we demonstrate that this bio-organic interface restores light sensitivity in explants of rat retinas with light-induced photoreceptor degeneration. These findings suggest that all-organic devices may play an important future role in subretinal prosthetic implants.

A polymer optoelectronic interface restores light sensitivity in blind rat retinas

PubMed Central

Ghezzi, Diego; Antognazza, Maria Rosa; Maccarone, Rita; Bellani, Sebastiano; Lanzarini, Erica; Martino, Nicola; Mete, Maurizio; Pertile, Grazia; Bisti, Silvia; Lanzani, Guglielmo; Benfenati, Fabio

2013-01-01

Interfacing organic electronics with biological substrates offers new possibilities for biotechnology due to the beneficial properties exhibited by organic conducting polymers. These polymers have been used for cellular interfaces in several fashions, including cellular scaffolds, neural probes, biosensors and actuators for drug release. Recently, an organic photovoltaic blend has been exploited for neuronal stimulation via a photo-excitation process. Here, we document the use of a single-component organic film of poly(3-hexylthiophene) (P3HT) to trigger neuronal firing upon illumination. Moreover, we demonstrate that this bio-organic interface restored light sensitivity in explants of rat retinas with light-induced photoreceptor degeneration. These findings suggest that all-organic devices may play an important future role in sub-retinal prosthetic implants. PMID:27158258

Portable non-invasive brain-computer interface: challenges and opportunities of optical modalities

NASA Astrophysics Data System (ADS)

Scholl, Clara A.; Hendrickson, Scott M.; Swett, Bruce A.; Fitch, Michael J.; Walter, Erich C.; McLoughlin, Michael P.; Chevillet, Mark A.; Blodgett, David W.; Hwang, Grace M.

2017-05-01

The development of portable non-invasive brain computer interface technologies with higher spatio-temporal resolution has been motivated by the tremendous success seen with implanted devices. This talk will discuss efforts to overcome several major obstacles to viability including approaches that promise to improve spatial and temporal resolution. Optical approaches in particular will be highlighted and the potential benefits of both Blood-Oxygen Level Dependent (BOLD) and Fast Optical Signal (FOS) will be discussed. Early-stage research into the correlations between neural activity and FOS will be explored.

The effect of micro-ECoG substrate footprint on the meningeal tissue response

NASA Astrophysics Data System (ADS)

Schendel, Amelia A.; Nonte, Michael W.; Vokoun, Corinne; Richner, Thomas J.; Brodnick, Sarah K.; Atry, Farid; Frye, Seth; Bostrom, Paige; Pashaie, Ramin; Thongpang, Sanitta; Eliceiri, Kevin W.; Williams, Justin C.

2014-08-01

Objective. There is great interest in designing implantable neural electrode arrays that maximize function while minimizing tissue effects and damage. Although it has been shown that substrate geometry plays a key role in the tissue response to intracortically implanted, penetrating neural interfaces, there has been minimal investigation into the effect of substrate footprint on the tissue response to surface electrode arrays. This study investigates the effect of micro-electrocorticography (micro-ECoG) device geometry on the longitudinal tissue response. Approach. The meningeal tissue response to two micro-ECoG devices with differing geometries was evaluated. The first device had each electrode site and trace individually insulated, with open regions in between, while the second device had a solid substrate, in which all 16 electrode sites were embedded in a continuous insulating sheet. These devices were implanted bilaterally in rats, beneath cranial windows, through which the meningeal tissue response was monitored for one month after implantation. Electrode site impedance spectra were also monitored during the implantation period. Main results. It was observed that collagenous scar tissue formed around both types of devices. However, the distribution of the tissue growth was different between the two array designs. The mesh devices experienced thick tissue growth between the device and the cranial window, and minimal tissue growth between the device and the brain, while the solid device showed the opposite effect, with thick tissue forming between the brain and the electrode sites. Significance. These data suggest that an open architecture device would be more ideal for neural recording applications, in which a low impedance path from the brain to the electrode sites is critical for maximum recording quality.

Adaptive Offset Correction for Intracortical Brain Computer Interfaces

PubMed Central

Homer, Mark L.; Perge, János A.; Black, Michael J.; Harrison, Matthew T.; Cash, Sydney S.; Hochberg, Leigh R.

2014-01-01

Intracortical brain computer interfaces (iBCIs) decode intended movement from neural activity for the control of external devices such as a robotic arm. Standard approaches include a calibration phase to estimate decoding parameters. During iBCI operation, the statistical properties of the neural activity can depart from those observed during calibration, sometimes hindering a user’s ability to control the iBCI. To address this problem, we adaptively correct the offset terms within a Kalman filter decoder via penalized maximum likelihood estimation. The approach can handle rapid shifts in neural signal behavior (on the order of seconds) and requires no knowledge of the intended movement. The algorithm, called MOCA, was tested using simulated neural activity and evaluated retrospectively using data collected from two people with tetraplegia operating an iBCI. In 19 clinical research test cases, where a nonadaptive Kalman filter yielded relatively high decoding errors, MOCA significantly reduced these errors (10.6 ±10.1%; p<0.05, pairwise t-test). MOCA did not significantly change the error in the remaining 23 cases where a nonadaptive Kalman filter already performed well. These results suggest that MOCA provides more robust decoding than the standard Kalman filter for iBCIs. PMID:24196868

Adaptive offset correction for intracortical brain-computer interfaces.

PubMed

Homer, Mark L; Perge, Janos A; Black, Michael J; Harrison, Matthew T; Cash, Sydney S; Hochberg, Leigh R

2014-03-01

Intracortical brain-computer interfaces (iBCIs) decode intended movement from neural activity for the control of external devices such as a robotic arm. Standard approaches include a calibration phase to estimate decoding parameters. During iBCI operation, the statistical properties of the neural activity can depart from those observed during calibration, sometimes hindering a user's ability to control the iBCI. To address this problem, we adaptively correct the offset terms within a Kalman filter decoder via penalized maximum likelihood estimation. The approach can handle rapid shifts in neural signal behavior (on the order of seconds) and requires no knowledge of the intended movement. The algorithm, called multiple offset correction algorithm (MOCA), was tested using simulated neural activity and evaluated retrospectively using data collected from two people with tetraplegia operating an iBCI. In 19 clinical research test cases, where a nonadaptive Kalman filter yielded relatively high decoding errors, MOCA significantly reduced these errors ( 10.6 ± 10.1% ; p < 0.05, pairwise t-test). MOCA did not significantly change the error in the remaining 23 cases where a nonadaptive Kalman filter already performed well. These results suggest that MOCA provides more robust decoding than the standard Kalman filter for iBCIs.

Quantum computing: a prime modality in neurosurgery's future.

PubMed

Lee, Brian; Liu, Charles Y; Apuzzo, Michael L J

2012-11-01

With each significant development in the field of neurosurgery, our dependence on computers, small and large, has continuously increased. From something as mundane as bipolar cautery to sophisticated intraoperative navigation with real-time magnetic resonance imaging-assisted surgical guidance, both technologies, however simple or complex, require computational processing power to function. The next frontier for neurosurgery involves developing a greater understanding of the brain and furthering our capabilities as surgeons to directly affect brain circuitry and function. This has come in the form of implantable devices that can electronically and nondestructively influence the cortex and nuclei with the purpose of restoring neuronal function and improving quality of life. We are now transitioning from devices that are turned on and left alone, such as vagus nerve stimulators and deep brain stimulators, to "smart" devices that can listen and react to the body as the situation may dictate. The development of quantum computers and their potential to be thousands, if not millions, of times faster than current "classical" computers, will significantly affect the neurosciences, especially the field of neurorehabilitation and neuromodulation. Quantum computers may advance our understanding of the neural code and, in turn, better develop and program implantable neural devices. When quantum computers reach the point where we can actually implant such devices in patients, the possibilities of what can be done to interface and restore neural function will be limitless. Copyright © 2012 Elsevier Inc. All rights reserved.

Power feasibility of implantable digital spike sorting circuits for neural prosthetic systems.

PubMed

Zumsteg, Zachary S; Kemere, Caleb; O'Driscoll, Stephen; Santhanam, Gopal; Ahmed, Rizwan E; Shenoy, Krishna V; Meng, Teresa H

2005-09-01

A new class of neural prosthetic systems aims to assist disabled patients by translating cortical neural activity into control signals for prosthetic devices. Based on the success of proof-of-concept systems in the laboratory, there is now considerable interest in increasing system performance and creating implantable electronics for use in clinical systems. A critical question that impacts system performance and the overall architecture of these systems is whether it is possible to identify the neural source of each action potential (spike sorting) in real-time and with low power. Low power is essential both for power supply considerations and heat dissipation in the brain. In this paper we report that state-of-the-art spike sorting algorithms are not only feasible using modern complementary metal oxide semiconductor very large scale integration processes, but may represent the best option for extracting large amounts of data in implantable neural prosthetic interfaces.

A novel flexible cuff-like microelectrode for dual purpose, acute and chronic electrical interfacing with the mouse cervical vagus nerve

NASA Astrophysics Data System (ADS)

Caravaca, A. S.; Tsaava, T.; Goldman, L.; Silverman, H.; Riggott, G.; Chavan, S. S.; Bouton, C.; Tracey, K. J.; Desimone, R.; Boyden, E. S.; Sohal, H. S.; Olofsson, P. S.

2017-12-01

Objective. Neural reflexes regulate immune responses and homeostasis. Advances in bioelectronic medicine indicate that electrical stimulation of the vagus nerve can be used to treat inflammatory disease, yet the understanding of neural signals that regulate inflammation is incomplete. Current interfaces with the vagus nerve do not permit effective chronic stimulation or recording in mouse models, which is vital to studying the molecular and neurophysiological mechanisms that control inflammation homeostasis in health and disease. We developed an implantable, dual purpose, multi-channel, flexible ‘microelectrode’ array, for recording and stimulation of the mouse vagus nerve. Approach. The array was microfabricated on an 8 µm layer of highly biocompatible parylene configured with 16 sites. The microelectrode was evaluated by studying the recording and stimulation performance. Mice were chronically implanted with devices for up to 12 weeks. Main results. Using the microelectrode in vivo, high fidelity signals were recorded during physiological challenges (e.g potassium chloride and interleukin-1β), and electrical stimulation of the vagus nerve produced the expected significant reduction of blood levels of tumor necrosis factor (TNF) in endotoxemia. Inflammatory cell infiltration at the microelectrode 12 weeks of implantation was limited according to radial distribution analysis of inflammatory cells. Significance. This novel device provides an important step towards a viable chronic interface for cervical vagus nerve stimulation and recording in mice.

A wideband wireless neural stimulation platform for high-density microelectrode arrays.

PubMed

Myers, Frank B; Simpson, Jim A; Ghovanloo, Maysam

2006-01-01

We describe a system that allows researchers to control an implantable neural microstimulator from a PC via a USB 2.0 interface and a novel dual-carrier wireless link, which provides separate data and power transmission. Our wireless stimulator, Interestim-2B (IS-2B), is a modular device capable of generating controlled-current stimulation pulse trains across 32 sites per module with support for a variety of stimulation schemes (biphasic/monophasic, bipolar/monopolar). We have developed software to generate multi-site stimulation commands for the IS-2B based on streaming data from artificial sensory devices such as cameras and microphones. For PC interfacing, we have developed a USB 2.0 microcontroller-based interface. Data is transmitted using frequency-shift keying (FSK) at 6/12 MHz to achieve a data rate of 3 Mb/s via a pair of rectangular coils. Power is generated using a class-E power amplifier operating at 1 MHz and transmitted via a separate pair of spiral planar coils which are oriented perpendicular to the data coils to minimize cross-coupling. We have successfully demonstrated the operation of the system by applying it as a visual prosthesis. Pulse-frequency modulated stimuli are generated in real-time based on a grayscale image from a webcam. These pulses are projected onto an 11x11 LED matrix that represents a 2D microelectrode array.

Listening to Brain Microcircuits for Interfacing With External World—Progress in Wireless Implantable Microelectronic Neuroengineering Devices

PubMed Central

Nurmikko, Arto V.; Donoghue, John P.; Hochberg, Leigh R.; Patterson, William R.; Song, Yoon-Kyu; Bull, Christopher W.; Borton, David A.; Laiwalla, Farah; Park, Sunmee; Ming, Yin; Aceros, Juan

2011-01-01

Acquiring neural signals at high spatial and temporal resolution directly from brain microcircuits and decoding their activity to interpret commands and/or prior planning activity, such as motion of an arm or a leg, is a prime goal of modern neurotechnology. Its practical aims include assistive devices for subjects whose normal neural information pathways are not functioning due to physical damage or disease. On the fundamental side, researchers are striving to decipher the code of multiple neural microcircuits which collectively make up nature’s amazing computing machine, the brain. By implanting biocompatible neural sensor probes directly into the brain, in the form of microelectrode arrays, it is now possible to extract information from interacting populations of neural cells with spatial and temporal resolution at the single cell level. With parallel advances in application of statistical and mathematical techniques tools for deciphering the neural code, extracted populations or correlated neurons, significant understanding has been achieved of those brain commands that control, e.g., the motion of an arm in a primate (monkey or a human subject). These developments are accelerating the work on neural prosthetics where brain derived signals may be employed to bypass, e.g., an injured spinal cord. One key element in achieving the goals for practical and versatile neural prostheses is the development of fully implantable wireless microelectronic “brain-interfaces” within the body, a point of special emphasis of this paper. PMID:21654935

Organic electrode coatings for next-generation neural interfaces

PubMed Central

Aregueta-Robles, Ulises A.; Woolley, Andrew J.; Poole-Warren, Laura A.; Lovell, Nigel H.; Green, Rylie A.

2014-01-01

Traditional neuronal interfaces utilize metallic electrodes which in recent years have reached a plateau in terms of the ability to provide safe stimulation at high resolution or rather with high densities of microelectrodes with improved spatial selectivity. To achieve higher resolution it has become clear that reducing the size of electrodes is required to enable higher electrode counts from the implant device. The limitations of interfacing electrodes including low charge injection limits, mechanical mismatch and foreign body response can be addressed through the use of organic electrode coatings which typically provide a softer, more roughened surface to enable both improved charge transfer and lower mechanical mismatch with neural tissue. Coating electrodes with conductive polymers or carbon nanotubes offers a substantial increase in charge transfer area compared to conventional platinum electrodes. These organic conductors provide safe electrical stimulation of tissue while avoiding undesirable chemical reactions and cell damage. However, the mechanical properties of conductive polymers are not ideal, as they are quite brittle. Hydrogel polymers present a versatile coating option for electrodes as they can be chemically modified to provide a soft and conductive scaffold. However, the in vivo chronic inflammatory response of these conductive hydrogels remains unknown. A more recent approach proposes tissue engineering the electrode interface through the use of encapsulated neurons within hydrogel coatings. This approach may provide a method for activating tissue at the cellular scale, however, several technological challenges must be addressed to demonstrate feasibility of this innovative idea. The review focuses on the various organic coatings which have been investigated to improve neural interface electrodes. PMID:24904405

Invasive Intraneural Interfaces: Foreign Body Reaction Issues

PubMed Central

Lotti, Fiorenza; Ranieri, Federico; Vadalà, Gianluca; Zollo, Loredana; Di Pino, Giovanni

2017-01-01

Intraneural interfaces are stimulation/registration devices designed to couple the peripheral nervous system (PNS) with the environment. Over the last years, their use has increased in a wide range of applications, such as the control of a new generation of neural-interfaced prostheses. At present, the success of this technology is limited by an electrical impedance increase, due to an inflammatory response called foreign body reaction (FBR), which leads to the formation of a fibrotic tissue around the interface, eventually causing an inefficient transduction of the electrical signal. Based on recent developments in biomaterials and inflammatory/fibrotic pathologies, we explore and select the biological solutions that might be adopted in the neural interfaces FBR context: modifications of the interface surface, such as organic and synthetic coatings; the use of specific drugs or molecular biology tools to target the microenvironment around the interface; the development of bio-engineered-scaffold to reduce immune response and promote interface-tissue integration. By linking what we believe are the major crucial steps of the FBR process with related solutions, we point out the main issues that future research has to focus on: biocompatibility without losing signal conduction properties, good reproducible in vitro/in vivo models, drugs exhaustion and undesired side effects. The underlined pros and cons of proposed solutions show clearly the importance of a better understanding of all the molecular and cellular pathways involved and the need of a multi-target action based on a bio-engineered combination approach. PMID:28932181

Visual Prosthesis: Interfacing Stimulating Electrodes with Retinal Neurons to Restore Vision

PubMed Central

Barriga-Rivera, Alejandro; Bareket, Lilach; Goding, Josef; Aregueta-Robles, Ulises A.; Suaning, Gregg J.

2017-01-01

The bypassing of degenerated photoreceptors using retinal neurostimulators is helping the blind to recover functional vision. Researchers are investigating new ways to improve visual percepts elicited by these means as the vision produced by these early devices remain rudimentary. However, several factors are hampering the progression of bionic technologies: the charge injection limits of metallic electrodes, the mechanical mismatch between excitable tissue and the stimulating elements, neural and electric crosstalk, the physical size of the implanted devices, and the inability to selectively activate different types of retinal neurons. Electrochemical and mechanical limitations are being addressed by the application of electromaterials such as conducting polymers, carbon nanotubes and nanocrystalline diamonds, among other biomaterials, to electrical neuromodulation. In addition, the use of synthetic hydrogels and cell-laden biomaterials is promising better interfaces, as it opens a door to establishing synaptic connections between the electrode material and the excitable cells. Finally, new electrostimulation approaches relying on the use of high-frequency stimulation and field overlapping techniques are being developed to better replicate the neural code of the retina. All these elements combined will bring bionic vision beyond its present state and into the realm of a viable, mainstream therapy for vision loss. PMID:29184478

Offline decoding of end-point forces using neural ensembles: application to a brain-machine interface.

PubMed

Gupta, Rahul; Ashe, James

2009-06-01

Brain-machine interfaces (BMIs) hold a lot of promise for restoring some level of motor function to patients with neuronal disease or injury. Current BMI approaches fall into two broad categories--those that decode discrete properties of limb movement (such as movement direction and movement intent) and those that decode continuous variables (such as position and velocity). However, to enable the prosthetic devices to be useful for common everyday tasks, precise control of the forces applied by the end-point of the prosthesis (e.g., the hand) is also essential. Here, we used linear regression and Kalman filter methods to show that neural activity recorded from the motor cortex of the monkey during movements in a force field can be used to decode the end-point forces applied by the subject successfully and with high fidelity. Furthermore, the models exhibit some generalization to novel task conditions. We also demonstrate how the simultaneous prediction of kinematics and kinetics can be easily achieved using the same framework, without any degradation in decoding quality. Our results represent a useful extension of the current BMI technology, making dynamic control of a prosthetic device a distinct possibility in the near future.

Connecting Neurons to a Mobile Robot: An In Vitro Bidirectional Neural Interface

PubMed Central

Novellino, A.; D'Angelo, P.; Cozzi, L.; Chiappalone, M.; Sanguineti, V.; Martinoia, S.

2007-01-01

One of the key properties of intelligent behaviors is the capability to learn and adapt to changing environmental conditions. These features are the result of the continuous and intense interaction of the brain with the external world, mediated by the body. For this reason “embodiment” represents an innovative and very suitable experimental paradigm when studying the neural processes underlying learning new behaviors and adapting to unpredicted situations. To this purpose, we developed a novel bidirectional neural interface. We interconnected in vitro neurons, extracted from rat embryos and plated on a microelectrode array (MEA), to external devices, thus allowing real-time closed-loop interaction. The novelty of this experimental approach entails the necessity to explore different computational schemes and experimental hypotheses. In this paper, we present an open, scalable architecture, which allows fast prototyping of different modules and where coding and decoding schemes and different experimental configurations can be tested. This hybrid system can be used for studying the computational properties and information coding in biological neuronal networks with far-reaching implications for the future development of advanced neuroprostheses. PMID:18350128

Neural prostheses in clinical applications--trends from precision mechanics towards biomedical microsystems in neurological rehabilitation.

PubMed

Stieglitz, T; Schuettler, M; Koch, K P

2004-04-01

Neural prostheses partially restore body functions by technical nerve excitation after trauma or neurological diseases. External devices and implants have been developed since the early 1960s for many applications. Several systems have reached nowadays clinical practice: Cochlea implants help the deaf to hear, micturition is induced by bladder stimulators in paralyzed persons and deep brain stimulation helps patients with Parkinson's disease to participate in daily life again. So far, clinical neural prostheses are fabricated with means of precision mechanics. Since microsystem technology opens the opportunity to design and develop complex systems with a high number of electrodes to interface with the nervous systems, the opportunity for selective stimulation and complex implant scenarios seems to be feasible in the near future. The potentials and limitations with regard to biomedical microdevices are introduced and discussed in this paper. Target specifications are derived from existing implants and are discussed on selected applications that has been investigated in experimental research: a micromachined implant to interface a nerve stump with a sieve electrode, cuff electrodes with integrated electronics, and an epiretinal vision prosthesis.

Titania nanotube arrays as potential interfaces for neurological prostheses

NASA Astrophysics Data System (ADS)

Sorkin, Jonathan Andrew

Neural prostheses can make a dramatic improvement for those suffering from visual and auditory, cognitive, and motor control disabilities, allowing them regained functionality by the use of stimulating or recording electrical signaling. However, the longevity of these devices is limited due to the neural tissue response to the implanted device. In response to the implant penetrating the blood brain barrier and causing trauma to the tissue, the body forms a to scar to isolate the implant in order to protect the nearby tissue. The scar tissue is a result of reactive gliosis and produces an insulated sheath, encapsulating the implant. The glial sheath limits the stimulating or recording capabilities of the implant, reducing its effectiveness over the long term. A favorable interaction with this tissue would be the direct adhesion of neurons onto the contacts of the implant, and the prevention of glial encapsulation. With direct neuronal adhesion the effectiveness and longevity of the device would be significantly improved. Titania nanotube arrays, fabricated using electrochemical anodization, provide a conductive architecture capable of altering cellular response. This work focuses on the fabrication of different titania nanotube array architectures to determine how their structures and properties influence the response of neural tissue, modeled using the C17.2 murine neural stem cell subclone, and if glial encapsulation can be reduced while neuronal adhesion is promoted.

Hybrid Spintronic-CMOS Spiking Neural Network with On-Chip Learning: Devices, Circuits, and Systems

NASA Astrophysics Data System (ADS)

Sengupta, Abhronil; Banerjee, Aparajita; Roy, Kaushik

2016-12-01

Over the past decade, spiking neural networks (SNNs) have emerged as one of the popular architectures to emulate the brain. In SNNs, information is temporally encoded and communication between neurons is accomplished by means of spikes. In such networks, spike-timing-dependent plasticity mechanisms require the online programing of synapses based on the temporal information of spikes transmitted by spiking neurons. In this work, we propose a spintronic synapse with decoupled spike-transmission and programing-current paths. The spintronic synapse consists of a ferromagnet-heavy-metal heterostructure where the programing current through the heavy metal generates spin-orbit torque to modulate the device conductance. Low programing energy and fast programing times demonstrate the efficacy of the proposed device as a nanoelectronic synapse. We perform a simulation study based on an experimentally benchmarked device-simulation framework to demonstrate the interfacing of such spintronic synapses with CMOS neurons and learning circuits operating in the transistor subthreshold region to form a network of spiking neurons that can be utilized for pattern-recognition problems.

ARACHNE: A neural-neuroglial network builder with remotely controlled parallel computing

PubMed Central

Rusakov, Dmitri A.; Savtchenko, Leonid P.

2017-01-01

Creating and running realistic models of neural networks has hitherto been a task for computing professionals rather than experimental neuroscientists. This is mainly because such networks usually engage substantial computational resources, the handling of which requires specific programing skills. Here we put forward a newly developed simulation environment ARACHNE: it enables an investigator to build and explore cellular networks of arbitrary biophysical and architectural complexity using the logic of NEURON and a simple interface on a local computer or a mobile device. The interface can control, through the internet, an optimized computational kernel installed on a remote computer cluster. ARACHNE can combine neuronal (wired) and astroglial (extracellular volume-transmission driven) network types and adopt realistic cell models from the NEURON library. The program and documentation (current version) are available at GitHub repository https://github.com/LeonidSavtchenko/Arachne under the MIT License (MIT). PMID:28362877

Nanoelectronics Meets Biology: From Novel Nanoscale Devices for Live Cell Recording to 3D Innervated Tissues†

PubMed Central

Duan, Xiaojie; Lieber, Charles M.

2013-01-01

High spatio-temporal resolution interfacing between electrical sensors and biological systems, from single live cells to tissues, is crucial for many areas, including fundamental biophysical studies as well as medical monitoring and intervention. This focused review summarizes recent progresses in the development and application of novel nanoscale devices for intracellular electrical recordings of action potentials, and the effort of merging electronic and biological systems seamlessly in three dimension using macroporous nanoelectronic scaffolds. The uniqueness of these nanoscale devices for minimally invasive, large scale, high spatial resolution, and three dimensional neural activity mapping will be highlighted. PMID:23946279

Three-dimensional macroporous nanoelectronic networks as minimally invasive brain probes

NASA Astrophysics Data System (ADS)

Xie, Chong; Liu, Jia; Fu, Tian-Ming; Dai, Xiaochuan; Zhou, Wei; Lieber, Charles M.

2015-12-01

Direct electrical recording and stimulation of neural activity using micro-fabricated silicon and metal micro-wire probes have contributed extensively to basic neuroscience and therapeutic applications; however, the dimensional and mechanical mismatch of these probes with the brain tissue limits their stability in chronic implants and decreases the neuron-device contact. Here, we demonstrate the realization of a three-dimensional macroporous nanoelectronic brain probe that combines ultra-flexibility and subcellular feature sizes to overcome these limitations. Built-in strains controlling the local geometry of the macroporous devices are designed to optimize the neuron/probe interface and to promote integration with the brain tissue while introducing minimal mechanical perturbation. The ultra-flexible probes were implanted frozen into rodent brains and used to record multiplexed local field potentials and single-unit action potentials from the somatosensory cortex. Significantly, histology analysis revealed filling-in of neural tissue through the macroporous network and attractive neuron-probe interactions, consistent with long-term biocompatibility of the device.

Interfacing to the brain’s motor decisions

PubMed Central

2017-01-01

It has been long known that neural activity, recorded with electrophysiological methods, contains rich information about a subject’s motor intentions, sensory experiences, allocation of attention, action planning, and even abstract thoughts. All these functions have been the subject of neurophysiological investigations, with the goal of understanding how neuronal activity represents behavioral parameters, sensory inputs, and cognitive functions. The field of brain-machine interfaces (BMIs) strives for a somewhat different goal: it endeavors to extract information from neural modulations to create a communication link between the brain and external devices. Although many remarkable successes have been already achieved in the BMI field, questions remain regarding the possibility of decoding high-order neural representations, such as decision making. Could BMIs be employed to decode the neural representations of decisions underlying goal-directed actions? In this review we lay out a framework that describes the computations underlying goal-directed actions as a multistep process performed by multiple cortical and subcortical areas. We then discuss how BMIs could connect to different decision-making steps and decode the neural processing ongoing before movements are initiated. Such decision-making BMIs could operate as a system with prediction that offers many advantages, such as shorter reaction time, better error processing, and improved unsupervised learning. To present the current state of the art, we review several recent BMIs incorporating decision-making components. PMID:28003406

A Wireless 32-Channel Implantable Bidirectional Brain Machine Interface

PubMed Central

Su, Yi; Routhu, Sudhamayee; Moon, Kee S.; Lee, Sung Q.; Youm, WooSub; Ozturk, Yusuf

2016-01-01

All neural information systems (NIS) rely on sensing neural activity to supply commands and control signals for computers, machines and a variety of prosthetic devices. Invasive systems achieve a high signal-to-noise ratio (SNR) by eliminating the volume conduction problems caused by tissue and bone. An implantable brain machine interface (BMI) using intracortical electrodes provides excellent detection of a broad range of frequency oscillatory activities through the placement of a sensor in direct contact with cortex. This paper introduces a compact-sized implantable wireless 32-channel bidirectional brain machine interface (BBMI) to be used with freely-moving primates. The system is designed to monitor brain sensorimotor rhythms and present current stimuli with a configurable duration, frequency and amplitude in real time to the brain based on the brain activity report. The battery is charged via a novel ultrasonic wireless power delivery module developed for efficient delivery of power into a deeply-implanted system. The system was successfully tested through bench tests and in vivo tests on a behaving primate to record the local field potential (LFP) oscillation and stimulate the target area at the same time. PMID:27669264

Electrochemical Deposition of Nanostructured Conducting Polymer Coatings on Neural Prosthetic Devices

NASA Astrophysics Data System (ADS)

Yang, Junyan; Martin, David

2003-03-01

Micromachined neural prosthetic devices facilitate the functional stimulation of and recording from the central nervous system (CNS). These devices have been fabricated to consist of silicon shanks that have gold or iridium sites along their surface. Our goal is to improve the biocompatibility and long-term performance of the neural prosthetic probes when they are implanted chronically in the brain. In our most recent efforts we have established that electrochemical polymerization can be used to deposit fuzzy coatings of conducting polymers specifically on the electrode sites. For neural prosthetic devices that are intended for long term implantation, we need to develop surfaces that provide intimate contact and promote efficient signal transport at the interface of the microelectrode array and brain tissue. We have developed methods to rapidly and reliably fabricate nanostructured conducting polymer coatings on the electrode probes using templated and surfactant-mediated techniques. Conducting polymer nanomushrooms and nanohairs of polypyrrole (PPy) were electrochemically polymerized onto the functional sites of neural probes by using either nanoporous block copolymers thin films, "track-etched" polycarbonate films or anodic aluminium oxide membranes as templates. Nanofibers of conducting polymers have also been successfully obtained by polymerizations in the presence of surfactants. The influence of current density, monomer concentration, surfactant concentration, and deposition charge on the thickness and morphology of the nanostructured conducting polymer coatings has been studied by optical, scanned probe, scanning electron and transmission electron microscopy. As compared with the normal nodular morphology of polypyrrole, the nanostructured morphologies grown from the neural electrode result in fuzzy coatings with extremely high surface area. The electrical properties of the polymer coatings were studied by Impedance Spectroscopy (IS) and Cyclic Voltammetry (CV). The significant drop in impedance in magnitude and phase angle is consistent with an increase of the surface area due to the roughened surface morphology.

Thinking Small: Progress on Microscale Neurostimulation Technology.

PubMed

Pancrazio, Joseph J; Deku, Felix; Ghazavi, Atefeh; Stiller, Allison M; Rihani, Rashed; Frewin, Christopher L; Varner, Victor D; Gardner, Timothy J; Cogan, Stuart F

2017-12-01

Neural stimulation is well-accepted as an effective therapy for a wide range of neurological disorders. While the scale of clinical devices is relatively large, translational, and pilot clinical applications are underway for microelectrode-based systems. Microelectrodes have the advantage of stimulating a relatively small tissue volume which may improve selectivity of therapeutic stimuli. Current microelectrode technology is associated with chronic tissue response which limits utility of these devices for neural recording and stimulation. One approach for addressing the tissue response problem may be to reduce physical dimensions of the device. "Thinking small" is a trend for the electronics industry, and for implantable neural interfaces, the result may be a device that can evade the foreign body response. This review paper surveys our current understanding pertaining to the relationship between implant size and tissue response and the state-of-the-art in ultrasmall microelectrodes. A comprehensive literature search was performed using PubMed, Web of Science (Clarivate Analytics), and Google Scholar. The literature review shows recent efforts to create microelectrodes that are extremely thin appear to reduce or even eliminate the chronic tissue response. With high charge capacity coatings, ultramicroelectrodes fabricated from emerging polymers, and amorphous silicon carbide appear promising for neurostimulation applications. We envision the emergence of robust and manufacturable ultramicroelectrodes that leverage advanced materials where the small cross-sectional geometry enables compliance within tissue. Nevertheless, future testing under in vivo conditions is particularly important for assessing the stability of thin film devices under chronic stimulation. © 2017 International Neuromodulation Society.

An introduction to neural networks surgery, a field of neuromodulation which is based on advances in neural networks science and digitised brain imaging.

PubMed

Sakas, D E; Panourias, I G; Simpson, B A

2007-01-01

Operative Neuromodulation is the field of altering electrically or chemically the signal transmission in the nervous system by implanted devices in order to excite, inhibit or tune the activities of neurons or neural networks and produce therapeutic effects. The present article reviews relevant literature on procedures or devices applied either in contact with the cerebral cortex or cranial nerves or in deep sites inside the brain in order to treat various refractory neurological conditions such as: a) chronic pain (facial, somatic, deafferentation, phantom limb), b) movement disorders (Parkinson's disease, dystonia, Tourette syndrome), c) epilepsy, d) psychiatric disease, e) hearing deficits, and f) visual loss. These data indicate that in operative neuromodulation, a new field emerges that is based on neural networks research and on advances in digitised stereometric brain imaging which allow precise localisation of cerebral neural networks and their relay stations; this field can be described as Neural networks surgery because it aims to act extrinsically or intrinsically on neural networks and to alter therapeutically the neural signal transmission with the use of implantable electrical or electronic devices. The authors also review neurotechnology literature relevant to neuroengineering, nanotechnologies, brain computer interfaces, hybrid cultured probes, neuromimetics, neuroinformatics, neurocomputation, and computational neuromodulation; the latter field is dedicated to the study of the biophysical and mathematical characteristics of electrochemical neuromodulation. The article also brings forward particularly interesting lines of research such as the carbon nanofibers electrode arrays for simultaneous electrochemical recording and stimulation, closed-loop systems for responsive neuromodulation, and the intracortical electrodes for restoring hearing or vision. The present review of cerebral neuromodulatory procedures highlights the transition from the conventional neurosurgery of resective or ablative techniques to a highly selective "surgery of networks". The dynamics of the convergence of the above biomedical and technological fields with biological restorative approaches have important implications for patients with severe neurological disorders.

Real-time encoding and compression of neuronal spikes by metal-oxide memristors

NASA Astrophysics Data System (ADS)

Gupta, Isha; Serb, Alexantrou; Khiat, Ali; Zeitler, Ralf; Vassanelli, Stefano; Prodromakis, Themistoklis

2016-09-01

Advanced brain-chip interfaces with numerous recording sites bear great potential for investigation of neuroprosthetic applications. The bottleneck towards achieving an efficient bio-electronic link is the real-time processing of neuronal signals, which imposes excessive requirements on bandwidth, energy and computation capacity. Here we present a unique concept where the intrinsic properties of memristive devices are exploited to compress information on neural spikes in real-time. We demonstrate that the inherent voltage thresholds of metal-oxide memristors can be used for discriminating recorded spiking events from background activity and without resorting to computationally heavy off-line processing. We prove that information on spike amplitude and frequency can be transduced and stored in single devices as non-volatile resistive state transitions. Finally, we show that a memristive device array allows for efficient data compression of signals recorded by a multi-electrode array, demonstrating the technology's potential for building scalable, yet energy-efficient on-node processors for brain-chip interfaces.

Real-time encoding and compression of neuronal spikes by metal-oxide memristors

PubMed Central

Gupta, Isha; Serb, Alexantrou; Khiat, Ali; Zeitler, Ralf; Vassanelli, Stefano; Prodromakis, Themistoklis

2016-01-01

Advanced brain-chip interfaces with numerous recording sites bear great potential for investigation of neuroprosthetic applications. The bottleneck towards achieving an efficient bio-electronic link is the real-time processing of neuronal signals, which imposes excessive requirements on bandwidth, energy and computation capacity. Here we present a unique concept where the intrinsic properties of memristive devices are exploited to compress information on neural spikes in real-time. We demonstrate that the inherent voltage thresholds of metal-oxide memristors can be used for discriminating recorded spiking events from background activity and without resorting to computationally heavy off-line processing. We prove that information on spike amplitude and frequency can be transduced and stored in single devices as non-volatile resistive state transitions. Finally, we show that a memristive device array allows for efficient data compression of signals recorded by a multi-electrode array, demonstrating the technology's potential for building scalable, yet energy-efficient on-node processors for brain-chip interfaces. PMID:27666698

Two-Dimensional Optoelectronic Graphene Nanoprobes for Neural Nerwork

NASA Astrophysics Data System (ADS)

Hong, Tu; Kitko, Kristina; Wang, Rui; Zhang, Qi; Xu, Yaqiong

2014-03-01

Brain is the most complex network created by nature, with billions of neurons connected by trillions of synapses through sophisticated wiring patterns and countless modulatory mechanisms. Current methods to study the neuronal process, either by electrophysiology or optical imaging, have significant limitations on throughput and sensitivity. Here, we use graphene, a monolayer of carbon atoms, as a two-dimensional nanoprobe for neural network. Scanning photocurrent measurement is applied to detect the local integration of electrical and chemical signals in mammalian neurons. Such interface between nanoscale electronic device and biological system provides not only ultra-high sensitivity, but also sub-millisecond temporal resolution, owing to the high carrier mobility of graphene.

Bioresorbable silicon electronics for transient spatiotemporal mapping of electrical activity from the cerebral cortex.

PubMed

Yu, Ki Jun; Kuzum, Duygu; Hwang, Suk-Won; Kim, Bong Hoon; Juul, Halvor; Kim, Nam Heon; Won, Sang Min; Chiang, Ken; Trumpis, Michael; Richardson, Andrew G; Cheng, Huanyu; Fang, Hui; Thomson, Marissa; Bink, Hank; Talos, Delia; Seo, Kyung Jin; Lee, Hee Nam; Kang, Seung-Kyun; Kim, Jae-Hwan; Lee, Jung Yup; Huang, Younggang; Jensen, Frances E; Dichter, Marc A; Lucas, Timothy H; Viventi, Jonathan; Litt, Brian; Rogers, John A

2016-07-01

Bioresorbable silicon electronics technology offers unprecedented opportunities to deploy advanced implantable monitoring systems that eliminate risks, cost and discomfort associated with surgical extraction. Applications include postoperative monitoring and transient physiologic recording after percutaneous or minimally invasive placement of vascular, cardiac, orthopaedic, neural or other devices. We present an embodiment of these materials in both passive and actively addressed arrays of bioresorbable silicon electrodes with multiplexing capabilities, which record in vivo electrophysiological signals from the cortical surface and the subgaleal space. The devices detect normal physiologic and epileptiform activity, both in acute and chronic recordings. Comparative studies show sensor performance comparable to standard clinical systems and reduced tissue reactivity relative to conventional clinical electrocorticography (ECoG) electrodes. This technology offers general applicability in neural interfaces, with additional potential utility in treatment of disorders where transient monitoring and modulation of physiologic function, implant integrity and tissue recovery or regeneration are required.

Evolvable synthetic neural system

NASA Technical Reports Server (NTRS)

Curtis, Steven A. (Inventor)

2009-01-01

An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

Wireless opto-electro neural interface for experiments with small freely behaving animals.

PubMed

Jia, Yaoyao; Khan, Wasif; Lee, Byunghun; Fan, Bin; Madi, Fatma; Weber, Arthur; Li, Wen; Ghovanloo, Maysam

2018-05-25

We have developed a wireless opto-electro interface (WOENI) device, which combines electrocorticogram (ECoG) recording and optical stimulation for bi-directional neuromodulation on small, freely behaving animals, such as rodents. The device is comprised of two components, a detachable headstage and an implantable polyimide-based substrate. The headstage establishes a Bluetooth Low Energy (BLE) bi-directional data communication with an external custom-designed USB dongle for receiving user commands and optogenetic stimulation patterns, and sending digitalized ECoG data. The functionality and stability of the device were evaluated in vivo on freely behaving rats. When the animal received optical stimulation on the primary visual cortex (V1) and visual stimulation via eyes, spontaneous changes in ECoG signals were recorded from both left and right V1 during 4 consecutive experiments with 7-day intervals over a time span of 21 days following device implantation. Immunostained tissue analyses showed results consistent with ECoG analyses, validating the efficacy of optical stimulation to upregulate the activity of cortical neurons expressing ChR2. The proposed WOENI device is potentially a versatile tool in the studies that involve long-term optogenetic neuromodulation. © 2018 IOP Publishing Ltd.

Nanoelectronics meets biology: from new nanoscale devices for live-cell recording to 3D innervated tissues.

PubMed

Duan, Xiaojie; Lieber, Charles M

2013-10-01

High spatiotemporal resolution interfaces between electrical sensors and biological systems, from single live cells to tissues, is crucial for many areas, including fundamental biophysical studies as well as medical monitoring and intervention. Herein, we summarize recent progress in the development and application of novel nanoscale devices for intracellular electrical recording of action potentials and the effort of merging electronic and biological systems seamlessly in three dimensions by using macroporous nanoelectronic scaffolds. The uniqueness of these nanoscale devices for minimally invasive, large-scale, high spatial resolution, and three-dimensional neural activity mapping are highlighted. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Neurotechnology for monitoring and restoring sensory, motor, and autonomic functions

NASA Astrophysics Data System (ADS)

Wu, Pae C.; Knaack, Gretchen; Weber, Douglas J.

2016-05-01

The rapid and exponential advances in micro- and nanotechnologies over the last decade have enabled devices that communicate directly with the nervous system to measure and influence neural activity. Many of the earliest implementations focused on restoration of sensory and motor function, but as knowledge of physiology advances and technology continues to improve in accuracy, precision, and safety, new modes of engaging with the autonomic system herald an era of health restoration that may augment or replace many conventional pharmacotherapies. DARPA's Biological Technologies Office is continuing to advance neurotechnology by investing in neural interface technologies that are effective, reliable, and safe for long-term use in humans. DARPA's Hand Proprioception and Touch Interfaces (HAPTIX) program is creating a fully implantable system that interfaces with peripheral nerves in amputees to enable natural control and sensation for prosthetic limbs. Beyond standard electrode implementations, the Electrical Prescriptions (ElectRx) program is investing in innovative approaches to minimally or non-invasively interface with the peripheral nervous system using novel magnetic, optogenetic, and ultrasound-based technologies. These new mechanisms of interrogating and stimulating the peripheral nervous system are driving towards unparalleled spatiotemporal resolution, specificity and targeting, and noninvasiveness to enable chronic, human-use applications in closed-loop neuromodulation for the treatment of disease.

A regenerative microchannel neural interface for recording from and stimulating peripheral axons in vivo

NASA Astrophysics Data System (ADS)

FitzGerald, James J.; Lago, Natalia; Benmerah, Samia; Serra, Jordi; Watling, Christopher P.; Cameron, Ruth E.; Tarte, Edward; Lacour, Stéphanie P.; McMahon, Stephen B.; Fawcett, James W.

2012-02-01

Neural interfaces are implanted devices that couple the nervous system to electronic circuitry. They are intended for long term use to control assistive technologies such as muscle stimulators or prosthetics that compensate for loss of function due to injury. Here we present a novel design of interface for peripheral nerves. Recording from axons is complicated by the small size of extracellular potentials and the concentration of current flow at nodes of Ranvier. Confining axons to microchannels of ˜100 µm diameter produces amplified potentials that are independent of node position. After implantation of microchannel arrays into rat sciatic nerve, axons regenerated through the channels forming ‘mini-fascicles’, each typically containing ˜100 myelinated fibres and one or more blood vessels. Regenerated motor axons reconnected to distal muscles, as demonstrated by the recovery of an electromyogram and partial prevention of muscle atrophy. Efferent motor potentials and afferent signals evoked by muscle stretch or cutaneous stimulation were easily recorded from the mini-fascicles and were in the range of 35-170 µV. Individual motor units in distal musculature were activated from channels using stimulus currents in the microampere range. Microchannel interfaces are a potential solution for applications such as prosthetic limb control or enhancing recovery after nerve injury.

Capacitor electrode stimulates nerve or muscle without oxidation-reduction reactions.

PubMed

Guyton, D L; Hambrecht, F T

1973-07-06

Porous tantalum disks, available as "slugs" from the capacitor industry, have large available surface area and a thin insulating coating of tantalum pentoxide. When implanted, they fill with extracellular fluid and operate as capacitor-stimulating electrodes having high capacitance per unit volume. Capable of stimulating excitable tissute without generating electrochemical by-products, these electrodes should provide a safer interface between neural prosthetic devices and human tissue.

The science of neural interface systems.

PubMed

Hatsopoulos, Nicholas G; Donoghue, John P

2009-01-01

The ultimate goal of neural interface research is to create links between the nervous system and the outside world either by stimulating or by recording from neural tissue to treat or assist people with sensory, motor, or other disabilities of neural function. Although electrical stimulation systems have already reached widespread clinical application, neural interfaces that record neural signals to decipher movement intentions are only now beginning to develop into clinically viable systems to help paralyzed people. We begin by reviewing state-of-the-art research and early-stage clinical recording systems and focus on systems that record single-unit action potentials. We then address the potential for neural interface research to enhance basic scientific understanding of brain function by offering unique insights in neural coding and representation, plasticity, brain-behavior relations, and the neurobiology of disease. Finally, we discuss technical and scientific challenges faced by these systems before they are widely adopted by severely motor-disabled patients.

Manufacturing, assembling and packaging of miniaturized implants for neural prostheses and brain-machine interfaces

NASA Astrophysics Data System (ADS)

Stieglitz, Thomas

2009-05-01

Implantable medical devices to interface with muscles, peripheral nerves, and the brain have been developed for many applications over the last decades. They have been applied in fundamental neuroscientific studies as well as in diagnosis, therapy and rehabilitation in clinical practice. Success stories of these implants have been written with help of precision mechanics manufacturing techniques. Latest cutting edge research approaches to restore vision in blind persons and to develop an interface with the human brain as motor control interface, however, need more complex systems and larger scales of integration and higher degrees of miniaturization. Microsystems engineering offers adequate tools, methods, and materials but so far, no MEMS based active medical device has been transferred into clinical practice. Silicone rubber, polyimide, parylene as flexible materials and silicon and alumina (aluminum dioxide ceramics) as substrates and insulation or packaging materials, respectively, and precious metals as electrodes have to be combined to systems that do not harm the biological target structure and have to work reliably in a wet environment with ions and proteins. Here, different design, manufacturing and packaging paradigms will be presented and strengths and drawbacks will be discussed in close relation to the envisioned biological and medical applications.

NeuroMEMS: Neural Probe Microtechnologies

PubMed Central

HajjHassan, Mohamad; Chodavarapu, Vamsy; Musallam, Sam

2008-01-01

Neural probe technologies have already had a significant positive effect on our understanding of the brain by revealing the functioning of networks of biological neurons. Probes are implanted in different areas of the brain to record and/or stimulate specific sites in the brain. Neural probes are currently used in many clinical settings for diagnosis of brain diseases such as seizers, epilepsy, migraine, Alzheimer's, and dementia. We find these devices assisting paralyzed patients by allowing them to operate computers or robots using their neural activity. In recent years, probe technologies were assisted by rapid advancements in microfabrication and microelectronic technologies and thus are enabling highly functional and robust neural probes which are opening new and exciting avenues in neural sciences and brain machine interfaces. With a wide variety of probes that have been designed, fabricated, and tested to date, this review aims to provide an overview of the advances and recent progress in the microfabrication techniques of neural probes. In addition, we aim to highlight the challenges faced in developing and implementing ultra-long multi-site recording probes that are needed to monitor neural activity from deeper regions in the brain. Finally, we review techniques that can improve the biocompatibility of the neural probes to minimize the immune response and encourage neural growth around the electrodes for long term implantation studies. PMID:27873894

Wireless communication links for brain-machine interface applications

NASA Astrophysics Data System (ADS)

Larson, L.

2016-05-01

Recent technological developments have given neuroscientists direct access to neural signals in real time, with the accompanying ability to decode the resulting information and control various prosthetic devices and gain insight into deeper aspects of cognition. These developments - along with deep brain stimulation for Parkinson's disease and the possible use of electro-stimulation for other maladies - leads to the conclusion that the widespread use electronic brain interface technology is a long term possibility. This talk will summarize the various technical challenges and approaches that have been developed to wirelessly communicate with the brain, including technology constraints, dc power limits, compression and data rate issues.

Advantages of soft subdural implants for the delivery of electrochemical neuromodulation therapies to the spinal cord

NASA Astrophysics Data System (ADS)

Capogrosso, Marco; Gandar, Jerome; Greiner, Nathan; Moraud, Eduardo Martin; Wenger, Nikolaus; Shkorbatova, Polina; Musienko, Pavel; Minev, Ivan; Lacour, Stephanie; Courtine, Grégoire

2018-04-01

Objective. We recently developed soft neural interfaces enabling the delivery of electrical and chemical stimulation to the spinal cord. These stimulations restored locomotion in animal models of paralysis. Soft interfaces can be placed either below or above the dura mater. Theoretically, the subdural location combines many advantages, including increased selectivity of electrical stimulation, lower stimulation thresholds, and targeted chemical stimulation through local drug delivery. However, these advantages have not been documented, nor have their functional impact been studied in silico or in a relevant animal model of neurological disorders using a multimodal neural interface. Approach. We characterized the recruitment properties of subdural interfaces using a realistic computational model of the rat spinal cord that included explicit representation of the spinal roots. We then validated and complemented computer simulations with electrophysiological experiments in rats. We additionally performed behavioral experiments in rats that received a lateral spinal cord hemisection and were implanted with a soft interface. Main results. In silico and in vivo experiments showed that the subdural location decreased stimulation thresholds compared to the epidural location while retaining high specificity. This feature reduces power consumption and risks of long-term damage in the tissues, thus increasing the clinical safety profile of this approach. The hemisection induced a transient paralysis of the leg ipsilateral to the injury. During this period, the delivery of electrical stimulation restricted to the injured side combined with local chemical modulation enabled coordinated locomotor movements of the paralyzed leg without affecting the non-impaired leg in all tested rats. Electrode properties remained stable over time, while anatomical examinations revealed excellent bio-integration properties. Significance. Soft neural interfaces inserted subdurally provide the opportunity to deliver electrical and chemical neuromodulation therapies using a single, bio-compatible and mechanically compliant device that effectively alleviates locomotor deficits after spinal cord injury.

A Review of Organic and Inorganic Biomaterials for Neural Interfaces

PubMed Central

Fattahi, Pouria; Yang, Guang; Kim, Gloria

2015-01-01

Recent advances in nanotechnology have generated wide interest in applying nanomaterials for neural prostheses. An ideal neural interface should create seamless integration into the nervous system and performs reliably for long periods of time. As a result, many nanoscale materials not originally developed for neural interfaces become attractive candidates to detect neural signals and stimulate neurons. In this comprehensive review, an overview of state-of-the-art microelectrode technologies provided first, with focus on the material properties of these microdevices. The advancements in electro active nanomaterials are then reviewed, including conducting polymers, carbon nanotubes, graphene, silicon nanowires, and hybrid organic-inorganic nanomaterials, for neural recording, stimulation, and growth. Finally, technical and scientific challenges are discussed regarding biocompatibility, mechanical mismatch, and electrical properties faced by these nanomaterials for the development of long-lasting functional neural interfaces. PMID:24677434

A review of organic and inorganic biomaterials for neural interfaces.

PubMed

Fattahi, Pouria; Yang, Guang; Kim, Gloria; Abidian, Mohammad Reza

2014-03-26

Recent advances in nanotechnology have generated wide interest in applying nanomaterials for neural prostheses. An ideal neural interface should create seamless integration into the nervous system and performs reliably for long periods of time. As a result, many nanoscale materials not originally developed for neural interfaces become attractive candidates to detect neural signals and stimulate neurons. In this comprehensive review, an overview of state-of-the-art microelectrode technologies provided fi rst, with focus on the material properties of these microdevices. The advancements in electro active nanomaterials are then reviewed, including conducting polymers, carbon nanotubes, graphene, silicon nanowires, and hybrid organic-inorganic nanomaterials, for neural recording, stimulation, and growth. Finally, technical and scientific challenges are discussed regarding biocompatibility, mechanical mismatch, and electrical properties faced by these nanomaterials for the development of long-lasting functional neural interfaces.

Establishing a Novel Modeling Tool: A Python-Based Interface for a Neuromorphic Hardware System

PubMed Central

Brüderle, Daniel; Müller, Eric; Davison, Andrew; Muller, Eilif; Schemmel, Johannes; Meier, Karlheinz

2008-01-01

Neuromorphic hardware systems provide new possibilities for the neuroscience modeling community. Due to the intrinsic parallelism of the micro-electronic emulation of neural computation, such models are highly scalable without a loss of speed. However, the communities of software simulator users and neuromorphic engineering in neuroscience are rather disjoint. We present a software concept that provides the possibility to establish such hardware devices as valuable modeling tools. It is based on the integration of the hardware interface into a simulator-independent language which allows for unified experiment descriptions that can be run on various simulation platforms without modification, implying experiment portability and a huge simplification of the quantitative comparison of hardware and simulator results. We introduce an accelerated neuromorphic hardware device and describe the implementation of the proposed concept for this system. An example setup and results acquired by utilizing both the hardware system and a software simulator are demonstrated. PMID:19562085

Establishing a novel modeling tool: a python-based interface for a neuromorphic hardware system.

PubMed

Brüderle, Daniel; Müller, Eric; Davison, Andrew; Muller, Eilif; Schemmel, Johannes; Meier, Karlheinz

2009-01-01

Neuromorphic hardware systems provide new possibilities for the neuroscience modeling community. Due to the intrinsic parallelism of the micro-electronic emulation of neural computation, such models are highly scalable without a loss of speed. However, the communities of software simulator users and neuromorphic engineering in neuroscience are rather disjoint. We present a software concept that provides the possibility to establish such hardware devices as valuable modeling tools. It is based on the integration of the hardware interface into a simulator-independent language which allows for unified experiment descriptions that can be run on various simulation platforms without modification, implying experiment portability and a huge simplification of the quantitative comparison of hardware and simulator results. We introduce an accelerated neuromorphic hardware device and describe the implementation of the proposed concept for this system. An example setup and results acquired by utilizing both the hardware system and a software simulator are demonstrated.

A hybrid microfluidic-vacuum device for direct interfacing with conventional cell culture methods

PubMed Central

Chung, Bong Geun; Park, Jeong Won; Hu, Jia Sheng; Huang, Carlos; Monuki, Edwin S; Jeon, Noo Li

2007-01-01

Background Microfluidics is an enabling technology with a number of advantages over traditional tissue culture methods when precise control of cellular microenvironment is required. However, there are a number of practical and technical limitations that impede wider implementation in routine biomedical research. Specialized equipment and protocols required for fabrication and setting up microfluidic experiments present hurdles for routine use by most biology laboratories. Results We have developed and validated a novel microfluidic device that can directly interface with conventional tissue culture methods to generate and maintain controlled soluble environments in a Petri dish. It incorporates separate sets of fluidic channels and vacuum networks on a single device that allows reversible application of microfluidic gradients onto wet cell culture surfaces. Stable, precise concentration gradients of soluble factors were generated using simple microfluidic channels that were attached to a perfusion system. We successfully demonstrated real-time optical live/dead cell imaging of neural stem cells exposed to a hydrogen peroxide gradient and chemotaxis of metastatic breast cancer cells in a growth factor gradient. Conclusion This paper describes the design and application of a versatile microfluidic device that can directly interface with conventional cell culture methods. This platform provides a simple yet versatile tool for incorporating the advantages of a microfluidic approach to biological assays without changing established tissue culture protocols. PMID:17883868

Thinking Small – Progress on Microscale Neurostimulation Technology

PubMed Central

Pancrazio, Joseph J.; Deku, Felix; Ghazavi, Atefeh; Stiller, Allison M.; Rihani, Rashed; Frewin, Christopher L.; Varner, Victor D.; Gardner, Timothy J.; Cogan, Stuart F.

2017-01-01

Objectives Neural stimulation is well-accepted as an effective therapy for a wide range of neurological disorders. While the scale of clinical devices is relatively large, translational and pilot clinical applications are underway for microelectrode-based systems. Microelectrodes have the advantage of stimulating a relatively small tissue volume which may improve selectivity of therapeutic stimuli. Current microelectrode technology is associated with chronic tissue response which limits utility of these devices for neural recording and stimulation. One approach for addressing the tissue response problem may be to reduce physical dimensions of the device. “Thinking small” is a trend for the electronics industry, and for implantable neural interfaces, the result may be a device that can evade the foreign body response. Materials and Methods This review paper surveys our current understanding pertaining to the relationship between implant size and tissue response and the state-of-the-art in ultra-small microelectrodes. A comprehensive literature search was performed using PubMed, Web of Science (Clarivate Analytics), and Google Scholar. Results The literature review shows recent efforts to create microelectrodes that are extremely thin appear to reduce or even eliminate the chronic tissue response. With high charge capacity coatings, ultra-microelectrodes fabricated from emerging polymers and amorphous silicon carbide appear promising for neurostimulation applications. Conclusion We envision the emergence of robust and manufacturable ultra-microelectrodes that leverage advanced materials where the small cross-sectional geometry enables compliance within tissue. Nevertheless, future testing under in vivo conditions is particularly important for assessing the stability of thin film devices under chronic stimulation. PMID:29076214

Nanowire FET Based Neural Element for Robotic Tactile Sensing Skin

PubMed Central

Taube Navaraj, William; García Núñez, Carlos; Shakthivel, Dhayalan; Vinciguerra, Vincenzo; Labeau, Fabrice; Gregory, Duncan H.; Dahiya, Ravinder

2017-01-01

This paper presents novel Neural Nanowire Field Effect Transistors (υ-NWFETs) based hardware-implementable neural network (HNN) approach for tactile data processing in electronic skin (e-skin). The viability of Si nanowires (NWs) as the active material for υ-NWFETs in HNN is explored through modeling and demonstrated by fabricating the first device. Using υ-NWFETs to realize HNNs is an interesting approach as by printing NWs on large area flexible substrates it will be possible to develop a bendable tactile skin with distributed neural elements (for local data processing, as in biological skin) in the backplane. The modeling and simulation of υ-NWFET based devices show that the overlapping areas between individual gates and the floating gate determines the initial synaptic weights of the neural network - thus validating the working of υ-NWFETs as the building block for HNN. The simulation has been further extended to υ-NWFET based circuits and neuronal computation system and this has been validated by interfacing it with a transparent tactile skin prototype (comprising of 6 × 6 ITO based capacitive tactile sensors array) integrated on the palm of a 3D printed robotic hand. In this regard, a tactile data coding system is presented to detect touch gesture and the direction of touch. Following these simulation studies, a four-gated υ-NWFET is fabricated with Pt/Ti metal stack for gates, source and drain, Ni floating gate, and Al2O3 high-k dielectric layer. The current-voltage characteristics of fabricated υ-NWFET devices confirm the dependence of turn-off voltages on the (synaptic) weight of each gate. The presented υ-NWFET approach is promising for a neuro-robotic tactile sensory system with distributed computing as well as numerous futuristic applications such as prosthetics, and electroceuticals. PMID:28979183

Planar Diamond-Based Multiarrays to Monitor Neurotransmitter Release and Action Potential Firing: New Perspectives in Cellular Neuroscience.

PubMed

Carabelli, Valentina; Marcantoni, Andrea; Picollo, Federico; Battiato, Alfio; Bernardi, Ettore; Pasquarelli, Alberto; Olivero, Paolo; Carbone, Emilio

2017-02-15

High biocompatibility, outstanding electrochemical responsiveness, inertness, and transparency make diamond-based multiarrays (DBMs) first-rate biosensors for in vitro detection of electrochemical and electrical signals from excitable cells together, with potential for in vivo applications as neural interfaces and prostheses. Here, we will review the electrochemical and physical properties of various DBMs and how these devices have been employed for recording released neurotransmitter molecules and all-or-none action potentials from living cells. Specifically, we will overview how DBMs can resolve localized exocytotic events from subcellular compartments using high-density microelectrode arrays (MEAs), or monitoring oxidizable neurotransmitter release from populations of cells in culture and tissue slices using low-density MEAs. Interfacing DBMs with excitable cells is currently leading to the promising opportunity of recording electrical signals as well as creating neuronal interfaces through the same device. Given the recent increasingly growing development of newly available DBMs of various geometries to monitor electrical activity and neurotransmitter release in a variety of excitable and neuronal tissues, the discussion will be limited to planar DBMs.

Physiological properties of brain-machine interface input signals.

PubMed

Slutzky, Marc W; Flint, Robert D

2017-08-01

Brain-machine interfaces (BMIs), also called brain-computer interfaces (BCIs), decode neural signals and use them to control some type of external device. Despite many experimental successes and terrific demonstrations in animals and humans, a high-performance, clinically viable device has not yet been developed for widespread usage. There are many factors that impact clinical viability and BMI performance. Arguably, the first of these is the selection of brain signals used to control BMIs. In this review, we summarize the physiological characteristics and performance-including movement-related information, longevity, and stability-of multiple types of input signals that have been used in invasive BMIs to date. These include intracortical spikes as well as field potentials obtained inside the cortex, at the surface of the cortex (electrocorticography), and at the surface of the dura mater (epidural signals). We also discuss the potential for future enhancements in input signal performance, both by improving hardware and by leveraging the knowledge of the physiological characteristics of these signals to improve decoding and stability. Copyright © 2017 the American Physiological Society.

Syringe-Injectable Electronics with a Plug-and-Play Input/Output Interface.

PubMed

Schuhmann, Thomas G; Yao, Jun; Hong, Guosong; Fu, Tian-Ming; Lieber, Charles M

2017-09-13

Syringe-injectable mesh electronics represent a new paradigm for brain science and neural prosthetics by virtue of the stable seamless integration of the electronics with neural tissues, a consequence of the macroporous mesh electronics structure with all size features similar to or less than individual neurons and tissue-like flexibility. These same properties, however, make input/output (I/O) connection to measurement electronics challenging, and work to-date has required methods that could be difficult to implement by the life sciences community. Here we present a new syringe-injectable mesh electronics design with plug-and-play I/O interfacing that is rapid, scalable, and user-friendly to nonexperts. The basic design tapers the ultraflexible mesh electronics to a narrow stem that routes all of the device/electrode interconnects to I/O pads that are inserted into a standard zero insertion force (ZIF) connector. Studies show that the entire plug-and-play mesh electronics can be delivered through capillary needles with precise targeting using microliter-scale injection volumes similar to the standard mesh electronics design. Electrical characterization of mesh electronics containing platinum (Pt) electrodes and silicon (Si) nanowire field-effect transistors (NW-FETs) demonstrates the ability to interface arbitrary devices with a contact resistance of only 3 Ω. Finally, in vivo injection into mice required only minutes for I/O connection and yielded expected local field potential (LFP) recordings from a compact head-stage compatible with chronic studies. Our results substantially lower barriers for use by new investigators and open the door for increasingly sophisticated and multifunctional mesh electronics designs for both basic and translational studies.

Stab injury and device implantation within the brain results in inversely multiphasic neuroinflammatory and neurodegenerative responses

NASA Astrophysics Data System (ADS)

Potter, Kelsey A.; Buck, Amy C.; Self, Wade K.; Capadona, Jeffrey R.

2012-08-01

An estimated 25 million people in the US alone rely on implanted medical devices, ˜2.5 million implanted within the nervous system. Even though many devices perform adequately for years, the host response to medical devices often severely limits tissue integration and long-term performance. This host response is believed to be particularly limiting in the case of intracortical microelectrodes, where it has been shown that glial cell encapsulation and localized neuronal cell loss accompany intracortical microelectrode implantation. Since neuronal ensembles must be within ˜50 µm of the electrode to obtain neuronal spikes and local field potentials, developing a better understanding of the molecular and cellular environment at the device-tissue interface has been the subject of significant research. Unfortunately, immunohistochemical studies of scar maturation in correlation to device function have been inconclusive. Therefore, here we present a detailed quantitative study of the cellular events and the stability of the blood-brain barrier (BBB) following intracortical microelectrode implantation and cortical stab injury in a chronic survival model. We found two distinctly inverse multiphasic profiles for neuronal survival in device-implanted tissue compared to stab-injured animals. For chronically implanted animals, we observed a biphasic paradigm between blood-derived/trauma-induced and CNS-derived inflammatory markers driving neurodegeneration at the interface. In contrast, stab injured animals demonstrated a CNS-mediated neurodegenerative environment. Collectively these data provide valuable insight to the possibility of multiple roles of chronic neuroinflammatory events on BBB disruption and localized neurodegeneration, while also suggesting the importance to consider multiphasic neuroinflammatory kinetics in the design of therapeutic strategies for stabilizing neural interfaces.

A New Animal Model for Developing a Somatosensory Neural Interface for Prosthetic Limbs

DTIC Science & Technology

2008-02-12

interface for neuroprosthetic limbs . PI: Douglas J. Weber, Ph.D. University of Pittsburgh 1 10/15/2007 Scientific progress and accomplishments. We...information to the brain. A new animal model for developing a somatosensory neural interface for neuroprosthetic limbs . PI: Douglas J. Weber, Ph.D...A new animal model for developing a somatosensory neural interface for neuroprosthetic limbs . PI: Douglas J. Weber, Ph.D. University of Pittsburgh

Bidirectional neural interface: Closed-loop feedback control for hybrid neural systems.

PubMed

Chou, Zane; Lim, Jeffrey; Brown, Sophie; Keller, Melissa; Bugbee, Joseph; Broccard, Frédéric D; Khraiche, Massoud L; Silva, Gabriel A; Cauwenberghs, Gert

2015-01-01

Closed-loop neural prostheses enable bidirectional communication between the biological and artificial components of a hybrid system. However, a major challenge in this field is the limited understanding of how these components, the two separate neural networks, interact with each other. In this paper, we propose an in vitro model of a closed-loop system that allows for easy experimental testing and modification of both biological and artificial network parameters. The interface closes the system loop in real time by stimulating each network based on recorded activity of the other network, within preset parameters. As a proof of concept we demonstrate that the bidirectional interface is able to establish and control network properties, such as synchrony, in a hybrid system of two neural networks more significantly more effectively than the same system without the interface or with unidirectional alternatives. This success holds promise for the application of closed-loop systems in neural prostheses, brain-machine interfaces, and drug testing.

Molecular Electronic Devices Based On Electrooptical Behavior Of Heme-Like Molecules

NASA Astrophysics Data System (ADS)

Simic-Glavaski, B.

1986-02-01

This paper discusses application of the electrically modulated and unusually strong Raman emitted light produced by an adsorbed monolayer of phthalocyanine molecules on silver electrode or silver bromide substrates and on neural membranes. The analysis of electronic energy levels in semiconducting silver bromide and the adsorbed phthalocyanine molecules suggests a lasing mechanism as a possible origin of the high enhancement factor in surface enhanced Raman scattering. Electrically modulated Raman scattering may be used as a carrier of information which is drawn fran the fast intramolecular electron transfer aN,the multiplicity of quantum wells in phthalocyanine molecules. Fast switching times on the order of 10-13 seconds have been measured at room temperature. Multilevel and multioutput optical signals have also been obtained fran such an electrically modulated adsorbed monolayer of phthalocyanine molecules which can be precisely addressed and interrogated. This may be of practical use to develop Nlecular electronic devices with high density memory and fast parallel processing systems with a typical 1020 gate Hz/cm2 capacity at room temperature for use in optical computers. The paper also discusses the electrooptical modulation of Raman signals obtained from adsorbed bio-compatible phthalocyanine molecules on nerve membranes. This optical probe of neural systems can be used in studies of complex information processing in neural nets and provides a possible method for interfacing natural and man-made information processing devices.

A physiological and behavioral system for hearing restoration with cochlear implants

PubMed Central

King, Julia; Shehu, Ina; Roland, J. Thomas; Svirsky, Mario A.

2016-01-01

Cochlear implants are neuroprosthetic devices that provide hearing to deaf patients, although outcomes are highly variable even with prolonged training and use. The central auditory system must process cochlear implant signals, but it is unclear how neural circuits adapt—or fail to adapt—to such inputs. The knowledge of these mechanisms is required for development of next-generation neuroprosthetics that interface with existing neural circuits and enable synaptic plasticity to improve perceptual outcomes. Here, we describe a new system for cochlear implant insertion, stimulation, and behavioral training in rats. Animals were first ensured to have significant hearing loss via physiological and behavioral criteria. We developed a surgical approach for multichannel (2- or 8-channel) array insertion, comparable with implantation procedures and depth in humans. Peripheral and cortical responses to stimulation were used to program the implant objectively. Animals fitted with implants learned to use them for an auditory-dependent task that assesses frequency detection and recognition in a background of environmentally and self-generated noise and ceased responding appropriately to sounds when the implant was temporarily inactivated. This physiologically calibrated and behaviorally validated system provides a powerful opportunity to study the neural basis of neuroprosthetic device use and plasticity. PMID:27281743

In vivo imaging of neuronal calcium during electrode implantation: Spatial and temporal mapping of damage and recovery.

PubMed

Eles, James R; Vazquez, Alberto L; Kozai, Takashi D Y; Cui, X Tracy

2018-08-01

Implantable electrode devices enable long-term electrophysiological recordings for brain-machine interfaces and basic neuroscience research. Implantation of these devices, however, leads to neuronal damage and progressive neural degeneration that can lead to device failure. The present study uses in vivo two-photon microscopy to study the calcium activity and morphology of neurons before, during, and one month after electrode implantation to determine how implantation trauma injures neurons. We show that implantation leads to prolonged, elevated calcium levels in neurons within 150 μm of the electrode interface. These neurons show signs of mechanical distortion and mechanoporation after implantation, suggesting that calcium influx is related to mechanical trauma. Further, calcium-laden neurites develop signs of axonal injury at 1-3 h post-insert. Over the first month after implantation, physiological neuronal calcium activity increases, suggesting that neurons may be recovering. By defining the mechanisms of neuron damage after electrode implantation, our results suggest new directions for therapies to improve electrode longevity. Copyright © 2018 Elsevier Ltd. All rights reserved.

A silicon carbide array for electrocorticography and peripheral nerve recording.

PubMed

Diaz-Botia, C A; Luna, L E; Neely, R M; Chamanzar, M; Carraro, C; Carmena, J M; Sabes, P N; Maboudian, R; Maharbiz, M M

2017-10-01

Current neural probes have a limited device lifetime of a few years. Their common failure mode is the degradation of insulating films and/or the delamination of the conductor-insulator interfaces. We sought to develop a technology that does not suffer from such limitations and would be suitable for chronic applications with very long device lifetimes. We developed a fabrication method that integrates polycrystalline conductive silicon carbide with insulating silicon carbide. The technology employs amorphous silicon carbide as the insulator and conductive silicon carbide at the recording sites, resulting in a seamless transition between doped and amorphous regions of the same material, eliminating heterogeneous interfaces prone to delamination. Silicon carbide has outstanding chemical stability, is biocompatible, is an excellent molecular barrier and is compatible with standard microfabrication processes. We have fabricated silicon carbide electrode arrays using our novel fabrication method. We conducted in vivo experiments in which electrocorticography recordings from the primary visual cortex of a rat were obtained and were of similar quality to those of polymer based electrocorticography arrays. The silicon carbide electrode arrays were also used as a cuff electrode wrapped around the sciatic nerve of a rat to record the nerve response to electrical stimulation. Finally, we demonstrated the outstanding long term stability of our insulating silicon carbide films through accelerated aging tests. Clinical translation in neural engineering has been slowed in part due to the poor long term performance of current probes. Silicon carbide devices are a promising technology that may accelerate this transition by enabling truly chronic applications.

A silicon carbide array for electrocorticography and peripheral nerve recording

NASA Astrophysics Data System (ADS)

Diaz-Botia, C. A.; Luna, L. E.; Neely, R. M.; Chamanzar, M.; Carraro, C.; Carmena, J. M.; Sabes, P. N.; Maboudian, R.; Maharbiz, M. M.

2017-10-01

Objective. Current neural probes have a limited device lifetime of a few years. Their common failure mode is the degradation of insulating films and/or the delamination of the conductor-insulator interfaces. We sought to develop a technology that does not suffer from such limitations and would be suitable for chronic applications with very long device lifetimes. Approach. We developed a fabrication method that integrates polycrystalline conductive silicon carbide with insulating silicon carbide. The technology employs amorphous silicon carbide as the insulator and conductive silicon carbide at the recording sites, resulting in a seamless transition between doped and amorphous regions of the same material, eliminating heterogeneous interfaces prone to delamination. Silicon carbide has outstanding chemical stability, is biocompatible, is an excellent molecular barrier and is compatible with standard microfabrication processes. Main results. We have fabricated silicon carbide electrode arrays using our novel fabrication method. We conducted in vivo experiments in which electrocorticography recordings from the primary visual cortex of a rat were obtained and were of similar quality to those of polymer based electrocorticography arrays. The silicon carbide electrode arrays were also used as a cuff electrode wrapped around the sciatic nerve of a rat to record the nerve response to electrical stimulation. Finally, we demonstrated the outstanding long term stability of our insulating silicon carbide films through accelerated aging tests. Significance. Clinical translation in neural engineering has been slowed in part due to the poor long term performance of current probes. Silicon carbide devices are a promising technology that may accelerate this transition by enabling truly chronic applications.

Brain-computer interface controlled functional electrical stimulation device for foot drop due to stroke.

PubMed

Do, An H; Wang, Po T; King, Christine E; Schombs, Andrew; Cramer, Steven C; Nenadic, Zoran

2012-01-01

Gait impairment due to foot drop is a common outcome of stroke, and current physiotherapy provides only limited restoration of gait function. Gait function can also be aided by orthoses, but these devices may be cumbersome and their benefits disappear upon removal. Hence, new neuro-rehabilitative therapies are being sought to generate permanent improvements in motor function beyond those of conventional physiotherapies through positive neural plasticity processes. Here, the authors describe an electroencephalogram (EEG) based brain-computer interface (BCI) controlled functional electrical stimulation (FES) system that enabled a stroke subject with foot drop to re-establish foot dorsiflexion. To this end, a prediction model was generated from EEG data collected as the subject alternated between periods of idling and attempted foot dorsiflexion. This prediction model was then used to classify online EEG data into either "idling" or "dorsiflexion" states, and this information was subsequently used to control an FES device to elicit effective foot dorsiflexion. The performance of the system was assessed in online sessions, where the subject was prompted by a computer to alternate between periods of idling and dorsiflexion. The subject demonstrated purposeful operation of the BCI-FES system, with an average cross-correlation between instructional cues and BCI-FES response of 0.60 over 3 sessions. In addition, analysis of the prediction model indicated that non-classical brain areas were activated in the process, suggesting post-stroke cortical re-organization. In the future, these systems may be explored as a potential therapeutic tool that can help promote positive plasticity and neural repair in chronic stroke patients.

A Fully Integrated Wireless Compressed Sensing Neural Signal Acquisition System for Chronic Recording and Brain Machine Interface.

PubMed

Liu, Xilin; Zhang, Milin; Xiong, Tao; Richardson, Andrew G; Lucas, Timothy H; Chin, Peter S; Etienne-Cummings, Ralph; Tran, Trac D; Van der Spiegel, Jan

2016-07-18

Reliable, multi-channel neural recording is critical to the neuroscience research and clinical treatment. However, most hardware development of fully integrated, multi-channel wireless neural recorders to-date, is still in the proof-of-concept stage. To be ready for practical use, the trade-offs between performance, power consumption, device size, robustness, and compatibility need to be carefully taken into account. This paper presents an optimized wireless compressed sensing neural signal recording system. The system takes advantages of both custom integrated circuits and universal compatible wireless solutions. The proposed system includes an implantable wireless system-on-chip (SoC) and an external wireless relay. The SoC integrates 16-channel low-noise neural amplifiers, programmable filters and gain stages, a SAR ADC, a real-time compressed sensing module, and a near field wireless power and data transmission link. The external relay integrates a 32 bit low-power microcontroller with Bluetooth 4.0 wireless module, a programming interface, and an inductive charging unit. The SoC achieves high signal recording quality with minimized power consumption, while reducing the risk of infection from through-skin connectors. The external relay maximizes the compatibility and programmability. The proposed compressed sensing module is highly configurable, featuring a SNDR of 9.78 dB with a compression ratio of 8×. The SoC has been fabricated in a 180 nm standard CMOS technology, occupying 2.1 mm × 0.6 mm silicon area. A pre-implantable system has been assembled to demonstrate the proposed paradigm. The developed system has been successfully used for long-term wireless neural recording in freely behaving rhesus monkey.

Optical Neural Interfaces

PubMed Central

Warden, Melissa R.; Cardin, Jessica A.; Deisseroth, Karl

2014-01-01

Genetically encoded optical actuators and indicators have changed the landscape of neuroscience, enabling targetable control and readout of specific components of intact neural circuits in behaving animals. Here, we review the development of optical neural interfaces, focusing on hardware designed for optical control of neural activity, integrated optical control and electrical readout, and optical readout of population and single-cell neural activity in freely moving mammals. PMID:25014785

Reactivation of emergent task-related ensembles during slow-wave sleep after neuroprosthetic learning

PubMed Central

Gulati, Tanuj; Ramanathan, Dhakshin; Wong, Chelsea; Ganguly, Karunesh

2017-01-01

Brain-Machine Interfaces can allow neural control over assistive devices. They also provide an important platform to study neural plasticity. Recent studies indicate that optimal engagement of learning is essential for robust neuroprosthetic control. However, little is known about the neural processes that may consolidate a neuroprosthetic skill. Based on the growing body of evidence linking slow-wave activity (SWA) during sleep to consolidation, we examined if there is ‘offline’ processing after neuroprosthetic learning. Using a rodent model, here we show that after successful learning, task-related units specifically experienced increased locking and coherency to SWA during sleep. Moreover, spike-spike coherence among these units was significantly enhanced. These changes were not present with poor skill acquisition or after control awake periods, demonstrating specificity of our observations to learning. Interestingly, time spent in SWA predicted performance gains. Thus, SWA appears to play a role in offline processing after neuroprosthetic learning. PMID:24997761

Dynamic gesture recognition using neural networks: a fundament for advanced interaction construction

NASA Astrophysics Data System (ADS)

Boehm, Klaus; Broll, Wolfgang; Sokolewicz, Michael A.

1994-04-01

Interaction in virtual reality environments is still a challenging task. Static hand posture recognition is currently the most common and widely used method for interaction using glove input devices. In order to improve the naturalness of interaction, and thereby decrease the user-interface learning time, there is a need to be able to recognize dynamic gestures. In this paper we describe our approach to overcoming the difficulties of dynamic gesture recognition (DGR) using neural networks. Backpropagation neural networks have already proven themselves to be appropriate and efficient for posture recognition. However, the extensive amount of data involved in DGR requires a different approach. Because of features such as topology preservation and automatic-learning, Kohonen Feature Maps are particularly suitable for the reduction of the high dimensional data space that is the result of a dynamic gesture, and are thus implemented for this task.

Neural Coding for Effective Rehabilitation

PubMed Central

2014-01-01

Successful neurological rehabilitation depends on accurate diagnosis, effective treatment, and quantitative evaluation. Neural coding, a technology for interpretation of functional and structural information of the nervous system, has contributed to the advancements in neuroimaging, brain-machine interface (BMI), and design of training devices for rehabilitation purposes. In this review, we summarized the latest breakthroughs in neuroimaging from microscale to macroscale levels with potential diagnostic applications for rehabilitation. We also reviewed the achievements in electrocorticography (ECoG) coding with both animal models and human beings for BMI design, electromyography (EMG) interpretation for interaction with external robotic systems, and robot-assisted quantitative evaluation on the progress of rehabilitation programs. Future rehabilitation would be more home-based, automatic, and self-served by patients. Further investigations and breakthroughs are mainly needed in aspects of improving the computational efficiency in neuroimaging and multichannel ECoG by selection of localized neuroinformatics, validation of the effectiveness in BMI guided rehabilitation programs, and simplification of the system operation in training devices. PMID:25258708

Acute changes associated with electrode insertion measured with optical coherence microscopy

NASA Astrophysics Data System (ADS)

Hammer, Daniel X.; Lozzi, Andrea; Boretsky, Adam; Agrawal, Anant; Welle, Cristin G.

2016-03-01

Despite advances in functional neural imaging, penetrating microelectrodes provide the most direct interface for the extraction of neural signals from the nervous system and are a critical component of many high degree-of-freedom braincomputer interface devices. Electrode insertion is a traumatic event that elicits a complex neuroinflammatory response. In this investigation we applied optical coherence microscopy (OCM), particularly optical coherence angiography (OCA), to characterize the immediate tissue response during microelectrode insertion. Microelectrodes of varying dimension and footprint (one-, two-, and four-shank) were inserted into mouse motor cortex beneath a window after craniotomy surgery. The microelectrodes were inserted in 3-4 steps at 15-20°, with approximately 250 μm linear insertion distance for each step. Before insertion and between each step, OCM datasets were collected, including for quantitative capillary velocimetry. A cohort of control animals without microelectrode insertion was also imaged over a similar time period (2-3 hours). Mechanical tissue deformation was observed in all the experimental animals. The quantitative angiography results varied across animals, and were not correlated with device dimensions. In some cases, localized flow drop-out was observed in a small region surrounding the electrode, while in other instances a global disruption in flow occurred, perhaps as a result of large vessel compression caused by mechanical pressure. OCM is a tool that can be used in various neurophotonics applications, including quantification of the neuroinflammatory response to penetrating electrode insertion.

Toward more versatile and intuitive cortical brain-machine interfaces.

PubMed

Andersen, Richard A; Kellis, Spencer; Klaes, Christian; Aflalo, Tyson

2014-09-22

Brain-machine interfaces have great potential for the development of neuroprosthetic applications to assist patients suffering from brain injury or neurodegenerative disease. One type of brain-machine interface is a cortical motor prosthetic, which is used to assist paralyzed subjects. Motor prosthetics to date have typically used the motor cortex as a source of neural signals for controlling external devices. The review will focus on several new topics in the arena of cortical prosthetics. These include using: recordings from cortical areas outside motor cortex; local field potentials as a source of recorded signals; somatosensory feedback for more dexterous control of robotics; and new decoding methods that work in concert to form an ecology of decode algorithms. These new advances promise to greatly accelerate the applicability and ease of operation of motor prosthetics. Copyright © 2014 Elsevier Ltd. All rights reserved.

A training platform for many-dimensional prosthetic devices using a virtual reality environment

PubMed Central

Putrino, David; Wong, Yan T.; Weiss, Adam; Pesaran, Bijan

2014-01-01

Brain machine interfaces (BMIs) have the potential to assist in the rehabilitation of millions of patients worldwide. Despite recent advancements in BMI technology for the restoration of lost motor function, a training environment to restore full control of the anatomical segments of an upper limb extremity has not yet been presented. Here, we develop a virtual upper limb prosthesis with 27 independent dimensions, the anatomical dimensions of the human arm and hand, and deploy the virtual prosthesis as an avatar in a virtual reality environment (VRE) that can be controlled in real-time. The prosthesis avatar accepts kinematic control inputs that can be captured from movements of the arm and hand as well as neural control inputs derived from processed neural signals. We characterize the system performance under kinematic control using a commercially available motion capture system. We also present the performance under kinematic control achieved by two non-human primates (Macaca Mulatta) trained to use the prosthetic avatar to perform reaching and grasping tasks. This is the first virtual prosthetic device that is capable of emulating all the anatomical movements of a healthy upper limb in real-time. Since the system accepts both neural and kinematic inputs for a variety of many-dimensional skeletons, we propose it provides a customizable training platform for the acquisition of many-dimensional neural prosthetic control. PMID:24726625

New Perspectives on Neuroengineering and Neurotechnologies: NSF-DFG Workshop Report.

PubMed

Moritz, Chet T; Ruther, Patrick; Goering, Sara; Stett, Alfred; Ball, Tonio; Burgard, Wolfram; Chudler, Eric H; Rao, Rajesh P N

2016-07-01

To identify and overcome barriers to creating new neurotechnologies capable of restoring both motor and sensory function in individuals with neurological conditions. This report builds upon the outcomes of a joint workshop between the US National Science Foundation and the German Research Foundation on New Perspectives in Neuroengineering and Neurotechnology convened in Arlington, VA, USA, November 13-14, 2014. The participants identified key technological challenges for recording and manipulating neural activity, decoding, and interpreting brain data in the presence of plasticity, and early considerations of ethical and social issues pertinent to the adoption of neurotechnologies. The envisaged progress in neuroengineering requires tightly integrated hardware and signal processing efforts, advances in understanding of physiological adaptations to closed-loop interactions with neural devices, and an open dialog with stakeholders and potential end-users of neurotechnology. The development of new neurotechnologies (e.g., bidirectional brain-computer interfaces) could significantly improve the quality of life of people living with the effects of brain or spinal cord injury, or other neurodegenerative diseases. Focused efforts aimed at overcoming the remaining barriers at the electrode tissue interface, developing implantable hardware with on-board computation, and refining stimulation methods to precisely activate neural tissue will advance both our understanding of brain function and our ability to treat currently intractable disorders of the nervous system.

Safe Direct Current Stimulation to Expand Capabilities of Neural Prostheses

PubMed Central

Fridman, Gene Y.; Della Santina, Charles C.

2014-01-01

While effective in treating some neurological disorders, neuroelectric prostheses are fundamentally limited because they must employ charge-balanced stimuli to avoid evolution of irreversible electrochemical reactions and their byproducts at the interface between metal electrodes and body fluids. Charge-balancing is typically achieved by using brief biphasic alternating current (AC) pulses, which typically excite nearby neural tissues but cannot efficiently inhibit them. In contrast, direct current (DC) applied via a metal electrode in contact with body fluids can excite, inhibit and modulate sensitivity of neurons; however, DC stimulation is biologically unsafe because it violates “safe charge injection” limits that have long been considered unavoidable constraints. In this report, we describe the design and fabrication of a safe DC stimulator (SDCS) that overcomes this constraint. The SCDS drives DC ionic current into target tissue via salt-bridge micropipette electrodes by switching valves in phase with AC square waves applied to metal electrodes contained within the device. This approach achieves DC ionic flow through tissue while still adhering to charge-balancing constraints at each electrode-saline interface. We show the SDCS’s ability to both inhibit and excite neural activity to achieve improved dynamic range during prosthetic stimulation of the vestibular part of the inner ear in chinchillas. PMID:23476007

A regenerative microchannel device for recording multiple single-unit action potentials in awake, ambulatory animals.

PubMed

Srinivasan, Akhil; Tipton, John; Tahilramani, Mayank; Kharbouch, Adel; Gaupp, Eric; Song, Chao; Venkataraman, Poornima; Falcone, Jessica; Lacour, Stéphanie P; Stanley, Garrett B; English, Arthur W; Bellamkonda, Ravi V

2016-02-01

Despite significant advances in robotics, commercially advanced prosthetics provide only a small fraction of the functionality of the amputated limb that they are meant to replace. Peripheral nerve interfacing could provide a rich controlling link between the body and these advanced prosthetics in order to increase their overall utility. Here, we report on the development of a fully integrated regenerative microchannel interface with 30 microelectrodes and signal extraction capabilities enabling evaluation in an awake and ambulatory rat animal model. In vitro functional testing validated the capability of the microelectrodes to record neural signals similar in size and nature to those that occur in vivo. In vitro dorsal root ganglia cultures revealed striking cytocompatibility of the microchannel interface. Finally, in vivo, the microchannel interface was successfully used to record a multitude of single-unit action potentials through 63% of the integrated microelectrodes at the early time point of 3 weeks. This marks a significant advance in microchannel interfacing, demonstrating the capability of microchannels to be used for peripheral nerve interfacing. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Assessing the Depth of Cognitive Processing as the Basis for Potential User-State Adaptation

PubMed Central

Nicolae, Irina-Emilia; Acqualagna, Laura; Blankertz, Benjamin

2017-01-01

Objective: Decoding neurocognitive processes on a single-trial basis with Brain-Computer Interface (BCI) techniques can reveal the user's internal interpretation of the current situation. Such information can potentially be exploited to make devices and interfaces more user aware. In this line of research, we took a further step by studying neural correlates of different levels of cognitive processes and developing a method that allows to quantify how deeply presented information is processed in the brain. Methods/Approach: Seventeen participants took part in an EEG study in which we evaluated different levels of cognitive processing (no processing, shallow, and deep processing) within three distinct domains (memory, language, and visual imagination). Our investigations showed gradual differences in the amplitudes of event-related potentials (ERPs) and in the extend and duration of event-related desynchronization (ERD) which both correlate with task difficulty. We performed multi-modal classification to map the measured correlates of neurocognitive processing to the corresponding level of processing. Results: Successful classification of the neural components was achieved, which reflects the level of cognitive processing performed by the participants. The results show performances above chance level for each participant and a mean performance of 70–90% for all conditions and classification pairs. Significance: The successful estimation of the level of cognition on a single-trial basis supports the feasibility of user-state adaptation based on ongoing neural activity. There is a variety of potential use cases such as: a user-friendly adaptive design of an interface or the development of assistance systems in safety critical workplaces. PMID:29046625

Assessing the Depth of Cognitive Processing as the Basis for Potential User-State Adaptation.

PubMed

Nicolae, Irina-Emilia; Acqualagna, Laura; Blankertz, Benjamin

2017-01-01

Objective: Decoding neurocognitive processes on a single-trial basis with Brain-Computer Interface (BCI) techniques can reveal the user's internal interpretation of the current situation. Such information can potentially be exploited to make devices and interfaces more user aware. In this line of research, we took a further step by studying neural correlates of different levels of cognitive processes and developing a method that allows to quantify how deeply presented information is processed in the brain. Methods/Approach: Seventeen participants took part in an EEG study in which we evaluated different levels of cognitive processing (no processing, shallow, and deep processing) within three distinct domains (memory, language, and visual imagination). Our investigations showed gradual differences in the amplitudes of event-related potentials (ERPs) and in the extend and duration of event-related desynchronization (ERD) which both correlate with task difficulty. We performed multi-modal classification to map the measured correlates of neurocognitive processing to the corresponding level of processing. Results: Successful classification of the neural components was achieved, which reflects the level of cognitive processing performed by the participants. The results show performances above chance level for each participant and a mean performance of 70-90% for all conditions and classification pairs. Significance: The successful estimation of the level of cognition on a single-trial basis supports the feasibility of user-state adaptation based on ongoing neural activity. There is a variety of potential use cases such as: a user-friendly adaptive design of an interface or the development of assistance systems in safety critical workplaces.

Brain computer interface learning for systems based on electrocorticography and intracortical microelectrode arrays.

PubMed

Hiremath, Shivayogi V; Chen, Weidong; Wang, Wei; Foldes, Stephen; Yang, Ying; Tyler-Kabara, Elizabeth C; Collinger, Jennifer L; Boninger, Michael L

2015-01-01

A brain-computer interface (BCI) system transforms neural activity into control signals for external devices in real time. A BCI user needs to learn to generate specific cortical activity patterns to control external devices effectively. We call this process BCI learning, and it often requires significant effort and time. Therefore, it is important to study this process and develop novel and efficient approaches to accelerate BCI learning. This article reviews major approaches that have been used for BCI learning, including computer-assisted learning, co-adaptive learning, operant conditioning, and sensory feedback. We focus on BCIs based on electrocorticography and intracortical microelectrode arrays for restoring motor function. This article also explores the possibility of brain modulation techniques in promoting BCI learning, such as electrical cortical stimulation, transcranial magnetic stimulation, and optogenetics. Furthermore, as proposed by recent BCI studies, we suggest that BCI learning is in many ways analogous to motor and cognitive skill learning, and therefore skill learning should be a useful metaphor to model BCI learning.

Non-causal spike filtering improves decoding of movement intention for intracortical BCIs

PubMed Central

Masse, Nicolas Y.; Jarosiewicz, Beata; Simeral, John D.; Bacher, Daniel; Stavisky, Sergey D.; Cash, Sydney S.; Oakley, Erin M.; Berhanu, Etsub; Eskandar, Emad; Friehs, Gerhard; Hochberg, Leigh R.; Donoghue, John P.

2014-01-01

Background Multiple types of neural signals are available for controlling assistive devices through brain-computer interfaces (BCIs). Intracortically-recorded spiking neural signals are attractive for BCIs because they can in principle provide greater fidelity of encoded information compared to electrocorticographic (ECoG) signals and electroencephalograms (EEGs). Recent reports show that the information content of these spiking neural signals can be reliably extracted simply by causally band-pass filtering the recorded extracellular voltage signals and then applying a spike detection threshold, without relying on “sorting” action potentials. New method We show that replacing the causal filter with an equivalent non-causal filter increases the information content extracted from the extracellular spiking signal and improves decoding of intended movement direction. This method can be used for real-time BCI applications by using a 4 ms lag between recording and filtering neural signals. Results Across 18 sessions from two people with tetraplegia enrolled in the BrainGate2 pilot clinical trial, we found that threshold crossing events extracted using this non-causal filtering method were significantly more informative of each participant’s intended cursor kinematics compared to threshold crossing events derived from causally filtered signals. This new method decreased the mean angular error between the intended and decoded cursor direction by 9.7° for participant S3, who was implanted 5.4 years prior to this study, and by 3.5° for participant T2, who was implanted 3 months prior to this study. Conclusions Non-causally filtering neural signals prior to extracting threshold crossing events may be a simple yet effective way to condition intracortically recorded neural activity for direct control of external devices through BCIs. PMID:25128256

Command and control interfaces for advanced neuroprosthetic applications.

PubMed

Scott, T R; Haugland, M

2001-10-01

Command and control interfaces permit the intention and situation of the user to influence the operation of the neural prosthesis. The wishes of the user are communicated via command interfaces to the neural prosthesis and the situation of the user by feedback control interfaces. Both these interfaces have been reviewed separately and are discussed in light of the current state of the art and projections for the future. It is apparent that as system functional complexity increases, the need for simpler command interfaces will increase. Such systems will demand more information to function effectively in order not to unreasonably increase user attention overhead. This will increase the need for bioelectric and biomechanical signals in a comprehensible form via elegant feedback control interfaces. Implementing such systems will also increase the computational demand on such neural prostheses.

SNAVA-A real-time multi-FPGA multi-model spiking neural network simulation architecture.

PubMed

Sripad, Athul; Sanchez, Giovanny; Zapata, Mireya; Pirrone, Vito; Dorta, Taho; Cambria, Salvatore; Marti, Albert; Krishnamourthy, Karthikeyan; Madrenas, Jordi

2018-01-01

Spiking Neural Networks (SNN) for Versatile Applications (SNAVA) simulation platform is a scalable and programmable parallel architecture that supports real-time, large-scale, multi-model SNN computation. This parallel architecture is implemented in modern Field-Programmable Gate Arrays (FPGAs) devices to provide high performance execution and flexibility to support large-scale SNN models. Flexibility is defined in terms of programmability, which allows easy synapse and neuron implementation. This has been achieved by using a special-purpose Processing Elements (PEs) for computing SNNs, and analyzing and customizing the instruction set according to the processing needs to achieve maximum performance with minimum resources. The parallel architecture is interfaced with customized Graphical User Interfaces (GUIs) to configure the SNN's connectivity, to compile the neuron-synapse model and to monitor SNN's activity. Our contribution intends to provide a tool that allows to prototype SNNs faster than on CPU/GPU architectures but significantly cheaper than fabricating a customized neuromorphic chip. This could be potentially valuable to the computational neuroscience and neuromorphic engineering communities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of high-performing semiconducting polymers for organic electrochemical transistors (Conference Presentation)

NASA Astrophysics Data System (ADS)

Nielsen, Christian

2016-11-01

The organic electrochemical transistor (OECT), capable of amplifying small electrical signals in an aqueous environment, is an ideal device to utilize in organic bioelectronic applications involving for example neural interfacing and diagnostics. Currently, most OECTs are fabricated with commercially available conducting poly(3,4-ethylenedioxythiophene)-based suspensions such as PEDOT:PSS and are therefore operated in depletion mode giving rise to devices that are permanently on with non-optimal operational voltage. With the aim to develop and utilize efficient accumulation mode OECT devices, we discuss here our recent results regarding the design, synthesis and performance of novel intrinsic semiconducting polymers. Covering key aspects such as ion and charge transport in the bulk semiconductor and operational voltage and stability of the materials and devices, we have elucidated important structure-property relationships. We illustrate the improvements this approach has afforded in the development of high performance accumulation mode OECT materials.

AsTeRICS.

PubMed

Drajsajtl, Tomáš; Struk, Petr; Bednárová, Alice

2013-01-01

AsTeRICS - "The Assistive Technology Rapid Integration & Construction Set" is a construction set for assistive technologies which can be adapted to the motor abilities of end-users. AsTeRICS allows access to different devices such as PCs, cell phones and smart home devices, with all of them integrated in a platform adapted as much as possible to each user. People with motor disabilities in the upper limbs, with no cognitive impairment, no perceptual limitations (neither visual nor auditory) and with basic skills in using technologies such as PCs, cell phones, electronic agendas, etc. have available a flexible and adaptable technology which enables them to access the Human-Machine-Interfaces (HMI) on the standard desktop and beyond. AsTeRICS provides graphical model design tools, a middleware and hardware support for the creation of tailored AT-solutions involving bioelectric signal acquisition, Brain-/Neural Computer Interfaces, Computer-Vision techniques and standardized actuator and device controls and allows combining several off-the-shelf AT-devices in every desired combination. Novel, end-user ready solutions can be created and adapted via a graphical editor without additional programming efforts. The AsTeRICS open-source framework provides resources for utilization and extension of the system to developers and researches. AsTeRICS was developed by the AsTeRICS project and was partially funded by EC.

Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia*

PubMed Central

Kim, Sung-Phil; Simeral, John D; Hochberg, Leigh R; Donoghue, John P; Black, Michael J

2010-01-01

Computer-mediated connections between human motor cortical neurons and assistive devices promise to improve or restore lost function in people with paralysis. Recently, a pilot clinical study of an intracortical neural interface system demonstrated that a tetraplegic human was able to obtain continuous two-dimensional control of a computer cursor using neural activity recorded from his motor cortex. This control, however, was not sufficiently accurate for reliable use in many common computer control tasks. Here, we studied several central design choices for such a system including the kinematic representation for cursor movement, the decoding method that translates neuronal ensemble spiking activity into a control signal and the cursor control task used during training for optimizing the parameters of the decoding method. In two tetraplegic participants, we found that controlling a cursor's velocity resulted in more accurate closed-loop control than controlling its position directly and that cursor velocity control was achieved more rapidly than position control. Control quality was further improved over conventional linear filters by using a probabilistic method, the Kalman filter, to decode human motor cortical activity. Performance assessment based on standard metrics used for the evaluation of a wide range of pointing devices demonstrated significantly improved cursor control with velocity rather than position decoding. PMID:19015583

Use of Research Interfaces for Psychophysical Studies With Cochlear-Implant Users

PubMed Central

Goupell, Matthew J.; Kan, Alan; Landsberger, David M.

2017-01-01

A growing number of laboratories are using research interfaces to conduct experiments with cochlear-implant (CI) users. Because these interfaces bypass a subject’s clinical sound processor, several concerns exist regarding safety and stimulation levels. Here we suggest best-practice approaches for how to safely and ethically perform this type of research and highlight areas of limited knowledge where further research is needed to help clarify safety limits. The article is designed to provide an introductory level of technical detail about the devices and the effects of electrical stimulation on perception and neurophysiology. From this, we summarize what should be the best practices in the field, based on the literature and our experience. Findings from the review of the literature suggest that there are three main safety concerns: (a) to prevent biological or neural damage, (b) to avoid presentation of uncomfortably loud sounds, and (c) to ensure that subjects have control over stimulus presentation. Researchers must pay close attention to the software–hardware interface to ensure that the three main safety concerns are closely monitored. An important area for future research will be the determination of the amount of biological damage that can occur from electrical stimulation from a CI placed in the cochlea, not in direct contact with neural tissue. As technology used in research with CIs evolve, some of these approaches may change. However, the three main safety principles outlined here are not anticipated to undergo change with technological advances. PMID:29113579

Employing TDMA Protocol in Neural Nanonetworks in Case of Neuron Specific Faults.

PubMed

Tezcan, Hakan; Oktug, Sema F; Kök, Fatma Neşe

2015-09-01

Many neurodegenerative diseases arise from the malfunctioning neurons in the pathway where the signal is carried. In this paper, we propose neuron specific TDMA/multiplexing and demultiplexing mechanisms to convey the spikes of a receptor neuron over a neighboring path in case of an irreversible path fault existing in its original path. The multiplexing mechanism depends on neural delay box (NDB) which is composed of a relay unit and a buffering unit. The relay unit can be realized as a nanoelectronic device. The buffering unit can be implemented either via neural delay lines as employed in optical switching systems or via nanoelectronic delay lines, i.e., delay flip flops. Demultiplexing is realized by a demultiplexer unit according to the time slot assignment information. Besides, we propose the use of neural interfaces in the NDBs and the demultiplexer unit for detecting and stimulating the generation of spikes. The objective of the proposed mechanisms is to substitute a malfunctioning path, increase the number of spikes delivered and correctly deliver the spikes to the intended part of the somatosensory cortex. The results demonstrate that significant performance improvement on the successively delivered number of spikes is achievable when delay lines are employed as neural buffers in NDBs.

A programmable closed-loop recording and stimulating wireless system for behaving small laboratory animals

PubMed Central

Angotzi, Gian Nicola; Boi, Fabio; Zordan, Stefano; Bonfanti, Andrea; Vato, Alessandro

2014-01-01

A portable 16-channels microcontroller-based wireless system for a bi-directional interaction with the central nervous system is presented in this work. The device is designed to be used with freely behaving small laboratory animals and allows recording of spontaneous and evoked neural activity wirelessly transmitted and stored on a personal computer. Biphasic current stimuli with programmable duration, frequency and amplitude may be triggered in real-time on the basis of the recorded neural activity as well as by the animal behavior within a specifically designed experimental setup. An intuitive graphical user interface was developed to configure and to monitor the whole system. The system was successfully tested through bench tests and in vivo measurements on behaving rats chronically implanted with multi-channels microwire arrays. PMID:25096831

Design and manufacturing challenges of optogenetic neural interfaces: a review

NASA Astrophysics Data System (ADS)

Goncalves, S. B.; Ribeiro, J. F.; Silva, A. F.; Costa, R. M.; Correia, J. H.

2017-08-01

Optogenetics is a relatively new technology to achieve cell-type specific neuromodulation with millisecond-scale temporal precision. Optogenetic tools are being developed to address neuroscience challenges, and to improve the knowledge about brain networks, with the ultimate aim of catalyzing new treatments for brain disorders and diseases. To reach this ambitious goal the implementation of mature and reliable engineered tools is required. The success of optogenetics relies on optical tools that can deliver light into the neural tissue. Objective/Approach: Here, the design and manufacturing approaches available to the scientific community are reviewed, and current challenges to accomplish appropriate scalable, multimodal and wireless optical devices are discussed. Significance: Overall, this review aims at presenting a helpful guidance to the engineering and design of optical microsystems for optogenetic applications.

Gold Nanoparticles for Neural Prosthetics Devices

PubMed Central

Zhang, Huanan; Shih, Jimmy; Zhu, Jian; Kotov, Nicholas A.

2012-01-01

Treatments of neurological diseases and the realization of brain-computer interfaces require ultrasmall electrodes which are “invisible” to resident immune cells. Functional electrodes smaller than 50μm are impossible to produce with traditional materials due to high interfacial impedance at the characteristic frequency of neural activity and insufficient charge storage capacity. The problem can be resolved by using gold nanoparticle nanocomposites. Careful comparison indicates that layer-by-layer assembled films from Au NPs provide more than threefold improvement in interfacial impedance and one order of magnitude increase in charge storage capacity. Prototypes of microelectrodes could be made using traditional photolithography. Integration of unique nanocomposite materials with microfabrication techniques opens the door for practical realization of the ultrasmall implantable electrodes. Further improvement of electrical properties is expected when using special shapes of gold nanoparticles. PMID:22734673

An all-diamond, hermetic electrical feedthrough array for a retinal prosthesis.

PubMed

Ganesan, Kumaravelu; Garrett, David J; Ahnood, Arman; Shivdasani, Mohit N; Tong, Wei; Turnley, Ann M; Fox, Kate; Meffin, Hamish; Prawer, Steven

2014-01-01

The interface between medical implants and the human nervous system is rapidly becoming more and more complex. This rise in complexity is driving the need for increasing numbers of densely packed electrical feedthrough to carry signals to and from implanted devices. This is particularly crucial in the field of neural prosthesis where high resolution stimulating or recording arrays near peripheral nerves or in the brain could dramatically improve the performance of these devices. Here we describe a flexible strategy for implementing high density, high count arrays of hermetic electrical feedthroughs by forming conducting nitrogen doped nanocrystalline diamond channels within an insulating polycrystalline diamond substrate. A unique feature of these arrays is that the feedthroughs can themselves be used as stimulating electrodes for neural tissue. Our particular application is such a feedthrough, designed as a component of a retinal implant to restore vision to the blind. The hermeticity of the feedthroughs means that the array can also form part of an implantable capsule which can interface directly with internal electronic chips. The hermeticity of the array is demonstrated by helium leak tests and electrical and electrochemical characterisation of the feedthroughs is described. The nitrogen doped nanocrystalline diamond forming the electrical feedthroughs is shown to be non-cyctotoxic. New fabrication strategies, such as the one described here, combined with the exceptional biostability of diamond can be exploited to generate a range of biomedical implants that last for the lifetime of the user without fear of degradation.

Techniques and devices to restore cognition

PubMed Central

Serruya, Mijail Demian; Kahana, Michael J.

2011-01-01

Executive planning, the ability to direct and sustain attention, language and several types of memory may be compromised by conditions such as stroke, traumatic brain injury, cancer, autism, cerebral palsy and Alzheimer’s disease. No medical devices are currently available to help restore these cognitive functions. Recent findings about the neurophysiology of these conditions in humans coupled with progress in engineering devices to treat refractory neurological conditions imply that the time has arrived to consider the design and evaluation of a new class of devices. Like their neuromotor counterparts, neurocognitive prostheses might sense or modulate neural function in a non-invasive manner or by means of implanted electrodes. In order to paint a vision for future device development, it is essential to first review what can be achieved using behavioral and external modulatory techniques. While non-invasive approaches might strengthen a patient’s remaining intact cognitive abilities, neurocognitive prosthetics comprised of direct brain–computer interfaces could in theory physically reconstitute and augment the substrate of cognition itself. PMID:18539345

Biocompatibility of nanostructured boron doped diamond for the attachment and proliferation of human neural stem cells.

PubMed

Taylor, Alice C; Vagaska, Barbora; Edgington, Robert; Hébert, Clément; Ferretti, Patrizia; Bergonzo, Philippe; Jackman, Richard B

2015-12-01

We quantitatively investigate the biocompatibility of chemical vapour deposited (CVD) nanocrystalline diamond (NCD) after the inclusion of boron, with and without nanostructuring. The nanostructuring method involves a novel approach of growing NCD over carbon nanotubes (CNTs) that act as a 3D scaffold. This nanostructuring of BNCD leads to a material with increased capacitance, and this along with wide electrochemical window makes BNCD an ideal material for neural interface applications, and thus it is essential that their biocompatibility is investigated. Biocompatibility was assessed by observing the interaction of human neural stem cells (hNSCs) with a variety of NCD substrates including un-doped ones, and NCD doped with boron, which are both planar, and nanostructured. hNSCs were chosen due to their sensitivity, and various methods including cell population and confluency were used to quantify biocompatibility. Boron inclusion into NCD film was shown to have no observable effect on hNSC attachment, proliferation and viability. Furthermore, the biocompatibility of nanostructured boron-doped NCD is increased upon nanostructuring, potentially due to the increased surface area. Diamond is an attractive material for supporting the attachment and development of cells as it can show exceptional biocompatibility. When boron is used as a dopant within diamond it becomes a p-type semiconductor, and at high concentrations the diamond becomes quasi-metallic, offering the prospect of a direct electrical device-cell interfacing system.

Neurofeedback-based functional near-infrared spectroscopy upregulates motor cortex activity in imagined motor tasks

PubMed Central

Lapborisuth, Pawan; Zhang, Xian; Noah, Adam; Hirsch, Joy

2017-01-01

Abstract. Neurofeedback is a method for using neural activity displayed on a computer to regulate one’s own brain function and has been shown to be a promising technique for training individuals to interact with brain–machine interface applications such as neuroprosthetic limbs. The goal of this study was to develop a user-friendly functional near-infrared spectroscopy (fNIRS)-based neurofeedback system to upregulate neural activity associated with motor imagery, which is frequently used in neuroprosthetic applications. We hypothesized that fNIRS neurofeedback would enhance activity in motor cortex during a motor imagery task. Twenty-two participants performed active and imaginary right-handed squeezing movements using an elastic ball while wearing a 98-channel fNIRS device. Neurofeedback traces representing localized cortical hemodynamic responses were graphically presented to participants in real time. Participants were instructed to observe this graphical representation and use the information to increase signal amplitude. Neural activity was compared during active and imaginary squeezing with and without neurofeedback. Active squeezing resulted in activity localized to the left premotor and supplementary motor cortex, and activity in the motor cortex was found to be modulated by neurofeedback. Activity in the motor cortex was also shown in the imaginary squeezing condition only in the presence of neurofeedback. These findings demonstrate that real-time fNIRS neurofeedback is a viable platform for brain–machine interface applications. PMID:28680906

Neurofeedback-based functional near-infrared spectroscopy upregulates motor cortex activity in imagined motor tasks.

PubMed

Lapborisuth, Pawan; Zhang, Xian; Noah, Adam; Hirsch, Joy

2017-04-01

Neurofeedback is a method for using neural activity displayed on a computer to regulate one's own brain function and has been shown to be a promising technique for training individuals to interact with brain-machine interface applications such as neuroprosthetic limbs. The goal of this study was to develop a user-friendly functional near-infrared spectroscopy (fNIRS)-based neurofeedback system to upregulate neural activity associated with motor imagery, which is frequently used in neuroprosthetic applications. We hypothesized that fNIRS neurofeedback would enhance activity in motor cortex during a motor imagery task. Twenty-two participants performed active and imaginary right-handed squeezing movements using an elastic ball while wearing a 98-channel fNIRS device. Neurofeedback traces representing localized cortical hemodynamic responses were graphically presented to participants in real time. Participants were instructed to observe this graphical representation and use the information to increase signal amplitude. Neural activity was compared during active and imaginary squeezing with and without neurofeedback. Active squeezing resulted in activity localized to the left premotor and supplementary motor cortex, and activity in the motor cortex was found to be modulated by neurofeedback. Activity in the motor cortex was also shown in the imaginary squeezing condition only in the presence of neurofeedback. These findings demonstrate that real-time fNIRS neurofeedback is a viable platform for brain-machine interface applications.

Boron-Doped Nanocrystalline Diamond Electrodes for Neural Interfaces: In vivo Biocompatibility Evaluation

PubMed Central

Alcaide, María; Taylor, Andrew; Fjorback, Morten; Zachar, Vladimir; Pennisi, Cristian P.

2016-01-01

Boron-doped nanocrystalline diamond (BDD) electrodes have recently attracted attention as materials for neural electrodes due to their superior physical and electrochemical properties, however their biocompatibility remains largely unexplored. In this work, we aim to investigate the in vivo biocompatibility of BDD electrodes in relation to conventional titanium nitride (TiN) electrodes using a rat subcutaneous implantation model. High quality BDD films were synthesized on electrodes intended for use as an implantable neurostimulation device. After implantation for 2 and 4 weeks, tissue sections adjacent to the electrodes were obtained for histological analysis. Both types of implants were contained in a thin fibrous encapsulation layer, the thickness of which decreased with time. Although the level of neovascularization around the implants was similar, BDD electrodes elicited significantly thinner fibrous capsules and a milder inflammatory reaction at both time points. These results suggest that BDD films may constitute an appropriate material to support stable performance of implantable neural electrodes over time. PMID:27013949

Digital implementation of a neural network for imaging

NASA Astrophysics Data System (ADS)

Wood, Richard; McGlashan, Alex; Yatulis, Jay; Mascher, Peter; Bruce, Ian

2012-10-01

This paper outlines the design and testing of a digital imaging system that utilizes an artificial neural network with unsupervised and supervised learning to convert streaming input (real time) image space into parameter space. The primary objective of this work is to investigate the effectiveness of using a neural network to significantly reduce the information density of streaming images so that objects can be readily identified by a limited set of primary parameters and act as an enhanced human machine interface (HMI). Many applications are envisioned including use in biomedical imaging, anomaly detection and as an assistive device for the visually impaired. A digital circuit was designed and tested using a Field Programmable Gate Array (FPGA) and an off the shelf digital camera. Our results indicate that the networks can be readily trained when subject to limited sets of objects such as the alphabet. We can also separate limited object sets with rotational and positional invariance. The results also show that limited visual fields form with only local connectivity.

A 32-channel fully implantable wireless neurosensor for simultaneous recording from two cortical regions.

PubMed

Aceros, Juan; Yin, Ming; Borton, David A; Patterson, William R; Nurmikko, Arto V

2011-01-01

We present a fully implantable, wireless, neurosensor for multiple-location neural interface applications. The device integrates two independent 16-channel intracortical microelectrode arrays and can simultaneously acquire 32 channels of broadband neural data from two separate cortical areas. The system-on-chip implantable sensor is built on a flexible Kapton polymer substrate and incorporates three very low power subunits: two cortical subunits connected to a common subcutaneous subunit. Each cortical subunit has an ultra-low power 16-channel preamplifier and multiplexer integrated onto a cortical microelectrode array. The subcutaneous epicranial unit has an inductively coupled power supply, two analog-to-digital converters, a low power digital controller chip, and microlaser-based infrared telemetry. The entire system is soft encapsulated with biocompatible flexible materials for in vivo applications. Broadband neural data is conditioned, amplified, and analog multiplexed by each of the cortical subunits and passed to the subcutaneous component, where it is digitized and combined with synchronization data and wirelessly transmitted transcutaneously using high speed infrared telemetry.

A wireless transmission neural interface system for unconstrained non-human primates.

PubMed

Fernandez-Leon, Jose A; Parajuli, Arun; Franklin, Robert; Sorenson, Michael; Felleman, Daniel J; Hansen, Bryan J; Hu, Ming; Dragoi, Valentin

2015-10-01

Studying the brain in large animal models in a restrained laboratory rig severely limits our capacity to examine brain circuits in experimental and clinical applications. To overcome these limitations, we developed a high-fidelity 96-channel wireless system to record extracellular spikes and local field potentials from the neocortex. A removable, external case of the wireless device is attached to a titanium pedestal placed in the animal skull. Broadband neural signals are amplified, multiplexed, and continuously transmitted as TCP/IP data at a sustained rate of 24 Mbps. A Xilinx Spartan 6 FPGA assembles the digital signals into serial data frames for transmission at 20 kHz though an 802.11n wireless data link on a frequency-shift key-modulated signal at 5.7-5.8 GHz to a receiver up to 10 m away. The system is powered by two CR123A, 3 V batteries for 2 h of operation. We implanted a multi-electrode array in visual area V4 of one anesthetized monkey (Macaca fascicularis) and in the dorsolateral prefrontal cortex (dlPFC) of a freely moving monkey (Macaca mulatta). The implanted recording arrays were electrically stable and delivered broadband neural data over a year of testing. For the first time, we compared dlPFC neuronal responses to the same set of stimuli (food reward) in restrained and freely moving conditions. Although we did not find differences in neuronal responses as a function of reward type in the restrained and unrestrained conditions, there were significant differences in correlated activity. This demonstrates that measuring neural responses in freely moving animals can capture phenomena that are absent in the traditional head-fixed paradigm. We implemented a wireless neural interface for multi-electrode recordings in freely moving non-human primates, which can potentially move systems neuroscience to a new direction by allowing one to record neural signals while animals interact with their environment.

A wireless transmission neural interface system for unconstrained non-human primates

PubMed Central

Fernandez-Leon, Jose A.; Parajuli, Arun; Franklin, Robert; Sorenson, Michael; Felleman, Daniel J.; Hansen, Bryan J.; Hu, Ming; Dragoi, Valentin

2018-01-01

Objective Studying the brain in large animal models in a restrained laboratory rig severely limits our capacity to examine brain circuits in experimental and clinical applications. Approach To overcome these limitations, we developed a high-fidelity 96-channel wireless system to record extracellular spikes and local field potentials from neocortex. A removable, external case of the wireless device is attached to a titanium pedestal placed in the animal skull. Broadband neural signals are amplified, multiplexed, and continuously transmitted as TCP/IP data at a sustained rate of 24 Mbps. A Xilinx Spartan 6 FPGA assembles the digital signals into serial data frames for transmission at 20 kHz though an 802.11n wireless data link on a frequency shift key modulated signal at 5.7-5.8 GHz to a receiver up to 10 m away. The system is powered by two CR123A, 3-V batteries for 2 hours of operation. Main results We implanted a multi-electrode array in visual area V4 of one anesthetized monkey (Macaca fascicularis) and in the dorsolateral prefrontal cortex (dlPFC) of a freely moving monkey (Macaca mulatta). The implanted recording arrays were electrically stable and delivered broadband neural data over a year of testing. For the first time, we compared dlPFC neuronal responses to the same set of stimuli (food reward) in restrained and freely moving conditions. Although we did not find differences in neuronal responses as a function of reward type in the restrained and unrestrained conditions, there were significant differences in correlated activity. This demonstrates that measuring neural responses in freely-moving animals can capture phenomena that are absent in the traditional head-fixed paradigm. Significance We implemented a wireless neural interface for multi-electrode recordings in freely moving non-human primates which can potentially move systems neuroscience to a new direction by allowing to record neural signals while animals interact with their environment. PMID:26269496

Intra-day signal instabilities affect decoding performance in an intracortical neural interface system.

PubMed

Perge, János A; Homer, Mark L; Malik, Wasim Q; Cash, Sydney; Eskandar, Emad; Friehs, Gerhard; Donoghue, John P; Hochberg, Leigh R

2013-06-01

Motor neural interface systems (NIS) aim to convert neural signals into motor prosthetic or assistive device control, allowing people with paralysis to regain movement or control over their immediate environment. Effector or prosthetic control can degrade if the relationship between recorded neural signals and intended motor behavior changes. Therefore, characterizing both biological and technological sources of signal variability is important for a reliable NIS. To address the frequency and causes of neural signal variability in a spike-based NIS, we analyzed within-day fluctuations in spiking activity and action potential amplitude recorded with silicon microelectrode arrays implanted in the motor cortex of three people with tetraplegia (BrainGate pilot clinical trial, IDE). 84% of the recorded units showed a statistically significant change in apparent firing rate (3.8 ± 8.71 Hz or 49% of the mean rate) across several-minute epochs of tasks performed on a single session, and 74% of the units showed a significant change in spike amplitude (3.7 ± 6.5 µV or 5.5% of mean spike amplitude). 40% of the recording sessions showed a significant correlation in the occurrence of amplitude changes across electrodes, suggesting array micro-movement. Despite the relatively frequent amplitude changes, only 15% of the observed within-day rate changes originated from recording artifacts such as spike amplitude change or electrical noise, while 85% of the rate changes most likely emerged from physiological mechanisms. Computer simulations confirmed that systematic rate changes of individual neurons could produce a directional 'bias' in the decoded neural cursor movements. Instability in apparent neuronal spike rates indeed yielded a directional bias in 56% of all performance assessments in participant cursor control (n = 2 participants, 108 and 20 assessments over two years), resulting in suboptimal performance in these sessions. We anticipate that signal acquisition and decoding methods that can adapt to the reported instabilities will further improve the performance of intracortically-based NISs.

A wireless transmission neural interface system for unconstrained non-human primates

NASA Astrophysics Data System (ADS)

Fernandez-Leon, Jose A.; Parajuli, Arun; Franklin, Robert; Sorenson, Michael; Felleman, Daniel J.; Hansen, Bryan J.; Hu, Ming; Dragoi, Valentin

2015-10-01

Objective. Studying the brain in large animal models in a restrained laboratory rig severely limits our capacity to examine brain circuits in experimental and clinical applications. Approach. To overcome these limitations, we developed a high-fidelity 96-channel wireless system to record extracellular spikes and local field potentials from the neocortex. A removable, external case of the wireless device is attached to a titanium pedestal placed in the animal skull. Broadband neural signals are amplified, multiplexed, and continuously transmitted as TCP/IP data at a sustained rate of 24 Mbps. A Xilinx Spartan 6 FPGA assembles the digital signals into serial data frames for transmission at 20 kHz though an 802.11n wireless data link on a frequency-shift key-modulated signal at 5.7-5.8 GHz to a receiver up to 10 m away. The system is powered by two CR123A, 3 V batteries for 2 h of operation. Main results. We implanted a multi-electrode array in visual area V4 of one anesthetized monkey (Macaca fascicularis) and in the dorsolateral prefrontal cortex (dlPFC) of a freely moving monkey (Macaca mulatta). The implanted recording arrays were electrically stable and delivered broadband neural data over a year of testing. For the first time, we compared dlPFC neuronal responses to the same set of stimuli (food reward) in restrained and freely moving conditions. Although we did not find differences in neuronal responses as a function of reward type in the restrained and unrestrained conditions, there were significant differences in correlated activity. This demonstrates that measuring neural responses in freely moving animals can capture phenomena that are absent in the traditional head-fixed paradigm. Significance. We implemented a wireless neural interface for multi-electrode recordings in freely moving non-human primates, which can potentially move systems neuroscience to a new direction by allowing one to record neural signals while animals interact with their environment.

PyNCS: a microkernel for high-level definition and configuration of neuromorphic electronic systems

PubMed Central

Stefanini, Fabio; Neftci, Emre O.; Sheik, Sadique; Indiveri, Giacomo

2014-01-01

Neuromorphic hardware offers an electronic substrate for the realization of asynchronous event-based sensory-motor systems and large-scale spiking neural network architectures. In order to characterize these systems, configure them, and carry out modeling experiments, it is often necessary to interface them to workstations. The software used for this purpose typically consists of a large monolithic block of code which is highly specific to the hardware setup used. While this approach can lead to highly integrated hardware/software systems, it hampers the development of modular and reconfigurable infrastructures thus preventing a rapid evolution of such systems. To alleviate this problem, we propose PyNCS, an open-source front-end for the definition of neural network models that is interfaced to the hardware through a set of Python Application Programming Interfaces (APIs). The design of PyNCS promotes modularity, portability and expandability and separates implementation from hardware description. The high-level front-end that comes with PyNCS includes tools to define neural network models as well as to create, monitor and analyze spiking data. Here we report the design philosophy behind the PyNCS framework and describe its implementation. We demonstrate its functionality with two representative case studies, one using an event-based neuromorphic vision sensor, and one using a set of multi-neuron devices for carrying out a cognitive decision-making task involving state-dependent computation. PyNCS, already applicable to a wide range of existing spike-based neuromorphic setups, will accelerate the development of hybrid software/hardware neuromorphic systems, thanks to its code flexibility. The code is open-source and available online at https://github.com/inincs/pyNCS. PMID:25232314

PyNCS: a microkernel for high-level definition and configuration of neuromorphic electronic systems.

PubMed

Stefanini, Fabio; Neftci, Emre O; Sheik, Sadique; Indiveri, Giacomo

2014-01-01

Neuromorphic hardware offers an electronic substrate for the realization of asynchronous event-based sensory-motor systems and large-scale spiking neural network architectures. In order to characterize these systems, configure them, and carry out modeling experiments, it is often necessary to interface them to workstations. The software used for this purpose typically consists of a large monolithic block of code which is highly specific to the hardware setup used. While this approach can lead to highly integrated hardware/software systems, it hampers the development of modular and reconfigurable infrastructures thus preventing a rapid evolution of such systems. To alleviate this problem, we propose PyNCS, an open-source front-end for the definition of neural network models that is interfaced to the hardware through a set of Python Application Programming Interfaces (APIs). The design of PyNCS promotes modularity, portability and expandability and separates implementation from hardware description. The high-level front-end that comes with PyNCS includes tools to define neural network models as well as to create, monitor and analyze spiking data. Here we report the design philosophy behind the PyNCS framework and describe its implementation. We demonstrate its functionality with two representative case studies, one using an event-based neuromorphic vision sensor, and one using a set of multi-neuron devices for carrying out a cognitive decision-making task involving state-dependent computation. PyNCS, already applicable to a wide range of existing spike-based neuromorphic setups, will accelerate the development of hybrid software/hardware neuromorphic systems, thanks to its code flexibility. The code is open-source and available online at https://github.com/inincs/pyNCS.

A closed-loop compressive-sensing-based neural recording system.

PubMed

Zhang, Jie; Mitra, Srinjoy; Suo, Yuanming; Cheng, Andrew; Xiong, Tao; Michon, Frederic; Welkenhuysen, Marleen; Kloosterman, Fabian; Chin, Peter S; Hsiao, Steven; Tran, Trac D; Yazicioglu, Firat; Etienne-Cummings, Ralph

2015-06-01

This paper describes a low power closed-loop compressive sensing (CS) based neural recording system. This system provides an efficient method to reduce data transmission bandwidth for implantable neural recording devices. By doing so, this technique reduces a majority of system power consumption which is dissipated at data readout interface. The design of the system is scalable and is a viable option for large scale integration of electrodes or recording sites onto a single device. The entire system consists of an application-specific integrated circuit (ASIC) with 4 recording readout channels with CS circuits, a real time off-chip CS recovery block and a recovery quality evaluation block that provides a closed feedback to adaptively adjust compression rate. Since CS performance is strongly signal dependent, the ASIC has been tested in vivo and with standard public neural databases. Implemented using efficient digital circuit, this system is able to achieve >10 times data compression on the entire neural spike band (500-6KHz) while consuming only 0.83uW (0.53 V voltage supply) additional digital power per electrode. When only the spikes are desired, the system is able to further compress the detected spikes by around 16 times. Unlike other similar systems, the characteristic spikes and inter-spike data can both be recovered which guarantes a >95% spike classification success rate. The compression circuit occupied 0.11mm(2)/electrode in a 180nm CMOS process. The complete signal processing circuit consumes <16uW/electrode. Power and area efficiency demonstrated by the system make it an ideal candidate for integration into large recording arrays containing thousands of electrode. Closed-loop recording and reconstruction performance evaluation further improves the robustness of the compression method, thus making the system more practical for long term recording.

Electroactive SWNT/PEGDA hybrid hydrogel coating for bio-electrode interface.

PubMed

He, Lei; Lin, Demeng; Wang, Yanping; Xiao, Yinghong; Che, Jianfei

2011-10-15

Electric interface between neural tissue and electrode plays a significant role in the development of implanted devices for continuous monitoring and functional stimulation of central nervous system in terms of electroactivity, biocompatibility and long-term stability. To engineer an interface that possesses these merits, a polymeric hydrogel based on poly(ethylene glycol) diacrylate (PEGDA) and single-walled carbon nanotubes (SWNTs) were employed to fabricate a hybrid hydrogel via covalent anchoring strategy, i.e., self-assembly of cysteamine (Cys) followed by Michael addition between Cys and PEGDA. XPS characterization proves that the Cys molecules are linked to gold surface via the strong S-Au bond and that the PEGDA macromers are covalently bonded to Cys. FTIR spectra indicate the formation of hybrid hydrogel coating during photopolymerization. Electrochemical measurements using cyclic voltammetry (CV) and impedance spectrum clearly show the enhancement of electric properties to the hydrogel by the SWNTs. The charge transfer of the hybrid hydrogel-based electrode is quasi-reversible and charge transfer resistance decreases to the tenth of that of the pure hydrogel due to electron hopping along the SWNTs. Additionally, this hybrid hydrogel provides a favorable biomimetic microenvironment for cell attachment and growth due to its inherent biocompatibility. Combination of these merits yields hybrid hydrogels that can be good candidates for application to biosensors and biomedical devices. More importantly, the hybrid hydrogel coatings fabricated via the current strategy have good adhesion to the electrode substrate which is highly desired for chronically implantable devices. Copyright © 2011 Elsevier B.V. All rights reserved.

Toward more versatile and intuitive cortical brain machine interfaces

PubMed Central

Andersen, Richard A.; Kellis, Spencer; Klaes, Christian; Aflalo, Tyson

2015-01-01

Brain machine interfaces have great potential in neuroprosthetic applications to assist patients with brain injury and neurodegenerative diseases. One type of BMI is a cortical motor prosthetic which is used to assist paralyzed subjects. Motor prosthetics to date have typically used the motor cortex as a source of neural signals for controlling external devices. The review will focus on several new topics in the arena of cortical prosthetics. These include using 1) recordings from cortical areas outside motor cortex; 2) local field potentials (LFPs) as a source of recorded signals; 3) somatosensory feedback for more dexterous control of robotics; and 4) new decoding methods that work in concert to form an ecology of decode algorithms. These new advances hold promise in greatly accelerating the applicability and ease of operation of motor prosthetics. PMID:25247368

Reach and grasp by people with tetraplegia using a neurally controlled robotic arm

PubMed Central

Hochberg, Leigh R.; Bacher, Daniel; Jarosiewicz, Beata; Masse, Nicolas Y.; Simeral, John D.; Vogel, Joern; Haddadin, Sami; Liu, Jie; Cash, Sydney S.; van der Smagt, Patrick; Donoghue, John P.

2012-01-01

Paralysis following spinal cord injury (SCI), brainstem stroke, amyotrophic lateral sclerosis (ALS) and other disorders can disconnect the brain from the body, eliminating the ability to carry out volitional movements. A neural interface system (NIS)1–5 could restore mobility and independence for people with paralysis by translating neuronal activity directly into control signals for assistive devices. We have previously shown that people with longstanding tetraplegia can use an NIS to move and click a computer cursor and to control physical devices6–8. Able-bodied monkeys have used an NIS to control a robotic arm9, but it is unknown whether people with profound upper extremity paralysis or limb loss could use cortical neuronal ensemble signals to direct useful arm actions. Here, we demonstrate the ability of two people with long-standing tetraplegia to use NIS-based control of a robotic arm to perform three-dimensional reach and grasp movements. Participants controlled the arm over a broad space without explicit training, using signals decoded from a small, local population of motor cortex (MI) neurons recorded from a 96-channel microelectrode array. One of the study participants, implanted with the sensor five years earlier, also used a robotic arm to drink coffee from a bottle. While robotic reach and grasp actions were not as fast or accurate as those of an able-bodied person, our results demonstrate the feasibility for people with tetraplegia, years after CNS injury, to recreate useful multidimensional control of complex devices directly from a small sample of neural signals. PMID:22596161

Neurosecurity: security and privacy for neural devices.

PubMed

Denning, Tamara; Matsuoka, Yoky; Kohno, Tadayoshi

2009-07-01

An increasing number of neural implantable devices will become available in the near future due to advances in neural engineering. This discipline holds the potential to improve many patients' lives dramatically by offering improved-and in some cases entirely new-forms of rehabilitation for conditions ranging from missing limbs to degenerative cognitive diseases. The use of standard engineering practices, medical trials, and neuroethical evaluations during the design process can create systems that are safe and that follow ethical guidelines; unfortunately, none of these disciplines currently ensure that neural devices are robust against adversarial entities trying to exploit these devices to alter, block, or eavesdrop on neural signals. The authors define "neurosecurity"-a version of computer science security principles and methods applied to neural engineering-and discuss why neurosecurity should be a critical consideration in the design of future neural devices.

Organic electronics for high-resolution electrocorticography of the human brain.

PubMed

Khodagholy, Dion; Gelinas, Jennifer N; Zhao, Zifang; Yeh, Malcolm; Long, Michael; Greenlee, Jeremy D; Doyle, Werner; Devinsky, Orrin; Buzsáki, György

2016-11-01

Localizing neuronal patterns that generate pathological brain signals may assist with tissue resection and intervention strategies in patients with neurological diseases. Precise localization requires high spatiotemporal recording from populations of neurons while minimizing invasiveness and adverse events. We describe a large-scale, high-density, organic material-based, conformable neural interface device ("NeuroGrid") capable of simultaneously recording local field potentials (LFPs) and action potentials from the cortical surface. We demonstrate the feasibility and safety of intraoperative recording with NeuroGrids in anesthetized and awake subjects. Highly localized and propagating physiological and pathological LFP patterns were recorded, and correlated neural firing provided evidence about their local generation. Application of NeuroGrids to brain disorders, such as epilepsy, may improve diagnostic precision and therapeutic outcomes while reducing complications associated with invasive electrodes conventionally used to acquire high-resolution and spiking data.

Fast attainment of computer cursor control with noninvasively acquired brain signals

NASA Astrophysics Data System (ADS)

Bradberry, Trent J.; Gentili, Rodolphe J.; Contreras-Vidal, José L.

2011-06-01

Brain-computer interface (BCI) systems are allowing humans and non-human primates to drive prosthetic devices such as computer cursors and artificial arms with just their thoughts. Invasive BCI systems acquire neural signals with intracranial or subdural electrodes, while noninvasive BCI systems typically acquire neural signals with scalp electroencephalography (EEG). Some drawbacks of invasive BCI systems are the inherent risks of surgery and gradual degradation of signal integrity. A limitation of noninvasive BCI systems for two-dimensional control of a cursor, in particular those based on sensorimotor rhythms, is the lengthy training time required by users to achieve satisfactory performance. Here we describe a novel approach to continuously decoding imagined movements from EEG signals in a BCI experiment with reduced training time. We demonstrate that, using our noninvasive BCI system and observational learning, subjects were able to accomplish two-dimensional control of a cursor with performance levels comparable to those of invasive BCI systems. Compared to other studies of noninvasive BCI systems, training time was substantially reduced, requiring only a single session of decoder calibration (~20 min) and subject practice (~20 min). In addition, we used standardized low-resolution brain electromagnetic tomography to reveal that the neural sources that encoded observed cursor movement may implicate a human mirror neuron system. These findings offer the potential to continuously control complex devices such as robotic arms with one's mind without lengthy training or surgery.

Progress towards biocompatible intracortical microelectrodes for neural interfacing applications

NASA Astrophysics Data System (ADS)

Jorfi, Mehdi; Skousen, John L.; Weder, Christoph; Capadona, Jeffrey R.

2015-02-01

To ensure long-term consistent neural recordings, next-generation intracortical microelectrodes are being developed with an increased emphasis on reducing the neuro-inflammatory response. The increased emphasis stems from the improved understanding of the multifaceted role that inflammation may play in disrupting both biologic and abiologic components of the overall neural interface circuit. To combat neuro-inflammation and improve recording quality, the field is actively progressing from traditional inorganic materials towards approaches that either minimizes the microelectrode footprint or that incorporate compliant materials, bioactive molecules, conducting polymers or nanomaterials. However, the immune-privileged cortical tissue introduces an added complexity compared to other biomedical applications that remains to be fully understood. This review provides a comprehensive reflection on the current understanding of the key failure modes that may impact intracortical microelectrode performance. In addition, a detailed overview of the current status of various materials-based approaches that have gained interest for neural interfacing applications is presented, and key challenges that remain to be overcome are discussed. Finally, we present our vision on the future directions of materials-based treatments to improve intracortical microelectrodes for neural interfacing.

Progress Towards Biocompatible Intracortical Microelectrodes for Neural Interfacing Applications

PubMed Central

Jorfi, Mehdi; Skousen, John L.; Weder, Christoph; Capadona, Jeffrey R.

2015-01-01

To ensure long-term consistent neural recordings, next-generation intracortical microelectrodes are being developed with an increased emphasis on reducing the neuro-inflammatory response. The increased emphasis stems from the improved understanding of the multifaceted role that inflammation may play in disrupting both biologic and abiologic components of the overall neural interface circuit. To combat neuro-inflammation and improve recording quality, the field is actively progressing from traditional inorganic materials towards approaches that either minimizes the microelectrode footprint or that incorporate compliant materials, bioactive molecules, conducting polymers or nanomaterials. However, the immune-privileged cortical tissue introduces an added complexity compared to other biomedical applications that remains to be fully understood. This review provides a comprehensive reflection on the current understanding of the key failure modes that may impact intracortical microelectrode performance. In addition, a detailed overview of the current status of various materials-based approaches that have gained interest for neural interfacing applications is presented, and key challenges that remain to be overcome are discussed. Finally, we present our vision on the future directions of materials-based treatments to improve intracortical microelectrodes for neural interfacing. PMID:25460808

A simple miniature device for wireless stimulation of neural circuits in small behaving animals.

PubMed

Zhang, Yisi; Langford, Bruce; Kozhevnikov, Alexay

2011-10-30

The use of wireless neural stimulation devices offers significant advantages for neural stimulation experiments in behaving animals. We demonstrate a simple, low-cost and extremely lightweight wireless neural stimulation device which is made from off-the-shelf components. The device has low power consumption and does not require a high-power RF preamplifier. Neural stimulation can be carried out in either a voltage source mode or a current source mode. Using the device, we carry out wireless stimulation in the premotor brain area HVC of a songbird and demonstrate that such stimulation causes rapid perturbations of the acoustic structure of the song. Published by Elsevier B.V.

Progress in neuromorphic photonics

NASA Astrophysics Data System (ADS)

Ferreira de Lima, Thomas; Shastri, Bhavin J.; Tait, Alexander N.; Nahmias, Mitchell A.; Prucnal, Paul R.

2017-03-01

As society's appetite for information continues to grow, so does our need to process this information with increasing speed and versatility. Many believe that the one-size-fits-all solution of digital electronics is becoming a limiting factor in certain areas such as data links, cognitive radio, and ultrafast control. Analog photonic devices have found relatively simple signal processing niches where electronics can no longer provide sufficient speed and reconfigurability. Recently, the landscape for commercially manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. By bridging the mathematical prowess of artificial neural networks to the underlying physics of optoelectronic devices, neuromorphic photonics could breach new domains of information processing demanding significant complexity, low cost, and unmatched speed. In this article, we review the progress in neuromorphic photonics, focusing on photonic integrated devices. The challenges and design rules for optoelectronic instantiation of artificial neurons are presented. The proposed photonic architecture revolves around the processing network node composed of two parts: a nonlinear element and a network interface. We then survey excitable lasers in the recent literature as candidates for the nonlinear node and microring-resonator weight banks as the network interface. Finally, we compare metrics between neuromorphic electronics and neuromorphic photonics and discuss potential applications.

Visual communication interface for severe physically disabled patients

NASA Astrophysics Data System (ADS)

Savino, M. J.; Fernández, E. A.

2007-11-01

During the last years several interfaces have been developed to allow communication to those patients suffering serious physical disabilities. In this work, a computer based communication interface is presented. It was designed to allow communication to those patients that cannot use neither their hands nor their voice but they can do it through their eyes. The system monitors the eyes movements by means of a webcam. Then, by means of an Artificial Neural Network, the system allows the identification of specified position on the screen through the identification of the eyes positions. This way the user can control a virtual keyboard on a screen that allows him to write and browse the system and enables him to send e-mails, SMS, activate video/music programs and control environmental devices. A patient was simulated to evaluate the versatility of the system. Its operation was satisfactory and it allowed the evaluation of the system potential. The development of this system requires low cost elements that are easily found in the market.

EDITORIAL: Why we need a new journal in neural engineering

NASA Astrophysics Data System (ADS)

Durand, Dominique M.

2004-03-01

The field of neural engineering crystallizes for many engineers and scientists an area of research at the interface between neuroscience and engineering. For the last 15 years or so, the discipline of neural engineering (neuroengineering) has slowly appeared at conferences as a theme or track. The first conference devoted entirely to this area was the 1st International IEEE EMBS Conference on Neural Engineering which took place in Capri, Italy in 2003. Understanding how the brain works is considered the ultimate frontier and challenge in science. The complexity of the brain is so great that understanding even the most basic functions will require that we fully exploit all the tools currently at our disposal in science and engineering and simultaneously develop new methods of analysis. While neuroscientists and engineers from varied fields such as brain anatomy, neural development and electrophysiology have made great strides in the analysis of this complex organ, there remains a great deal yet to be uncovered. The potential for applications and remedies deriving from scientific discoveries and breakthroughs is extremely high. As a result of the growing availability of micromachining technology, research into neurotechnology has grown relatively rapidly in recent years and appears to be approaching a critical mass. For example, by understanding how neuronal circuits process and store information, we could design computers with capabilities beyond current limits. By understanding how neurons develop and grow, we could develop new technologies for spinal cord repair or central nervous system repair following neurological disorders. Moreover, discoveries related to higher-level cognitive function and consciousness could have a profound influence on how humans make sense of their surroundings and interact with each other. The ability to successfully interface the brain with external electronics would have enormous implications for our society and facilitate a revolutionary change in the quality of life of persons with sensory and/or motor deficits. Microelectrode technology represents the initial step towards this goal and has already improved the quality of life of many patients, as is evident from the success of auditory prostheses. The cost to society of neurological disorders such as stroke, Parkinson's disease, Alzheimer's disease and epilepsy is staggering. Stroke, which is the third leading cause of death in North America, runs up costs of 40 billion to society per year for its treatment. Costs associated with brain disorders are estimated at 285 billion. Breakthroughs in this field will have a significant impact on the market for enabling technologies. The market for neurological medical devices totaled 2 billion in 1999 and is projected to grow at a rate of 20 to 30% in the next ten years, far outpacing the market for cardiac devices. Although we have all recognized the importance of interdisciplinary research (see the NIH Road map at http://nihroadmap.nih.gov/), the fields of neuroscience and engineering have remained compartmentalized. Collaboration is still difficult since the language of these disciplines is different. Moreover, the scientific journals in these fields are also clearly separate. Researchers involved in neural engineering have a choice of publishing their research in either neuroscience-oriented journals such as Journal of Neuroscience, Journal of Neurophysiology and Brain Research or in engineering journals such as IEEE Transactions on Biomedical Engineering, IEEE Transactions on Neural Systems and Rehabilitation and Annals of Biomedical Engineering. There is no journal currently available focusing on the interdisciplinary field of neural engineering. In order to capitalize on the potential of neural engineering to investigate neural function and to solve problems related to neural disorders, it is necessary to break down the traditional barriers between neuroscientists and engineers not just in the laboratory but also in the publication of scientific papers. We do, therefore, need a new journal that provides a platform for this emerging interdisciplinary field of neural engineering where neuroscientists, neurobiologists and engineers can publish their work in one periodical that spans the disciplines. Journal of Neural Engineering will provide this platform. The new journal will publish full-length articles of the highest quality and importance in the field of neural engineering at the molecular, cellular and systems levels. The scope of Journal of Neural Engineering encompasses experimental, computational and theoretical aspects of neural interfacing, neuroelectronics, neuromechanical systems, neuroinformatics, neuroimaging, neural prostheses, artificial and biological neural circuits, neural control, neural tissue regeneration, neural signal processing, neural modeling and neuro-computation. The scope of the journal has both depth and breadth in areas relevant to the interface between neuroscience and engineering. There will be two Editors-in-Chief, with expertise covering both engineering and neuroscience. Experts in the areas encompassed by the journal's scope have been identified for the Editorial Board and the composition of the board will be continually updated to address the developments in this new and exciting field. The first issue of this new journal covers a variety of topics that combine neuroscience and engineering: mental state recognition from EEG signals, analysis of body motion in Parkinson's patients, non-linear dynamics of the respiratory system, automatic identification of saccade-related visual evoked potentials, multiple electrode stimulators, algorithms to estimate the causal relationship between brain sources, diffusion tensor imaging in the brain and phase synchronization of neural activity in vitro. This broad array of manuscripts focusing on neural imaging, neurophysiology, neural signal processing, neuroelectronics and neuro-dynamics can be found for the first time within the pages of a single journal: Journal of Neural Engineering. I am grateful to Institute of Physics Publishing and Jane Roscoe in particular for putting together this new journal to accommodate the fast-growing field of neural engineering. I am also grateful to Andrew Schwartz who has agreed to be the co-Editor-in-Chief for the journal.

Intention Concepts and Brain-Machine Interfacing

PubMed Central

Thinnes-Elker, Franziska; Iljina, Olga; Apostolides, John Kyle; Kraemer, Felicitas; Schulze-Bonhage, Andreas; Aertsen, Ad; Ball, Tonio

2012-01-01

Intentions, including their temporal properties and semantic content, are receiving increased attention, and neuroscientific studies in humans vary with respect to the topography of intention-related neural responses. This may reflect the fact that the kind of intentions investigated in one study may not be exactly the same kind investigated in the other. Fine-grained intention taxonomies developed in the philosophy of mind may be useful to identify the neural correlates of well-defined types of intentions, as well as to disentangle them from other related mental states, such as mere urges to perform an action. Intention-related neural signals may be exploited by brain-machine interfaces (BMIs) that are currently being developed to restore speech and motor control in paralyzed patients. Such BMI devices record the brain activity of the agent, interpret (“decode”) the agent’s intended action, and send the corresponding execution command to an artificial effector system, e.g., a computer cursor or a robotic arm. In the present paper, we evaluate the potential of intention concepts from philosophy of mind to improve the performance and safety of BMIs based on higher-order, intention-related control signals. To this end, we address the distinction between future-, present-directed, and motor intentions, as well as the organization of intentions in time, specifically to what extent it is sequential or hierarchical. This has consequences as to whether these different types of intentions can be expected to occur simultaneously or not. We further illustrate how it may be useful or even necessary to distinguish types of intentions exposited in philosophy, including yes- vs. no-intentions and oblique vs. direct intentions, to accurately decode the agent’s intentions from neural signals in practical BMI applications. PMID:23162504

3D hybrid electrode structure as implantable interface for a vestibular neural prosthesis in humans.

PubMed

Hoffmann, Klaus-P; Poppendieck, Wigand; Tätzner, Simon; DiGiovanna, Jack; Kos, Maria Izabel; Guinand, Nils; Guyot, Jean-P; Micera, Silvestro

2011-01-01

Implantable interfaces are essential components of vestibular neural prostheses. They interface the biological system with electrical stimulation that is used to restore transfer of vestibular information. Regarding the anatomical situation special 3D structures are required. In this paper, the design and the manufacturing process of a novel 3D hybrid microelectrode structure as interface to the human vestibular system are described. Photolithography techniques, assembling technology and rapid prototyping are used for manufacturing.

Single-trial dynamics of motor cortex and their applications to brain-machine interfaces

PubMed Central

Kao, Jonathan C.; Nuyujukian, Paul; Ryu, Stephen I.; Churchland, Mark M.; Cunningham, John P.; Shenoy, Krishna V.

2015-01-01

Increasing evidence suggests that neural population responses have their own internal drive, or dynamics, that describe how the neural population evolves through time. An important prediction of neural dynamical models is that previously observed neural activity is informative of noisy yet-to-be-observed activity on single-trials, and may thus have a denoising effect. To investigate this prediction, we built and characterized dynamical models of single-trial motor cortical activity. We find these models capture salient dynamical features of the neural population and are informative of future neural activity on single trials. To assess how neural dynamics may beneficially denoise single-trial neural activity, we incorporate neural dynamics into a brain–machine interface (BMI). In online experiments, we find that a neural dynamical BMI achieves substantially higher performance than its non-dynamical counterpart. These results provide evidence that neural dynamics beneficially inform the temporal evolution of neural activity on single trials and may directly impact the performance of BMIs. PMID:26220660

Photochemically modified diamond-like carbon surfaces for neural interfaces.

PubMed

Hopper, A P; Dugan, J M; Gill, A A; Regan, E M; Haycock, J W; Kelly, S; May, P W; Claeyssens, F

2016-01-01

Diamond-like carbon (DLC) was modified using a UV functionalization method to introduce surface-bound amine and aldehyde groups. The functionalization process rendered the DLC more hydrophilic and significantly increased the viability of neurons seeded to the surface. The amine functionalized DLC promoted adhesion of neurons and fostered neurite outgrowth to a degree indistinguishable from positive control substrates (glass coated with poly-L-lysine). The aldehyde-functionalized surfaces performed comparably to the amine functionalized surfaces and both additionally supported the adhesion and growth of primary rat Schwann cells. DLC has many properties that are desirable in biomaterials. With the UV functionalization method demonstrated here it may be possible to harness these properties for the development of implantable devices to interface with the nervous system. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Causal network in a deafferented non-human primate brain.

PubMed

Balasubramanian, Karthikeyan; Takahashi, Kazutaka; Hatsopoulos, Nicholas G

2015-01-01

De-afferented/efferented neural ensembles can undergo causal changes when interfaced to neuroprosthetic devices. These changes occur via recruitment or isolation of neurons, alterations in functional connectivity within the ensemble and/or changes in the role of neurons, i.e., excitatory/inhibitory. In this work, emergence of a causal network and changes in the dynamics are demonstrated for a deafferented brain region exposed to BMI (brain-machine interface) learning. The BMI was controlling a robot for reach-and-grasp behavior. And, the motor cortical regions used for the BMI were deafferented due to chronic amputation, and ensembles of neurons were decoded for velocity control of the multi-DOF robot. A generalized linear model-framework based Granger causality (GLM-GC) technique was used in estimating the ensemble connectivity. Model selection was based on the AIC (Akaike Information Criterion).

Interfacing Graphene-Based Materials With Neural Cells

PubMed Central

Bramini, Mattia; Alberini, Giulio; Colombo, Elisabetta; Chiacchiaretta, Martina; DiFrancesco, Mattia L.; Maya-Vetencourt, José F.; Maragliano, Luca; Benfenati, Fabio; Cesca, Fabrizia

2018-01-01

The scientific community has witnessed an exponential increase in the applications of graphene and graphene-based materials in a wide range of fields, from engineering to electronics to biotechnologies and biomedical applications. For what concerns neuroscience, the interest raised by these materials is two-fold. On one side, nanosheets made of graphene or graphene derivatives (graphene oxide, or its reduced form) can be used as carriers for drug delivery. Here, an important aspect is to evaluate their toxicity, which strongly depends on flake composition, chemical functionalization and dimensions. On the other side, graphene can be exploited as a substrate for tissue engineering. In this case, conductivity is probably the most relevant amongst the various properties of the different graphene materials, as it may allow to instruct and interrogate neural networks, as well as to drive neural growth and differentiation, which holds a great potential in regenerative medicine. In this review, we try to give a comprehensive view of the accomplishments and new challenges of the field, as well as which in our view are the most exciting directions to take in the immediate future. These include the need to engineer multifunctional nanoparticles (NPs) able to cross the blood-brain-barrier to reach neural cells, and to achieve on-demand delivery of specific drugs. We describe the state-of-the-art in the use of graphene materials to engineer three-dimensional scaffolds to drive neuronal growth and regeneration in vivo, and the possibility of using graphene as a component of hybrid composites/multi-layer organic electronics devices. Last but not least, we address the need of an accurate theoretical modeling of the interface between graphene and biological material, by modeling the interaction of graphene with proteins and cell membranes at the nanoscale, and describing the physical mechanism(s) of charge transfer by which the various graphene materials can influence the excitability and physiology of neural cells. PMID:29695956

Neuromorphic neural interfaces: from neurophysiological inspiration to biohybrid coupling with nervous systems

NASA Astrophysics Data System (ADS)

Broccard, Frédéric D.; Joshi, Siddharth; Wang, Jun; Cauwenberghs, Gert

2017-08-01

Objective. Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use of physical resources such as time, space and energy. In an effort to better understand neural computation on a physical medium with similar spatiotemporal and energetic constraints, the field of neuromorphic engineering aims to design and implement electronic systems that emulate in very large-scale integration (VLSI) hardware the organization and functions of neural systems at multiple levels of biological organization, from individual neurons up to large circuits and networks. Mixed analog/digital neuromorphic VLSI systems are compact, consume little power and operate in real time independently of the size and complexity of the model. Approach. This article highlights the current efforts to interface neuromorphic systems with neural systems at multiple levels of biological organization, from the synaptic to the system level, and discusses the prospects for future biohybrid systems with neuromorphic circuits of greater complexity. Main results. Single silicon neurons have been interfaced successfully with invertebrate and vertebrate neural networks. This approach allowed the investigation of neural properties that are inaccessible with traditional techniques while providing a realistic biological context not achievable with traditional numerical modeling methods. At the network level, populations of neurons are envisioned to communicate bidirectionally with neuromorphic processors of hundreds or thousands of silicon neurons. Recent work on brain-machine interfaces suggests that this is feasible with current neuromorphic technology. Significance. Biohybrid interfaces between biological neurons and VLSI neuromorphic systems of varying complexity have started to emerge in the literature. Primarily intended as a computational tool for investigating fundamental questions related to neural dynamics, the sophistication of current neuromorphic systems now allows direct interfaces with large neuronal networks and circuits, resulting in potentially interesting clinical applications for neuroengineering systems, neuroprosthetics and neurorehabilitation.

The Promise of Neurotechnology in Clinical Translational Science.

PubMed

White, Susan W; Richey, John A; Gracanin, Denis; Bell, Martha Ann; LaConte, Stephen; Coffman, Marika; Trubanova, Andrea; Kim, Inyoung

2015-09-01

Neurotechnology is broadly defined as a set of devices used to understand neural processes and applications that can potentially facilitate the brain's ability to repair itself. In the past decade, an increasingly explicit understanding of basic biological mechanisms of brain-related illnesses has produced applications that allow a direct yet noninvasive method to index and manipulate the functioning of the human nervous system. Clinical scientists are poised to apply this technology to assess, treat, and better understand complex socioemotional processes that underlie many forms of psychopathology. In this review, we describe the potential benefits and hurdles, both technical and methodological, of neurotechnology in the context of clinical dysfunction. We also offer a framework for developing and evaluating neurotechnologies that is intended to expedite progress at the nexus of clinical science and neural interface designs by providing a comprehensive vocabulary to describe the necessary features of neurotechnology in the clinic.

The Promise of Neurotechnology in Clinical Translational Science

PubMed Central

White, Susan W.; Richey, John A.; Gracanin, Denis; Bell, Martha Ann; LaConte, Stephen; Coffman, Marika; Trubanova, Andrea; Kim, Inyoung

2014-01-01

Neurotechnology is broadly defined as a set of devices used to understand neural processes and applications that can potentially facilitate the brain’s ability to repair itself. In the past decade, an increasingly explicit understanding of basic biological mechanisms of brain-related illnesses has produced applications that allow a direct yet noninvasive method to index and manipulate the functioning of the human nervous system. Clinical scientists are poised to apply this technology to assess, treat, and better understand complex socioemotional processes that underlie many forms of psychopathology. In this review, we describe the potential benefits and hurdles, both technical and methodological, of neurotechnology in the context of clinical dysfunction. We also offer a framework for developing and evaluating neurotechnologies that is intended to expedite progress at the nexus of clinical science and neural interface designs by providing a comprehensive vocabulary to describe the necessary features of neurotechnology in the clinic. PMID:26504676

Quantification of human upper extremity nerves and fascicular anatomy.

PubMed

Brill, Natalie A; Tyler, Dustin J

2017-09-01

In this study we provide detailed quantification of upper extremity nerve and fascicular anatomy. The purpose is to provide values and trends in neural features useful for clinical applications and neural interface device design. Nerve cross-sections were taken from 4 ulnar, 4 median, and 3 radial nerves from 5 arms of 3 human cadavers. Quantified nerve features included cross-sectional area, minor diameter, and major diameter. Fascicular features analyzed included count, perimeter, area, and position. Mean fascicular diameters were 0.57 ± 0.39, 0.6 ± 0.3, 0.5 ± 0.26 mm in the upper arm and 0.38 ± 0.18, 0.47 ± 0.18, 0.4 ± 0.27 mm in the forearm of ulnar, median, and radial nerves, respectively. Mean fascicular diameters were inversely proportional to fascicle count. Detailed quantitative anatomy of upper extremity nerves is a resource for design of neural electrodes, guidance in extraneural procedures, and improved neurosurgical planning. Muscle Nerve 56: 463-471, 2017. © 2016 Wiley Periodicals, Inc.

Chronic recording of regenerating VIIIth nerve axons with a sieve electrode

NASA Technical Reports Server (NTRS)

Mensinger, A. F.; Anderson, D. J.; Buchko, C. J.; Johnson, M. A.; Martin, D. C.; Tresco, P. A.; Silver, R. B.; Highstein, S. M.

2000-01-01

A micromachined silicon substrate sieve electrode was implanted within transected toadfish (Opsanus tau) otolith nerves. High fidelity, single unit neural activity was recorded from seven alert and unrestrained fish 30 to 60 days after implantation. Fibrous coatings of genetically engineered bioactive protein polymers and nerve guide tubes increased the number of axons regenerating through the electrode pores when compared with controls. Sieve electrodes have potential as permanent interfaces to the nervous system and to bridge missing connections between severed or damaged nerves and muscles. Recorded impulses might also be amplified and used to control prosthetic devices.

Three-Dimensional Flexible Electronics Enabled by Shape Memory Polymer Substrates for Responsive Neural Interfaces.

PubMed

Ware, Taylor; Simon, Dustin; Hearon, Keith; Liu, Clive; Shah, Sagar; Reeder, Jonathan; Khodaparast, Navid; Kilgard, Michael P; Maitland, Duncan J; Rennaker, Robert L; Voit, Walter E

2012-12-01

Planar electronics processing methods have enabled neural interfaces to become more precise and deliver more information. However, this processing paradigm is inherently 2D and rigid. The resulting mechanical and geometrical mismatch at the biotic-abiotic interface can elicit an immune response that prevents effective stimulation. In this work, a thiol-ene/acrylate shape memory polymer is utilized to create 3D softening substrates for stimulation electrodes. This substrate system is shown to soften in vivo from more than 600 to 6 MPa. A nerve cuff electrode that coils around the vagus nerve in a rat and that drives neural activity is demonstrated.

Modulation Depth Estimation and Variable Selection in State-Space Models for Neural Interfaces

PubMed Central

Hochberg, Leigh R.; Donoghue, John P.; Brown, Emery N.

2015-01-01

Rapid developments in neural interface technology are making it possible to record increasingly large signal sets of neural activity. Various factors such as asymmetrical information distribution and across-channel redundancy may, however, limit the benefit of high-dimensional signal sets, and the increased computational complexity may not yield corresponding improvement in system performance. High-dimensional system models may also lead to overfitting and lack of generalizability. To address these issues, we present a generalized modulation depth measure using the state-space framework that quantifies the tuning of a neural signal channel to relevant behavioral covariates. For a dynamical system, we develop computationally efficient procedures for estimating modulation depth from multivariate data. We show that this measure can be used to rank neural signals and select an optimal channel subset for inclusion in the neural decoding algorithm. We present a scheme for choosing the optimal subset based on model order selection criteria. We apply this method to neuronal ensemble spike-rate decoding in neural interfaces, using our framework to relate motor cortical activity with intended movement kinematics. With offline analysis of intracortical motor imagery data obtained from individuals with tetraplegia using the BrainGate neural interface, we demonstrate that our variable selection scheme is useful for identifying and ranking the most information-rich neural signals. We demonstrate that our approach offers several orders of magnitude lower complexity but virtually identical decoding performance compared to greedy search and other selection schemes. Our statistical analysis shows that the modulation depth of human motor cortical single-unit signals is well characterized by the generalized Pareto distribution. Our variable selection scheme has wide applicability in problems involving multisensor signal modeling and estimation in biomedical engineering systems. PMID:25265627

Optimizing growth and post treatment of diamond for high capacitance neural interfaces.

PubMed

Tong, Wei; Fox, Kate; Zamani, Akram; Turnley, Ann M; Ganesan, Kumaravelu; Ahnood, Arman; Cicione, Rosemary; Meffin, Hamish; Prawer, Steven; Stacey, Alastair; Garrett, David J

2016-10-01

Electrochemical and biological properties are two crucial criteria in the selection of the materials to be used as electrodes for neural interfaces. For neural stimulation, materials are required to exhibit high capacitance and to form intimate contact with neurons for eliciting effective neural responses at acceptably low voltages. Here we report on a new high capacitance material fabricated using nitrogen included ultrananocrystalline diamond (N-UNCD). After exposure to oxygen plasma for 3 h, the activated N-UNCD exhibited extremely high electrochemical capacitance greater than 1 mF/cm(2), which originates from the special hybrid sp(2)/sp(3) structure of N-UNCD. The in vitro biocompatibility of the activated N-UNCD was then assessed using rat cortical neurons and surface roughness was found to be critical for healthy neuron growth, with best results observed on surfaces with a roughness of approximately 20 nm. Therefore, by using oxygen plasma activated N-UNCD with appropriate surface roughness, and considering the chemical and mechanical stability of diamond, the fabricated neural interfaces are expected to exhibit high efficacy, long-term stability and a healthy neuron/electrode interface. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predicate calculus for an architecture of multiple neural networks

NASA Astrophysics Data System (ADS)

Consoli, Robert H.

1990-08-01

Future projects with neural networks will require multiple individual network components. Current efforts along these lines are ad hoc. This paper relates the neural network to a classical device and derives a multi-part architecture from that model. Further it provides a Predicate Calculus variant for describing the location and nature of the trainings and suggests Resolution Refutation as a method for determining the performance of the system as well as the location of needed trainings for specific proofs. 2. THE NEURAL NETWORK AND A CLASSICAL DEVICE Recently investigators have been making reports about architectures of multiple neural networksL234. These efforts are appearing at an early stage in neural network investigations they are characterized by architectures suggested directly by the problem space. Touretzky and Hinton suggest an architecture for processing logical statements1 the design of this architecture arises from the syntax of a restricted class of logical expressions and exhibits syntactic limitations. In similar fashion a multiple neural netword arises out of a control problem2 from the sequence learning problem3 and from the domain of machine learning. 4 But a general theory of multiple neural devices is missing. More general attempts to relate single or multiple neural networks to classical computing devices are not common although an attempt is made to relate single neural devices to a Turing machines and Sun et a!. develop a multiple neural architecture that performs pattern classification.

Inversion of Density Interfaces Using the Pseudo-Backpropagation Neural Network Method

NASA Astrophysics Data System (ADS)

Chen, Xiaohong; Du, Yukun; Liu, Zhan; Zhao, Wenju; Chen, Xiaocheng

2018-05-01

This paper presents a new pseudo-backpropagation (BP) neural network method that can invert multi-density interfaces at one time. The new method is based on the conventional forward modeling and inverse modeling theories in addition to conventional pseudo-BP neural network arithmetic. A 3D inversion model for gravity anomalies of multi-density interfaces using the pseudo-BP neural network method is constructed after analyzing the structure and function of the artificial neural network. The corresponding iterative inverse formula of the space field is presented at the same time. Based on trials of gravity anomalies and density noise, the influence of the two kinds of noise on the inverse result is discussed and the scale of noise requested for the stability of the arithmetic is analyzed. The effects of the initial model on the reduction of the ambiguity of the result and improvement of the precision of inversion are discussed. The correctness and validity of the method were verified by the 3D model of the three interfaces. 3D inversion was performed on the observed gravity anomaly data of the Okinawa trough using the program presented herein. The Tertiary basement and Moho depth were obtained from the inversion results, which also testify the adaptability of the method. This study has made a useful attempt for the inversion of gravity density interfaces.

Parsing learning in networks using brain-machine interfaces.

PubMed

Orsborn, Amy L; Pesaran, Bijan

2017-10-01

Brain-machine interfaces (BMIs) define new ways to interact with our environment and hold great promise for clinical therapies. Motor BMIs, for instance, re-route neural activity to control movements of a new effector and could restore movement to people with paralysis. Increasing experience shows that interfacing with the brain inevitably changes the brain. BMIs engage and depend on a wide array of innate learning mechanisms to produce meaningful behavior. BMIs precisely define the information streams into and out of the brain, but engage wide-spread learning. We take a network perspective and review existing observations of learning in motor BMIs to show that BMIs engage multiple learning mechanisms distributed across neural networks. Recent studies demonstrate the advantages of BMI for parsing this learning and its underlying neural mechanisms. BMIs therefore provide a powerful tool for studying the neural mechanisms of learning that highlights the critical role of learning in engineered neural therapies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Intra-day signal instabilities affect decoding performance in an intracortical neural interface system

PubMed Central

Perge, János A.; Homer, Mark L.; Malik, Wasim Q.; Cash, Sydney; Eskandar, Emad; Friehs, Gerhard; Donoghue, John P.; Hochberg, Leigh R.

2013-01-01

Objective Motor Neural Interface Systems (NIS) aim to convert neural signals into motor prosthetic or assistive device control, allowing people with paralysis to regain movement or control over their immediate environment. Effector or prosthetic control can degrade if the relationship between recorded neural signals and intended motor behavior changes. Therefore, characterizing both biological and technological sources of signal variability is important for a reliable NIS. Approach To address the frequency and causes of neural signal variability in a spike-based NIS, we analyzed within-day fluctuations in spiking activity and action potential amplitude recorded with silicon microelectrode arrays implanted in the motor cortex of three people with tetraplegia (BrainGate pilot clinical trial, IDE). Main results Eighty-four percent of the recorded units showed a statistically significant change in apparent firing rate (3.8±8.71Hz or 49% of the mean rate) across several-minute epochs of tasks performed on a single session, and seventy-four percent of the units showed a significant change in spike amplitude (3.7±6.5μV or 5.5% of mean spike amplitude). Forty percent of the recording sessions showed a significant correlation in the occurrence of amplitude changes across electrodes, suggesting array micro-movement. Despite the relatively frequent amplitude changes, only 15% of the observed within-day rate changes originated from recording artifacts such as spike amplitude change or electrical noise, while 85% of the rate changes most likely emerged from physiological mechanisms. Computer simulations confirmed that systematic rate changes of individual neurons could produce a directional “bias” in the decoded neural cursor movements. Instability in apparent neuronal spike rates indeed yielded a directional bias in fifty-six percent of all performance assessments in participant cursor control (n=2 participants, 108 and 20 assessments over two years), resulting in suboptimal performance in these sessions. Significance We anticipate that signal acquisition and decoding methods that can adapt to the reported instabilities will further improve the performance of intracortically-based NISs. PMID:23574741

Non-invasive neural stimulation

NASA Astrophysics Data System (ADS)

Tyler, William J.; Sanguinetti, Joseph L.; Fini, Maria; Hool, Nicholas

2017-05-01

Neurotechnologies for non-invasively interfacing with neural circuits have been evolving from those capable of sensing neural activity to those capable of restoring and enhancing human brain function. Generally referred to as non-invasive neural stimulation (NINS) methods, these neuromodulation approaches rely on electrical, magnetic, photonic, and acoustic or ultrasonic energy to influence nervous system activity, brain function, and behavior. Evidence that has been surmounting for decades shows that advanced neural engineering of NINS technologies will indeed transform the way humans treat diseases, interact with information, communicate, and learn. The physics underlying the ability of various NINS methods to modulate nervous system activity can be quite different from one another depending on the energy modality used as we briefly discuss. For members of commercial and defense industry sectors that have not traditionally engaged in neuroscience research and development, the science, engineering and technology required to advance NINS methods beyond the state-of-the-art presents tremendous opportunities. Within the past few years alone there have been large increases in global investments made by federal agencies, foundations, private investors and multinational corporations to develop advanced applications of NINS technologies. Driven by these efforts NINS methods and devices have recently been introduced to mass markets via the consumer electronics industry. Further, NINS continues to be explored in a growing number of defense applications focused on enhancing human dimensions. The present paper provides a brief introduction to the field of non-invasive neural stimulation by highlighting some of the more common methods in use or under current development today.

Protease-degradable PEG-maleimide coating with on-demand release of IL-1Ra to improve tissue response to neural electrodes

PubMed Central

Gutowski, Stacie M.; Shoemaker, James T.; Templeman, Kellie L.; Wei, Yang; Latour, Robert A.; Bellamkonda, Ravi V.; LaPlaca, Michelle C.; García, Andrés J.

2015-01-01

Neural electrodes are an important part of brain-machine interface devices that can restore functionality to patients with sensory and movement disorders. Chronically implanted neural electrodes induce an unfavorable tissue response which includes inflammation, scar formation, and neuronal cell death, eventually causing loss of electrode function. We developed a poly(ethylene glycol) hydrogel coating for neural electrodes with non-fouling characteristics, incorporated an anti-inflammatory agent, and engineered a stimulus-responsive degradable portion for on-demand release of the anti-inflammatory agent in response to inflammatory stimuli. This coating reduces in vitro glial cell adhesion, cell spreading, and cytokine release compared to uncoated controls. We also analyzed the in vivo tissue response using immunohistochemistry and microarray qRT-PCR. Although no differences were observed among coated and uncoated electrodes for inflammatory cell markers, lower IgG penetration into the tissue around PEG+IL-1Ra coated electrodes indicates an improvement in blood-brain barrier integrity. Gene expression analysis showed higher expression of IL-6 and MMP-2 around PEG+IL-1Ra samples, as well as an increase in CNTF expression, an important marker for neuronal survival. Importantly, increased neuronal survival around coated electrodes compared to uncoated controls was observed. Collectively, these results indicate promising findings for an engineered coating to increase neuronal survival and improve tissue response around implanted neural electrodes. PMID:25617126

Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia

NASA Astrophysics Data System (ADS)

Kim, Sung-Phil; Simeral, John D.; Hochberg, Leigh R.; Donoghue, John P.; Black, Michael J.

2008-12-01

Computer-mediated connections between human motor cortical neurons and assistive devices promise to improve or restore lost function in people with paralysis. Recently, a pilot clinical study of an intracortical neural interface system demonstrated that a tetraplegic human was able to obtain continuous two-dimensional control of a computer cursor using neural activity recorded from his motor cortex. This control, however, was not sufficiently accurate for reliable use in many common computer control tasks. Here, we studied several central design choices for such a system including the kinematic representation for cursor movement, the decoding method that translates neuronal ensemble spiking activity into a control signal and the cursor control task used during training for optimizing the parameters of the decoding method. In two tetraplegic participants, we found that controlling a cursor's velocity resulted in more accurate closed-loop control than controlling its position directly and that cursor velocity control was achieved more rapidly than position control. Control quality was further improved over conventional linear filters by using a probabilistic method, the Kalman filter, to decode human motor cortical activity. Performance assessment based on standard metrics used for the evaluation of a wide range of pointing devices demonstrated significantly improved cursor control with velocity rather than position decoding. Disclosure. JPD is the Chief Scientific Officer and a director of Cyberkinetics Neurotechnology Systems (CYKN); he holds stock and receives compensation. JDS has been a consultant for CYKN. LRH receives clinical trial support from CYKN.

Highly ordered large-scale neuronal networks of individual cells - toward single cell to 3D nanowire intracellular interfaces.

PubMed

Kwiat, Moria; Elnathan, Roey; Pevzner, Alexander; Peretz, Asher; Barak, Boaz; Peretz, Hagit; Ducobni, Tamir; Stein, Daniel; Mittelman, Leonid; Ashery, Uri; Patolsky, Fernando

2012-07-25

The use of artificial, prepatterned neuronal networks in vitro is a promising approach for studying the development and dynamics of small neural systems in order to understand the basic functionality of neurons and later on of the brain. The present work presents a high fidelity and robust procedure for controlling neuronal growth on substrates such as silicon wafers and glass, enabling us to obtain mature and durable neural networks of individual cells at designed geometries. It offers several advantages compared to other related techniques that have been reported in recent years mainly because of its high yield and reproducibility. The procedure is based on surface chemistry that allows the formation of functional, tailormade neural architectures with a micrometer high-resolution partition, that has the ability to promote or repel cells attachment. The main achievements of this work are deemed to be the creation of a large scale neuronal network at low density down to individual cells, that develop intact typical neurites and synapses without any glia-supportive cells straight from the plating stage and with a relatively long term survival rate, up to 4 weeks. An important application of this method is its use on 3D nanopillars and 3D nanowire-device arrays, enabling not only the cell bodies, but also their neurites to be positioned directly on electrical devices and grow with registration to the recording elements underneath.

Ethical issues in neuroprosthetics

NASA Astrophysics Data System (ADS)

Glannon, Walter

2016-04-01

Objective. Neuroprosthetics are artificial devices or systems designed to generate, restore or modulate a range of neurally mediated functions. These include sensorimotor, visual, auditory, cognitive affective and volitional functions that have been impaired or lost from congenital anomalies, traumatic brain injury, infection, amputation or neurodevelopmental and neurodegenerative disorders. Cochlear implants, visual prosthetics, deep brain stimulation, brain-computer interfaces, brain-to-brain interfaces and hippocampal prosthetics can bypass, replace or compensate for dysfunctional neural circuits, brain injury and limb loss. They can enable people with these conditions to gain or regain varying degrees of control of thought and behavior. These direct and indirect interventions in the brain raise general ethical questions about weighing the potential benefit of altering neural circuits against the potential harm from neurophysiological and psychological sequelae. Other ethical questions are more specific to the therapeutic goals of particular neuroprosthetics and the conditions for which they are indicated. These include informed consent, agency, autonomy (free will) and identity. Approach. This review is an analysis and discussion of these questions. It also includes consideration of social justice issues such as how to establish and implement fair selection criteria in providing access to neuroprosthetic research and balancing technological innovation with patients’ best interests. Main results. Neuroprosthetics can restore or improve motor and mental functions in bypassing areas of injury or modulating dysregulation in neural circuits. As enabling devices that integrate with these circuits, neuroprosthetics can restore varying degrees of autonomous agency for people affected by neurological and psychiatric disorders. They can also re-establish the connectedness and continuity of the psychological properties they had before injury or disease onset and thereby re-establish their identity. Neuroprosthetics can maximize benefit and minimize harm for people affected by damaged or dysfunctional brains and improve the quality of their lives. Significance. Provided that adequate protections are in place for research subjects and patients, the probable benefit of research into and therapeutic applications of neuroprosthetics outweighs the risk and therefore can be ethically justified. Depending on their neurogenerative potential, there may be an ethical obligation to conduct this research. Advances in neuroscience will generate new ethical and philosophical questions about people and their brains. These questions should shape the evolution and application of novel techniques to better understand and treat brain disorders.

Ethical issues in neuroprosthetics.

PubMed

Glannon, Walter

2016-04-01

Neuroprosthetics are artificial devices or systems designed to generate, restore or modulate a range of neurally mediated functions. These include sensorimotor, visual, auditory, cognitive affective and volitional functions that have been impaired or lost from congenital anomalies, traumatic brain injury, infection, amputation or neurodevelopmental and neurodegenerative disorders. Cochlear implants, visual prosthetics, deep brain stimulation, brain-computer interfaces, brain-to-brain interfaces and hippocampal prosthetics can bypass, replace or compensate for dysfunctional neural circuits, brain injury and limb loss. They can enable people with these conditions to gain or regain varying degrees of control of thought and behavior. These direct and indirect interventions in the brain raise general ethical questions about weighing the potential benefit of altering neural circuits against the potential harm from neurophysiological and psychological sequelae. Other ethical questions are more specific to the therapeutic goals of particular neuroprosthetics and the conditions for which they are indicated. These include informed consent, agency, autonomy (free will) and identity. This review is an analysis and discussion of these questions. It also includes consideration of social justice issues such as how to establish and implement fair selection criteria in providing access to neuroprosthetic research and balancing technological innovation with patients' best interests. Neuroprosthetics can restore or improve motor and mental functions in bypassing areas of injury or modulating dysregulation in neural circuits. As enabling devices that integrate with these circuits, neuroprosthetics can restore varying degrees of autonomous agency for people affected by neurological and psychiatric disorders. They can also re-establish the connectedness and continuity of the psychological properties they had before injury or disease onset and thereby re-establish their identity. Neuroprosthetics can maximize benefit and minimize harm for people affected by damaged or dysfunctional brains and improve the quality of their lives. Provided that adequate protections are in place for research subjects and patients, the probable benefit of research into and therapeutic applications of neuroprosthetics outweighs the risk and therefore can be ethically justified. Depending on their neurogenerative potential, there may be an ethical obligation to conduct this research. Advances in neuroscience will generate new ethical and philosophical questions about people and their brains. These questions should shape the evolution and application of novel techniques to better understand and treat brain disorders.

A device for emulating cuff recordings of action potentials propagating along peripheral nerves.

PubMed

Rieger, Robert; Schuettler, Martin; Chuang, Sheng-Chih

2014-09-01

This paper describes a device that emulates propagation of action potentials along a peripheral nerve, suitable for reproducible testing of bio-potential recording systems using nerve cuff electrodes. The system is a microcontroller-based stand-alone instrument which uses established nerve and electrode models to represent neural activity of real nerves recorded with a nerve cuff interface, taking into consideration electrode impedance, voltages picked up by the electrodes, and action potential propagation characteristics. The system emulates different scenarios including compound action potentials with selectable propagation velocities and naturally occurring nerve traffic from different velocity fiber populations. Measured results from a prototype implementation are reported and compared with in vitro recordings from Xenopus Laevis frog sciatic nerve, demonstrating that the electrophysiological setting is represented to a satisfactory degree, useful for the development, optimization and characterization of future recording systems.

Suppression of scarring in peripheral nerve implants by drug elution.

PubMed

FitzGerald, James J

2016-04-01

Medical implants made of non-biological materials provoke a chronic inflammatory response, resulting in the deposition of a collagenous scar tissue (ST) layer on their surface, that gradually thickens over time. This is a critical problem for neural interfaces. Scar build-up on electrodes results in a progressive decline in signal level because the scar tissue gradually separates axons away from the recording contacts. In regenerative sieves and microchannel electrodes, progressive scar deposition will constrict and may eventually choke off the sieve hole or channel lumen. Interface designs need to address this issue if they are to be fit for long term use. This study examines a novel method of inhibiting the formation and thickening of the fibrous scar. Research to date has mainly focused on methods of preventing stimulation of the foreign body response by implant surface modification. In this paper a pharmacological approach using drug elution to suppress chronic inflammation is introduced. Microchannel implants made of silicone doped with the steroid drug dexamethasone were implanted in the rat sciatic nerve for periods of up to a year. Tissue from within the microchannels was compared to that from control devices that did not release any drug. In the drug eluting implants the scar layer was significantly thinner at all timepoints, and unlike the controls it did not continue to thicken after 6 months. Control implants supported axon regeneration well initially, but axon counts fell rapidly at later timepoints as scar thickened. Axon counts in drug eluting devices were initially much lower, but increased rather than declined and by one year were significantly higher than in controls. Drug elution offers a potential long term solution to the problem of performance degradation due to scarring around neural implants.

Suppression of scarring in peripheral nerve implants by drug elution

NASA Astrophysics Data System (ADS)

FitzGerald, James J.

2016-04-01

Objective. Medical implants made of non-biological materials provoke a chronic inflammatory response, resulting in the deposition of a collagenous scar tissue (ST) layer on their surface, that gradually thickens over time. This is a critical problem for neural interfaces. Scar build-up on electrodes results in a progressive decline in signal level because the scar tissue gradually separates axons away from the recording contacts. In regenerative sieves and microchannel electrodes, progressive scar deposition will constrict and may eventually choke off the sieve hole or channel lumen. Interface designs need to address this issue if they are to be fit for long term use. This study examines a novel method of inhibiting the formation and thickening of the fibrous scar. Approach. Research to date has mainly focused on methods of preventing stimulation of the foreign body response by implant surface modification. In this paper a pharmacological approach using drug elution to suppress chronic inflammation is introduced. Microchannel implants made of silicone doped with the steroid drug dexamethasone were implanted in the rat sciatic nerve for periods of up to a year. Tissue from within the microchannels was compared to that from control devices that did not release any drug. Main results. In the drug eluting implants the scar layer was significantly thinner at all timepoints, and unlike the controls it did not continue to thicken after 6 months. Control implants supported axon regeneration well initially, but axon counts fell rapidly at later timepoints as scar thickened. Axon counts in drug eluting devices were initially much lower, but increased rather than declined and by one year were significantly higher than in controls. Significance. Drug elution offers a potential long term solution to the problem of performance degradation due to scarring around neural implants.

SELF ALIGNED TIP DEINSULATION OF ATOMIC LAYER DEPOSITED AL2O3 AND PARYLENE C COATED UTAH ELECTRODE ARRAY BASED NEURAL INTERFACES

PubMed Central

Xie, Xianzong; Rieth, Loren; Negi, Sandeep; Bhandari, Rajmohan; Caldwell, Ryan; Sharma, Rohit; Tathireddy, Prashant; Solzbacher, Florian

2014-01-01

The recently developed alumina and Parylene C bi-layer encapsulation improved the lifetime of neural interfaces. Tip deinsulation of Utah electrode array based neural interfaces is challenging due to the complex 3D geometries and high aspect ratios of the devices. A three-step self-aligned process was developed for tip deinsulation of bilayer encapsulated arrays. The deinsulation process utilizes laser ablation to remove Parylene C, O2 reactive ion etching to remove carbon and Parylene residues, and buffered oxide etch to remove alumina deposited by atomic layer deposition, and expose the IrOx tip metallization. The deinsulated iridium oxide area was characterized by scanning electron microscopy, atomic force microscopy, X-ray photoelectron spectroscopy, and electrochemical impedance spectroscopy to determine the morphology, surface morphology, composition, and electrical properties of the deposited layers and deinsulated tips. The alumina layer was found to prevent the formation of micro cracks on iridium oxide during the laser ablation process, which has been previously reported as a challenge for laser deinsulation of Parylene films. The charge injection capacity, charge storage capacity, and impedance of deinsulated iridium oxide were characterized to determine the deinsulation efficacy compared to Parylene-only insulation. Deinsulated iridium oxide with bilayer encapsulation had higher charge injection capacity (240 vs 320 nC) and similar electrochemical impedance (2.5 vs 2.5 kΩ) compared to deinsulated iridium oxide with only Parylene coating for an area of 2 × 10−4 cm2. Tip impedances were in the ranges of 20 to 50 kΩ, with median of 32 KΩ and standard deviation of 30 kΩ, showing the effectiveness of the self-aligned deinsulation process for alumina and Parylene C bi-layer encapsulation. The relatively uniform tip impedance values demonstrated the consistency of tip exposures. PMID:24771981

Spiking Neural Networks Based on OxRAM Synapses for Real-Time Unsupervised Spike Sorting.

PubMed

Werner, Thilo; Vianello, Elisa; Bichler, Olivier; Garbin, Daniele; Cattaert, Daniel; Yvert, Blaise; De Salvo, Barbara; Perniola, Luca

2016-01-01

In this paper, we present an alternative approach to perform spike sorting of complex brain signals based on spiking neural networks (SNN). The proposed architecture is suitable for hardware implementation by using resistive random access memory (RRAM) technology for the implementation of synapses whose low latency (<1μs) enables real-time spike sorting. This offers promising advantages to conventional spike sorting techniques for brain-computer interfaces (BCI) and neural prosthesis applications. Moreover, the ultra-low power consumption of the RRAM synapses of the spiking neural network (nW range) may enable the design of autonomous implantable devices for rehabilitation purposes. We demonstrate an original methodology to use Oxide based RRAM (OxRAM) as easy to program and low energy (<75 pJ) synapses. Synaptic weights are modulated through the application of an online learning strategy inspired by biological Spike Timing Dependent Plasticity. Real spiking data have been recorded both intra- and extracellularly from an in-vitro preparation of the Crayfish sensory-motor system and used for validation of the proposed OxRAM based SNN. This artificial SNN is able to identify, learn, recognize and distinguish between different spike shapes in the input signal with a recognition rate about 90% without any supervision.

Optical Control of Living Cells Electrical Activity by Conjugated Polymers.

PubMed

Martino, Nicola; Bossio, Caterina; Vaquero Morata, Susana; Lanzani, Guglielmo; Antognazza, Maria Rosa

2016-01-28

Hybrid interfaces between organic semiconductors and living tissues represent a new tool for in-vitro and in-vivo applications. In particular, conjugated polymers display several optimal properties as substrates for biological systems, such as good biocompatibility, excellent mechanical properties, cheap and easy processing technology, and possibility of deposition on light, thin and flexible substrates. These materials have been employed for cellular interfaces like neural probes, transistors for excitation and recording of neural activity, biosensors and actuators for drug release. Recent experiments have also demonstrated the possibility to use conjugated polymers for all-optical modulation of the electrical activity of cells. Several in-vitro study cases have been reported, including primary neuronal networks, astrocytes and secondary line cells. Moreover, signal photo-transduction mediated by organic polymers has been shown to restore light sensitivity in degenerated retinas, suggesting that these devices may be used for artificial retinal prosthesis in the future. All in all, light sensitive conjugated polymers represent a new approach for optical modulation of cellular activity. In this work, all the steps required to fabricate a bio-polymer interface for optical excitation of living cells are described. The function of the active interface is to transduce the light stimulus into a modulation of the cell membrane potential. As a study case, useful for in-vitro studies, a polythiophene thin film is used as the functional, light absorbing layer, and Human Embryonic Kidney (HEK-293) cells are employed as the biological component of the interface. Practical examples of successful control of the cell membrane potential upon stimulation with light pulses of different duration are provided. In particular, it is shown that both depolarizing and hyperpolarizing effects on the cell membrane can be achieved depending on the duration of the light stimulus. The reported protocol is of general validity and can be straightforwardly extended to other biological preparations.

Decoding the non-stationary neuron spike trains by dual Monte Carlo point process estimation in motor Brain Machine Interfaces.

PubMed

Liao, Yuxi; Li, Hongbao; Zhang, Qiaosheng; Fan, Gong; Wang, Yiwen; Zheng, Xiaoxiang

2014-01-01

Decoding algorithm in motor Brain Machine Interfaces translates the neural signals to movement parameters. They usually assume the connection between the neural firings and movements to be stationary, which is not true according to the recent studies that observe the time-varying neuron tuning property. This property results from the neural plasticity and motor learning etc., which leads to the degeneration of the decoding performance when the model is fixed. To track the non-stationary neuron tuning during decoding, we propose a dual model approach based on Monte Carlo point process filtering method that enables the estimation also on the dynamic tuning parameters. When applied on both simulated neural signal and in vivo BMI data, the proposed adaptive method performs better than the one with static tuning parameters, which raises a promising way to design a long-term-performing model for Brain Machine Interfaces decoder.

The Pursuit of Chronically Reliable Neural Interfaces: A Materials Perspective.

PubMed

Guo, Liang

2016-01-01

Brain-computer interfaces represent one of the most astonishing technologies in our era. However, the grand challenge of chronic instability and limited throughput of the electrode-tissue interface has significantly hindered the further development and ultimate deployment of such exciting technologies. A multidisciplinary research workforce has been called upon to respond to this engineering need. In this paper, I briefly review this multidisciplinary pursuit of chronically reliable neural interfaces from a materials perspective by analyzing the problem, abstracting the engineering principles, and summarizing the corresponding engineering strategies. I further draw my future perspectives by extending the proposed engineering principles.

Evaluation of the Impact of Groundwater Pumping on Freshwater-Saltwater Interface Fluctuations in a Coastal Aquifer of South Korea

NASA Astrophysics Data System (ADS)

Yoon, H.; Kim, Y.; Lee, S. H.; Ha, K.

2017-12-01

It is necessary to monitor the variation of freshwater-saltwater interface for the sustainable use of groundwater resources in coastal areas. In the present study, we developed a device to measure the location of the freshwater-saltwater interface based on the concept of the neutral buoyancy and installed it in a coastal aquifer of the western sea, South Korea. To evaluate the impact of pumping on the groundwater and saltwater-freshwater interface level, we designed nine different pumping scenarios and monitored the groundwater and saltwater-freshwater interface levels of pumping well and two observation wells. The result of monitoring groundwater level shows that the response of observation wells to the pumping is relatively fast and high, however, the response of freshwater-saltwater interface occurred when the pumping rate and duration are over 25m3/day and 48hours, respectively. For the prediction and simulation of the groundwater level fluctuation under groundwater pumping events, we designed a artificial neural network based time series model considering rainfall, tide, and pumping rate as input components. The result of the prediction shows that the correlation coefficient between observed and estimated groundwater levels is as high as 0.7. It is expected that the result of this research can provide useful information for the effective management of groundwater resources in the study area.

3D-nanostructured boron-doped diamond for microelectrode array neural interfacing.

PubMed

Piret, Gaëlle; Hébert, Clément; Mazellier, Jean-Paul; Rousseau, Lionel; Scorsone, Emmanuel; Cottance, Myline; Lissorgues, Gaelle; Heuschkel, Marc O; Picaud, Serge; Bergonzo, Philippe; Yvert, Blaise

2015-06-01

The electrode material is a key element in the design of long-term neural implants and neuroprostheses. To date, the ideal electrode material offering high longevity, biocompatibility, low-noise recording and high stimulation capabilities remains to be found. We show that 3D-nanostructured boron doped diamond (BDD), an innovative material consisting in a chemically stable material with a high aspect ratio structure obtained by encapsulation of a carbon nanotube template within two BDD nanolayers, allows neural cell attachment, survival and neurite extension. Further, we developed arrays of 20-μm-diameter 3D-nanostructured BDD microelectrodes for neural interfacing. These microelectrodes exhibited low impedances and low intrinsic recording noise levels. In particular, they allowed the detection of low amplitude (10-20 μV) local-field potentials, single units and multiunit bursts neural activity in both acute whole embryonic hindbrain-spinal cord preparations and long-term hippocampal cell cultures. Also, cyclic voltammetry measurements showed a wide potential window of about 3 V and a charge storage capacity of 10 mC.cm(-2), showing high potentiality of this material for neural stimulation. These results demonstrate the attractiveness of 3D-nanostructured BDD as a novel material for neural interfacing, with potential applications for the design of biocompatible neural implants for the exploration and rehabilitation of the nervous system. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Enhancement of electrical signaling in neural networks on graphene films.

PubMed

Tang, Mingliang; Song, Qin; Li, Ning; Jiang, Ziyun; Huang, Rong; Cheng, Guosheng

2013-09-01

One of the key challenges for neural tissue engineering is to exploit supporting materials with robust functionalities not only to govern cell-specific behaviors, but also to form functional neural network. The unique electrical and mechanical properties of graphene imply it as a promising candidate for neural interfaces, but little is known about the details of neural network formation on graphene as a scaffold material for tissue engineering. Therapeutic regenerative strategies aim to guide and enhance the intrinsic capacity of the neurons to reorganize by promoting plasticity mechanisms in a controllable manner. Here, we investigated the impact of graphene on the formation and performance in the assembly of neural networks in neural stem cell (NSC) culture. Using calcium imaging and electrophysiological recordings, we demonstrate the capabilities of graphene to support the growth of functional neural circuits, and improve neural performance and electrical signaling in the network. These results offer a better understanding of interactions between graphene and NSCs, also they clearly present the great potentials of graphene as neural interface in tissue engineering. Copyright © 2013 Elsevier Ltd. All rights reserved.

In vivo Characterization of Amorphous Silicon Carbide As a Biomaterial for Chronic Neural Interfaces

PubMed Central

Knaack, Gretchen L.; McHail, Daniel G.; Borda, German; Koo, Beomseo; Peixoto, Nathalia; Cogan, Stuart F.; Dumas, Theodore C.; Pancrazio, Joseph J.

2016-01-01

Implantable microelectrode arrays (MEAs) offer clinical promise for prosthetic devices by enabling restoration of communication and control of artificial limbs. While proof-of-concept recordings from MEAs have been promising, work in animal models demonstrates that the obtained signals degrade over time. Both material robustness and tissue response are acknowledged to have a role in device lifetime. Amorphous Silicon carbide (a-SiC), a robust material that is corrosion resistant, has emerged as an alternative encapsulation layer for implantable devices. We systematically examined the impact of a-SiC coating on Si probes by immunohistochemical characterization of key markers implicated in tissue-device response. After implantation, we performed device capture immunohistochemical labeling of neurons, astrocytes, and activated microglia/macrophages after 4 and 8 weeks of implantation. Neuron loss and microglia activation were similar between Si and a-SiC coated probes, while tissue implanted with a-SiC displayed a reduction in astrocytes adjacent to the probe. These results suggest that a-SiC has a similar biocompatibility profile as Si, and may be suitable for implantable MEA applications as a hermetic coating to prevent material degradation. PMID:27445672

In vivo Characterization of Amorphous Silicon Carbide As a Biomaterial for Chronic Neural Interfaces.

PubMed

Knaack, Gretchen L; McHail, Daniel G; Borda, German; Koo, Beomseo; Peixoto, Nathalia; Cogan, Stuart F; Dumas, Theodore C; Pancrazio, Joseph J

2016-01-01

Implantable microelectrode arrays (MEAs) offer clinical promise for prosthetic devices by enabling restoration of communication and control of artificial limbs. While proof-of-concept recordings from MEAs have been promising, work in animal models demonstrates that the obtained signals degrade over time. Both material robustness and tissue response are acknowledged to have a role in device lifetime. Amorphous Silicon carbide (a-SiC), a robust material that is corrosion resistant, has emerged as an alternative encapsulation layer for implantable devices. We systematically examined the impact of a-SiC coating on Si probes by immunohistochemical characterization of key markers implicated in tissue-device response. After implantation, we performed device capture immunohistochemical labeling of neurons, astrocytes, and activated microglia/macrophages after 4 and 8 weeks of implantation. Neuron loss and microglia activation were similar between Si and a-SiC coated probes, while tissue implanted with a-SiC displayed a reduction in astrocytes adjacent to the probe. These results suggest that a-SiC has a similar biocompatibility profile as Si, and may be suitable for implantable MEA applications as a hermetic coating to prevent material degradation.

Implantable radio frequency identification sensors: wireless power and communication.

PubMed

Hutchens, Chriswell; Rennaker, Robert L; Venkataraman, Srinivasan; Ahmed, Rehan; Liao, Ran; Ibrahim, Tamer

2011-01-01

There are significant technical challenges in the development of a fully implantable wirelessly powered neural interface. Challenges include wireless transmission of sufficient power to the implanted device to ensure reliable operation for decades without replacement, minimizing tissue heating, and adequate reliable communications bandwidth. Overcoming these challenges is essential for the development of implantable closed loop system for the treatment of disorders ranging from epilepsy, incontinence, stroke and spinal cord injury. We discuss the development of the wireless power, communication and control for a Radio-Frequency Identification Sensor (RFIDS) system with targeted power range for a 700 mV, 30 to 40 uA load attained at -2 dBm.

Clinical applications of penetrating neural interfaces and Utah Electrode Array technologies

NASA Astrophysics Data System (ADS)

Normann, Richard A.; Fernandez, Eduardo

2016-12-01

This paper briefly describes some of the recent progress in the development of penetrating microelectrode arrays and highlights the use of two of these devices, Utah electrode arrays and Utah slanted electrode arrays, in two therapeutic interventions: recording volitional skeletal motor commands from the central nervous system, and recording motor commands and evoking somatosensory percepts in the peripheral nervous system (PNS). The paper also briefly explores other potential sites for microelectrode array interventions that could be profitably pursued and that could have important consequences in enhancing the quality of life of patients that has been compromised by disorders of the central and PNSs.

Proposal for an All-Spin Artificial Neural Network: Emulating Neural and Synaptic Functionalities Through Domain Wall Motion in Ferromagnets.

PubMed

Sengupta, Abhronil; Shim, Yong; Roy, Kaushik

2016-12-01

Non-Boolean computing based on emerging post-CMOS technologies can potentially pave the way for low-power neural computing platforms. However, existing work on such emerging neuromorphic architectures have either focused on solely mimicking the neuron, or the synapse functionality. While memristive devices have been proposed to emulate biological synapses, spintronic devices have proved to be efficient at performing the thresholding operation of the neuron at ultra-low currents. In this work, we propose an All-Spin Artificial Neural Network where a single spintronic device acts as the basic building block of the system. The device offers a direct mapping to synapse and neuron functionalities in the brain while inter-layer network communication is accomplished via CMOS transistors. To the best of our knowledge, this is the first demonstration of a neural architecture where a single nanoelectronic device is able to mimic both neurons and synapses. The ultra-low voltage operation of low resistance magneto-metallic neurons enables the low-voltage operation of the array of spintronic synapses, thereby leading to ultra-low power neural architectures. Device-level simulations, calibrated to experimental results, was used to drive the circuit and system level simulations of the neural network for a standard pattern recognition problem. Simulation studies indicate energy savings by  ∼  100× in comparison to a corresponding digital/analog CMOS neuron implementation.

A TinyOS-based wireless neural interface.

PubMed

Farshchi, Shahin; Mody, Istvan; Judy, Jack W

2004-01-01

The overlay of a neural interface upon a TinyOS-based sensing and communication platform is described. The system amplifies, digitally encodes, and transmits two EEG channels of neural signals from an un-tethered subject to a remote gateway, which routes the signals to a client PC. This work demonstrates the viability of the TinyOS-based sensor technology as a foundation for chronic remote biological monitoring applications, and thus provides an opportunity to create a system that can leverage from the frequent networking and communications advancements being made by the global TinyOS-development community.

Selective electrical interfaces with the nervous system.

PubMed

Rutten, Wim L C

2002-01-01

To achieve selective electrical interfacing to the neural system it is necessary to approach neuronal elements on a scale of micrometers. This necessitates microtechnology fabrication and introduces the interdisciplinary field of neurotechnology, lying at the juncture of neuroscience with microtechnology. The neuroelectronic interface occurs where the membrane of a cell soma or axon meets a metal microelectrode surface. The seal between these may be narrow or may be leaky. In the latter case the surrounding volume conductor becomes part of the interface. Electrode design for successful interfacing, either for stimulation or recording, requires good understanding of membrane phenomena, natural and evoked action potential generation, volume conduction, and electrode behavior. Penetrating multimicroelectrodes have been produced as one-, two-, and three-dimensional arrays, mainly in silicon, glass, and metal microtechnology. Cuff electrodes circumvent a nerve; their selectivity aims at fascicles more than at nerve fibers. Other types of electrodes are regenerating sieves and cone-ingrowth electrodes. The latter may play a role in brain-computer interfaces. Planar substrate-embedded electrode arrays with cultured neural cells on top are used to study the activity and plasticity of developing neural networks. They also serve as substrates for future so-called cultured probes.

Multiplexed neural recording along a single optical fiber via optical reflectometry

PubMed Central

Rodriques, Samuel G.; Marblestone, Adam H.; Scholvin, Jorg; Dapello, Joel; Sarkar, Deblina; Mankin, Max; Gao, Ruixuan; Wood, Lowell; Boyden, Edward S.

2016-01-01

Abstract. We introduce the design and theoretical analysis of a fiber-optic architecture for neural recording without contrast agents, which transduces neural electrical signals into a multiplexed optical readout. Our sensor design is inspired by electro-optic modulators, which modulate the refractive index of a waveguide by applying a voltage across an electro-optic core material. We estimate that this design would allow recording of the activities of individual neurons located at points along a 10-cm length of optical fiber with 40-μm axial resolution and sensitivity down to 100  μV using commercially available optical reflectometers as readout devices. Neural recording sites detect a potential difference against a reference and apply this potential to a capacitor. The waveguide serves as one of the plates of the capacitor, so charge accumulation across the capacitor results in an optical effect. A key concept of the design is that the sensitivity can be improved by increasing the capacitance. To maximize the capacitance, we utilize a microscopic layer of material with high relative permittivity. If suitable materials can be found—possessing high capacitance per unit area as well as favorable properties with respect to toxicity, optical attenuation, ohmic junctions, and surface capacitance—then such sensing fibers could, in principle, be scaled down to few-micron cross-sections for minimally invasive neural interfacing. We study these material requirements and propose potential material choices. Custom-designed multimaterial optical fibers, probed using a reflectometric readout, may, therefore, provide a powerful platform for neural sensing. PMID:27194640

The impact of neurotechnology on rehabilitation.

PubMed

Berger, Theodore W; Gerhardt, Greg; Liker, Mark A; Soussou, Walid

2008-01-01

This paper present results of a multi-disciplinary project that is developing a microchip-based neural prosthesis for the hippocampus, a region of the brain responsible for the formation of long-term memories. Damage to the hippocampus is frequently associated with epilepsy, stroke, and dementia (Alzheimer's disease) and is considered to underlie the memory deficits related to these neurological conditions. The essential goals of the multi-laboratory effort include: (1) experimental study of neuron and neural network function--how does the hippocampus encode information? (2) formulation of biologically realistic models of neural system dynamics--can that encoding process be described mathematically to realize a predictive model of how the hippocampus responds to any event? (3) microchip implementation of neural system models--can the mathematical model be realized as a set of electronic circuits to achieve parallel processing, rapid computational speed, and miniaturization? and (4) creation of hybrid neuron-silicon interfaces-can structural and functional connections between electronic devices and neural tissue be achieved for long-term, bi-directional communication with the brain? By integrating solutions to these component problems, we are realizing a microchip-based model of hippocampal nonlinear dynamics that can perform the same function as part of the hippocampus. Through bi-directional communication with other neural tissue that normally provides the inputs and outputs to/from a damaged hippocampal area, the biomimetic model could serve as a neural prosthesis. A proof-of-concept will be presented in which the CA3 region of the hippocampal slice is surgically removed and is replaced by a microchip model of CA3 nonlinear dynamics--the "hybrid" hippocampal circuit displays normal physiological properties. How the work in brain slices is being extended to behaving animals also will be described.

A freely-moving monkey treadmill model.

PubMed

Foster, Justin D; Nuyujukian, Paul; Freifeld, Oren; Gao, Hua; Walker, Ross; I Ryu, Stephen; H Meng, Teresa; Murmann, Boris; J Black, Michael; Shenoy, Krishna V

2014-08-01

Motor neuroscience and brain-machine interface (BMI) design is based on examining how the brain controls voluntary movement, typically by recording neural activity and behavior from animal models. Recording technologies used with these animal models have traditionally limited the range of behaviors that can be studied, and thus the generality of science and engineering research. We aim to design a freely-moving animal model using neural and behavioral recording technologies that do not constrain movement. We have established a freely-moving rhesus monkey model employing technology that transmits neural activity from an intracortical array using a head-mounted device and records behavior through computer vision using markerless motion capture. We demonstrate the flexibility and utility of this new monkey model, including the first recordings from motor cortex while rhesus monkeys walk quadrupedally on a treadmill. Using this monkey model, we show that multi-unit threshold-crossing neural activity encodes the phase of walking and that the average firing rate of the threshold crossings covaries with the speed of individual steps. On a population level, we find that neural state-space trajectories of walking at different speeds have similar rotational dynamics in some dimensions that evolve at the step rate of walking, yet robustly separate by speed in other state-space dimensions. Freely-moving animal models may allow neuroscientists to examine a wider range of behaviors and can provide a flexible experimental paradigm for examining the neural mechanisms that underlie movement generation across behaviors and environments. For BMIs, freely-moving animal models have the potential to aid prosthetic design by examining how neural encoding changes with posture, environment and other real-world context changes. Understanding this new realm of behavior in more naturalistic settings is essential for overall progress of basic motor neuroscience and for the successful translation of BMIs to people with paralysis.

Applying cybernetic technology to diagnose human pulmonary sounds.

PubMed

Chen, Mei-Yung; Chou, Cheng-Han

2014-06-01

Chest auscultation is a crucial and efficient method for diagnosing lung disease; however, it is a subjective process that relies on physician experience and the ability to differentiate between various sound patterns. Because the physiological signals composed of heart sounds and pulmonary sounds (PSs) are greater than 120 Hz and the human ear is not sensitive to low frequencies, successfully making diagnostic classifications is difficult. To solve this problem, we constructed various PS recognition systems for classifying six PS classes: vesicular breath sounds, bronchial breath sounds, tracheal breath sounds, crackles, wheezes, and stridor sounds. First, we used a piezoelectric microphone and data acquisition card to acquire PS signals and perform signal preprocessing. A wavelet transform was used for feature extraction, and the PS signals were decomposed into frequency subbands. Using a statistical method, we extracted 17 features that were used as the input vectors of a neural network. We proposed a 2-stage classifier combined with a back-propagation (BP) neural network and learning vector quantization (LVQ) neural network, which improves classification accuracy by using a haploid neural network. The receiver operating characteristic (ROC) curve verifies the high performance level of the neural network. To expand traditional auscultation methods, we constructed various PS diagnostic systems that can correctly classify the six common PSs. The proposed device overcomes the lack of human sensitivity to low-frequency sounds and various PS waves, characteristic values, and a spectral analysis charts are provided to elucidate the design of the human-machine interface.

Python scripting in the nengo simulator.

PubMed

Stewart, Terrence C; Tripp, Bryan; Eliasmith, Chris

2009-01-01

Nengo (http://nengo.ca) is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the neural engineering framework (NEF). This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide (1) more realistic boundary conditions for the neural components, and (2) more realistic sub-components for the larger cognitive models.

Python Scripting in the Nengo Simulator

PubMed Central

Stewart, Terrence C.; Tripp, Bryan; Eliasmith, Chris

2008-01-01

Nengo (http://nengo.ca) is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the neural engineering framework (NEF). This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide (1) more realistic boundary conditions for the neural components, and (2) more realistic sub-components for the larger cognitive models. PMID:19352442

A neural network device for on-line particle identification in cosmic ray experiments

NASA Astrophysics Data System (ADS)

Scrimaglio, R.; Finetti, N.; D'Altorio, L.; Rantucci, E.; Raso, M.; Segreto, E.; Tassoni, A.; Cardarilli, G. C.

2004-05-01

On-line particle identification is one of the main goals of many experiments in space both for rare event studies and for optimizing measurements along the orbital trajectory. Neural networks can be a useful tool for signal processing and real time data analysis in such experiments. In this document we report on the performances of a programmable neural device which was developed in VLSI analog/digital technology. Neurons and synapses were accomplished by making use of Operational Transconductance Amplifier (OTA) structures. In this paper we report on the results of measurements performed in order to verify the agreement of the characteristic curves of each elementary cell with simulations and on the device performances obtained by implementing simple neural structures on the VLSI chip. A feed-forward neural network (Multi-Layer Perceptron, MLP) was implemented on the VLSI chip and trained to identify particles by processing the signals of two-dimensional position-sensitive Si detectors. The radiation monitoring device consisted of three double-sided silicon strip detectors. From the analysis of a set of simulated data it was found that the MLP implemented on the neural device gave results comparable with those obtained with the standard method of analysis confirming that the implemented neural network could be employed for real time particle identification.

Angiogenesis in the Developing Spinal Cord: Blood Vessel Exclusion from Neural Progenitor Region Is Mediated by VEGF and Its Antagonists

PubMed Central

Takahashi, Teruaki; Takase, Yuta; Yoshino, Takashi; Saito, Daisuke; Tadokoro, Ryosuke; Takahashi, Yoshiko

2015-01-01

Blood vessels in the central nervous system supply a considerable amount of oxygen via intricate vascular networks. We studied how the initial vasculature of the spinal cord is formed in avian (chicken and quail) embryos. Vascular formation in the spinal cord starts by the ingression of intra-neural vascular plexus (INVP) from the peri-neural vascular plexus (PNVP) that envelops the neural tube. At the ventral region of the PNVP, the INVP grows dorsally in the neural tube, and we observed that these vessels followed the defined path at the interface between the medially positioned and undifferentiated neural progenitor zone and the laterally positioned differentiated zone. When the interface between these two zones was experimentally displaced, INVP faithfully followed a newly formed interface, suggesting that the growth path of the INVP is determined by surrounding neural cells. The progenitor zone expressed mRNA of vascular endothelial growth factor-A whereas its receptor VEGFR2 and FLT-1 (VEGFR1), a decoy for VEGF, were expressed in INVP. By manipulating the neural tube with either VEGF or the soluble form of FLT-1, we found that INVP grew in a VEGF-dependent manner, where VEGF signals appear to be fine-tuned by counteractions with anti-angiogenic activities including FLT-1 and possibly semaphorins. These results suggest that the stereotypic patterning of early INVP is achieved by interactions between these vessels and their surrounding neural cells, where VEGF and its antagonists play important roles. PMID:25585380

Neural control of finger movement via intracortical brain-machine interface

NASA Astrophysics Data System (ADS)

Irwin, Z. T.; Schroeder, K. E.; Vu, P. P.; Bullard, A. J.; Tat, D. M.; Nu, C. S.; Vaskov, A.; Nason, S. R.; Thompson, D. E.; Bentley, J. N.; Patil, P. G.; Chestek, C. A.

2017-12-01

Objective. Intracortical brain-machine interfaces (BMIs) are a promising source of prosthesis control signals for individuals with severe motor disabilities. Previous BMI studies have primarily focused on predicting and controlling whole-arm movements; precise control of hand kinematics, however, has not been fully demonstrated. Here, we investigate the continuous decoding of precise finger movements in rhesus macaques. Approach. In order to elicit precise and repeatable finger movements, we have developed a novel behavioral task paradigm which requires the subject to acquire virtual fingertip position targets. In the physical control condition, four rhesus macaques performed this task by moving all four fingers together in order to acquire a single target. This movement was equivalent to controlling the aperture of a power grasp. During this task performance, we recorded neural spikes from intracortical electrode arrays in primary motor cortex. Main results. Using a standard Kalman filter, we could reconstruct continuous finger movement offline with an average correlation of ρ  =  0.78 between actual and predicted position across four rhesus macaques. For two of the monkeys, this movement prediction was performed in real-time to enable direct brain control of the virtual hand. Compared to physical control, neural control performance was slightly degraded; however, the monkeys were still able to successfully perform the task with an average target acquisition rate of 83.1%. The monkeys’ ability to arbitrarily specify fingertip position was also quantified using an information throughput metric. During brain control task performance, the monkeys achieved an average 1.01 bits s-1 throughput, similar to that achieved in previous studies which decoded upper-arm movements to control computer cursors using a standard Kalman filter. Significance. This is, to our knowledge, the first demonstration of brain control of finger-level fine motor skills. We believe that these results represent an important step towards full and dexterous control of neural prosthetic devices.

Intelligent neuroprocessors for in-situ launch vehicle propulsion systems health management

NASA Technical Reports Server (NTRS)

Gulati, S.; Tawel, R.; Thakoor, A. P.

1993-01-01

Efficacy of existing on-board propulsion systems health management systems (HMS) are severely impacted by computational limitations (e.g., low sampling rates); paradigmatic limitations (e.g., low-fidelity logic/parameter redlining only, false alarms due to noisy/corrupted sensor signatures, preprogrammed diagnostics only); and telemetry bandwidth limitations on space/ground interactions. Ultra-compact/light, adaptive neural networks with massively parallel, asynchronous, fast reconfigurable and fault-tolerant information processing properties have already demonstrated significant potential for inflight diagnostic analyses and resource allocation with reduced ground dependence. In particular, they can automatically exploit correlation effects across multiple sensor streams (plume analyzer, flow meters, vibration detectors, etc.) so as to detect anomaly signatures that cannot be determined from the exploitation of single sensor. Furthermore, neural networks have already demonstrated the potential for impacting real-time fault recovery in vehicle subsystems by adaptively regulating combustion mixture/power subsystems and optimizing resource utilization under degraded conditions. A class of high-performance neuroprocessors, developed at JPL, that have demonstrated potential for next-generation HMS for a family of space transportation vehicles envisioned for the next few decades, including HLLV, NLS, and space shuttle is presented. Of fundamental interest are intelligent neuroprocessors for real-time plume analysis, optimizing combustion mixture-ratio, and feedback to hydraulic, pneumatic control systems. This class includes concurrently asynchronous reprogrammable, nonvolatile, analog neural processors with high speed, high bandwidth electronic/optical I/O interfaced, with special emphasis on NASA's unique requirements in terms of performance, reliability, ultra-high density ultra-compactness, ultra-light weight devices, radiation hardened devices, power stringency, and long life terms.

A compact integrated device for spatially selective optogenetic neural stimulation based on the Utah Optrode Array

NASA Astrophysics Data System (ADS)

Scharf, Robert; Reiche, Christopher F.; McAlinden, Niall; Cheng, Yunzhou; Xie, Enyuan; Sharma, Rohit; Tathireddy, Prashant; Rieth, Loren; Mathieson, Keith; Blair, Steve

2018-02-01

Optogenetics is a powerful tool for neural control, but controlled light delivery beyond the superficial structures of the brain remains a challenge. For this, we have developed an optrode array, which can be used for optogenetic stimulation of the deep layers of the cortex. The device consists of a 10×10 array of penetrating optical waveguides, which are predefined using BOROFLOAT® wafer dicing. A wet etch step is then used to achieve the desired final optrode dimensions, followed by heat treatment to smoothen the edges and the surface. The major challenge that we have addressed is delivering light through individual waveguides in a controlled and efficient fashion. Simply coupling the waveguides in the optrode array to a separately-fabricated μLED array leads to low coupling efficiency and significant light scattering in the optrode backplane and crosstalk to adjacent optrodes due to the large mismatch between the μLED and waveguide numerical aperture and the working distance between them. We mitigate stray light by reducing the thickness of the glass backplane and adding a silicon interposer layer with optical vias connecting the μLEDs to the optrodes. The interposer additionally provides mechanical stability required by very thin backplanes, while restricting the unwanted spread of light. Initial testing of light output from the optrodes confirms intensity levels sufficient for optogenetic neural activation. These results pave the way for future work, which will focus on optimization of light coupling and adding recording electrodes to each optrode shank to create a bidirectional optoelectronic interface.

Cortical control of intraspinal microstimulation: Toward a new approach for restoration of function after spinal cord injury.

PubMed

Shahdoost, Shahab; Frost, Shawn; Dunham, Caleb; DeJong, Stacey; Barbay, Scott; Nudo, Randolph; Mohseni, Pedram

2015-08-01

Approximately 6 million people in the United States are currently living with paralysis in which 23% of the cases are related to spinal cord injury (SCI). Miniaturized closed-loop neural interfaces have the potential for restoring function and mobility lost to debilitating neural injuries such as SCI by leveraging recent advancements in bioelectronics and a better understanding of the processes that underlie functional and anatomical reorganization in an injured nervous system. This paper describes our current progress toward developing a miniaturized brain-machine-spinal cord interface (BMSI) that converts in real time the neural command signals recorded from the cortical motor regions to electrical stimuli delivered to the spinal cord below the injury level. Using a combination of custom integrated circuit (IC) technology for corticospinal interfacing and field-programmable gate array (FPGA)-based technology for embedded signal processing, we demonstrate proof-of-concept of distinct muscle pattern activation via intraspinal microstimulation (ISMS) controlled in real time by intracortical neural spikes in an anesthetized laboratory rat.

Covalent bonding of YIGSR and RGD to PEDOT/PSS/MWCNT-COOH composite material to improve the neural interface.

PubMed

Wang, Kun; Tang, Rong-Yu; Zhao, Xiao-Bo; Li, Jun-Jie; Lang, Yi-Ran; Jiang, Xiao-Xia; Sun, Hong-Ji; Lin, Qiu-Xia; Wang, Chang-Yong

2015-11-28

The development of coating materials for neural interfaces has been a pursued to improve the electrical, mechanical and biological performances. For these goals, a bioactive coating was developed in this work featuring a poly(3,4-ethylenedioxythiophene) (PEDOT)/carbon nanotube (CNT) composite and covalently bonded YIGSR and RGD. Its biological effect and electrical characteristics were assessed in vivo on microwire arrays (MWA). The coated electrodes exhibited a significantly higher charge storage capacity (CSC) and lower electrochemical impedance at 1 kHz which are desired to improve the stimulating and recording performances, respectively. Acute neural recording experiments revealed that coated MWA possess a higher signal/noise ratio capturing spikes undetected by uncoated electrodes. Moreover, coated MWA possessed more active sites and single units, and the noise floor of coated electrodes was lower than that of uncoated electrodes. There is little information in the literature concerning the chronic performance of bioactively modified neural interfaces in vivo. Therefore in this work, chronic in vivo tests were conducted and the PEDOT/PSS/MWCNT-polypeptide coated arrays exhibited excellent performances with the highest mean maximal amplitude from day 4 to day 12 during which the acute response severely compromised the performance of the electrodes. In brief, we developed a simple method of covalently bonding YIGSR and RGD to a PEDOT/PSS/MWCNT-COOH composite improving both the biocompatibility and electrical performance of the neural interface. Our findings suggest that YIGSR and RGD modified PEDOT/PSS/MWCNT is a promising bioactivated composite coating for neural recording and stimulating.

Photovoltaic Pixels for Neural Stimulation: Circuit Models and Performance.

PubMed

Boinagrov, David; Lei, Xin; Goetz, Georges; Kamins, Theodore I; Mathieson, Keith; Galambos, Ludwig; Harris, James S; Palanker, Daniel

2016-02-01

Photovoltaic conversion of pulsed light into pulsed electric current enables optically-activated neural stimulation with miniature wireless implants. In photovoltaic retinal prostheses, patterns of near-infrared light projected from video goggles onto subretinal arrays of photovoltaic pixels are converted into patterns of current to stimulate the inner retinal neurons. We describe a model of these devices and evaluate the performance of photovoltaic circuits, including the electrode-electrolyte interface. Characteristics of the electrodes measured in saline with various voltages, pulse durations, and polarities were modeled as voltage-dependent capacitances and Faradaic resistances. The resulting mathematical model of the circuit yielded dynamics of the electric current generated by the photovoltaic pixels illuminated by pulsed light. Voltages measured in saline with a pipette electrode above the pixel closely matched results of the model. Using the circuit model, our pixel design was optimized for maximum charge injection under various lighting conditions and for different stimulation thresholds. To speed discharge of the electrodes between the pulses of light, a shunt resistor was introduced and optimized for high frequency stimulation.

Recent developments in wireless recording from the nervous system with ultrasonic neural dust (Conference Presentation)

NASA Astrophysics Data System (ADS)

Maharbiz, Michel M.

2017-05-01

The emerging field of bioelectronic medicine seeks methods for deciphering and modulating electrophysiological activity in the body to attain therapeutic effects at target organs. Current approaches to interfacing with peripheral nerves and muscles rely heavily on wires, creating problems for chronic use, while emerging wireless approaches lack the size scalability necessary to interrogate small-diameter nerves. Furthermore, conventional electrode-based technologies lack the capability to record from nerves with high spatial resolution or to record independently from many discrete sites within a nerve bundle. We recently demonstrated (Seo et al., arXiV, 2013; Seo et al., Neuron, 2016) "neural dust," a wireless and scalable ultrasonic backscatter system for powering and communicating with implanted bioelectronics. There, we showed that ultrasound is effective at delivering power to mm-scale devices in tissue; likewise, passive, battery-less communication using backscatter enabled high-fidelity transmission of electromyogram (EMG) and electroneurogram (ENG) signals from anesthetized rats. In this talk, I will review recent developments from my group and collaborators in this area.

EDITORIAL: Commercial opportunities for neural engineers

NASA Astrophysics Data System (ADS)

Cavuoto, James

2008-03-01

Research and academic professionals in neural engineering know well the promise the field offers for advancing our understanding of basic neuroscience and devising new therapies for treating neurological diseases and disorders. But there is also considerable commercial opportunity for new start-up companies in several areas of neural engineering. The neurotechnology industry, which includes firms that manufacture neuromodulation devices, neural prostheses, neurorehabilitation systems, and neurosensing devices, is forecast to grow to grow from 3.6 billion this year to 8.8 billion in 2012, according to a recently published market research study from Neurotech Reports. In recent years, there have been several successful spinoffs of neurotechnology startup firms that originated with research at universities and clinical institutions. In many cases, the academic researchers who invented the new technology or product innovation have stayed on with their startup firms after receiving funding from venture capital firms, or after going public. Among the most successful neurotechnology industry spinoffs in recent years were: Cyberkinetics Inc., Foxborough, MA, a manufacturer of brain-computer interface devices based on research at Brown University. John Donoghue, a professor and chairman of the department of neuroscience at Brown University and executive director of the brain science program at Brown, founded the company in 2001 and remains on board as the chief scientific officer. Synapse Biomedical, Inc., Oberlin, OH, a manufacturer of diaphragm pacing systems, based on research at Case Western Reserve University. Raymond Onders, director of minimal invasive surgery and associate professor at University Hospital Case Medical Center in Cleveland, was the primary researcher. He was helped by J. Thomas Mortimer, professor emeritus of biomedical engineering at Case, and it was Mortimer who came up with the name NeuRx for the device. Onders performed his first surgical implant of the device in 2000. Anthony Ignagni, who worked with Mortimer and Onders as project director and chief biomedical engineer, became a co-founder of Synapse and is currently president and CEO. Afferent Corp., Providence, RI, a manufacturer of sensory stimulation systems based on research at Boston University, Afferent's technology is based on work by James Collins, professor of biomedical engineering at Boston University, who showed that low-level stochastic, or random, vibrations improved sense of touch. Collins went on to demonstrate that generating a subthreshold noise in the sensory pathways with a random electrical stimulation improves detectability of weak mechanical stimuli. In 1999 entrepreneur Jason Harry licensed the stochastic resonance technology from Boston University and received help from the Community Technology Fund-the university's technology transfer incubator. NeuroNexus Technologies, Inc., Ann Arbor, MI, a manufacturer of implanted neural probes, based on a program at the University of Michigan. NeuroNexus was spun out of UM's Center for Neural Communications Technology. Daryl Kipke, head of the Neural Engineering Laboratory at the university, started up NeuroNexus with several colleagues and currently serves as president and CEO. Commercialization issues were discussed recently at a preconference workshop at the 2007 meeting of the International Neuromodulation Society in Acapulco, Mexico. In the session, which was chaired by Chris Coburn of the Cleveland Clinic, neurotech entrepreneurs John Bowers from Northstar Neuroscience and Ben Pless, formerly of NeuroPace, shared their experiences bringing neuromodulation therapies to market. Coburn related his observations from the Cleveland Clinic, which has spun off 22 companies over the last five years. He cited several factors that would influence a neurotech startup's market potential, such as identifying the regulatory pathway, any predicate devices that exist, and the revenue potential for potential investors. Bowers cited several factors that would be critical for the growth of the industry, including reaching out to the 'influential implanters' and pushing reimbursement based on quality of life improvements, rather than mortality. Pless provided an overview of patent-related issues affecting neuromodulation devices. He noted that there have been 2000 issued patents for neuromodulation devices, most of them involving the peripheral nervous system. The example set by these companies and other startups in the neurotechnology industry should remind neural engineering researchers that there are plenty of opportunities for commercial success based on promising research at university and clinical research laboratories. Given the wide range of help and information that is available to potential entrepreneurs in this field, we expect to see many more examples of neurotechnology spinoffs in the years ahead.

Ten-dimensional anthropomorphic arm control in a human brain-machine interface: difficulties, solutions, and limitations

NASA Astrophysics Data System (ADS)

Wodlinger, B.; Downey, J. E.; Tyler-Kabara, E. C.; Schwartz, A. B.; Boninger, M. L.; Collinger, J. L.

2015-02-01

Objective. In a previous study we demonstrated continuous translation, orientation and one-dimensional grasping control of a prosthetic limb (seven degrees of freedom) by a human subject with tetraplegia using a brain-machine interface (BMI). The current study, in the same subject, immediately followed the previous work and expanded the scope of the control signal by also extracting hand-shape commands from the two 96-channel intracortical electrode arrays implanted in the subject’s left motor cortex. Approach. Four new control signals, dictating prosthetic hand shape, replaced the one-dimensional grasping in the previous study, allowing the subject to control the prosthetic limb with ten degrees of freedom (three-dimensional (3D) translation, 3D orientation, four-dimensional hand shaping) simultaneously. Main results. Robust neural tuning to hand shaping was found, leading to ten-dimensional (10D) performance well above chance levels in all tests. Neural unit preferred directions were broadly distributed through the 10D space, with the majority of units significantly tuned to all ten dimensions, instead of being restricted to isolated domains (e.g. translation, orientation or hand shape). The addition of hand shaping emphasized object-interaction behavior. A fundamental component of BMIs is the calibration used to associate neural activity to intended movement. We found that the presence of an object during calibration enhanced successful shaping of the prosthetic hand as it closed around the object during grasping. Significance. Our results show that individual motor cortical neurons encode many parameters of movement, that object interaction is an important factor when extracting these signals, and that high-dimensional operation of prosthetic devices can be achieved with simple decoding algorithms. ClinicalTrials.gov Identifier: NCT01364480.

Open Ephys electroencephalography (Open Ephys  +  EEG): a modular, low-cost, open-source solution to human neural recording

NASA Astrophysics Data System (ADS)

Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie

2017-06-01

Objective. Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Approach. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys  +  EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. Main results. The Open Ephys  +  EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys  +  EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Significance. Open Ephys  +  EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.

Open Ephys electroencephalography (Open Ephys  +  EEG): a modular, low-cost, open-source solution to human neural recording.

PubMed

Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie

2017-06-01

Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys  +  EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. The Open Ephys  +  EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys  +  EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Open Ephys  +  EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.

A Brain-Based Communication and Orientation System

DTIC Science & Technology

2014-10-06

Review of the BCI Competition IV, Frontiers in Neuroscience, ( 2012): 0. doi: 10.3389/fnins.2012.00055 Eric C. Leuthardt, Xiao-Mei Pei, Jonathan...hardware and software for brain– computer interfaces ( BCIs ), Journal of Neural Engineering, (04 2011): 1. doi: 10.1088/1741-2560/8/2/025001...Cincotti, G. Schalk, Peter Brunner. Current Trends in Brain–Computer Interface ( BCI ) Research and Development, Journal of Neural Engineering, (3 2011

Network device interface for digitally interfacing data channels to a controller a via network

NASA Technical Reports Server (NTRS)

Konz, Daniel W. (Inventor); Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Winkelmann, Joseph P. (Inventor)

2006-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. In one embodiment, the bus controller transmits messages to the network device interface containing a plurality of bits having a value defined by a transition between first and second states in the bits. The network device interface determines timing of the data sequence of the message and uses the determined timing to communicate with the bus controller.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Konz, Daniel W. (Inventor); Winkelmann, Joseph P. (Inventor)

2005-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted by the network device interface into digital signals and transmitted back to the controller. In one advantageous embodiment, the network device interface uses a specialized protocol for communicating across the network bus that uses a low-level instruction set and has low overhead for data communication.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Ellerbrock, Philip J. (Inventor); Winkelmann, Joseph P. (Inventor); Grant, Robert L. (Inventor); Konz, Daniel W. (Inventor)

2006-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted by the network device interface into digital signals and transmitted back to the controller. In one advantageous embodiment, the network device interface is a state machine, such as an ASIC, that operates independent of a processor in communicating with the bus controller and data channels.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Ellerbrock, Philip J. (Inventor); Konz, Daniel W. (Inventor); Winkelmann, Joseph P. (Inventor); Grant, Robert L. (Inventor)

2004-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted by the network device interface into digital signals and transmitted back to the controller. In one advantageous embodiment, the network device interface uses a specialized protocol for communicating across the network bus that uses a low-level instruction set and has low overhead for data communication.

Electronic Neural Networks

NASA Technical Reports Server (NTRS)

Thakoor, Anil

1990-01-01

Viewgraphs on electronic neural networks for space station are presented. Topics covered include: electronic neural networks; electronic implementations; VLSI/thin film hybrid hardware for neurocomputing; computations with analog parallel processing; features of neuroprocessors; applications of neuroprocessors; neural network hardware for terrain trafficability determination; a dedicated processor for path planning; neural network system interface; neural network for robotic control; error backpropagation algorithm for learning; resource allocation matrix; global optimization neuroprocessor; and electrically programmable read only thin-film synaptic array.

System and method for interfacing large-area electronics with integrated circuit devices

DOEpatents

Verma, Naveen; Glisic, Branko; Sturm, James; Wagner, Sigurd

2016-07-12

A system and method for interfacing large-area electronics with integrated circuit devices is provided. The system may be implemented in an electronic device including a large area electronic (LAE) device disposed on a substrate. An integrated circuit IC is disposed on the substrate. A non-contact interface is disposed on the substrate and coupled between the LAE device and the IC. The non-contact interface is configured to provide at least one of a data acquisition path or control path between the LAE device and the IC.

Optimal feedback control successfully explains changes in neural modulations during experiments with brain-machine interfaces.

PubMed

Benyamini, Miri; Zacksenhouse, Miriam

2015-01-01

Recent experiments with brain-machine-interfaces (BMIs) indicate that the extent of neural modulations increased abruptly upon starting to operate the interface, and especially after the monkey stopped moving its hand. In contrast, neural modulations that are correlated with the kinematics of the movement remained relatively unchanged. Here we demonstrate that similar changes are produced by simulated neurons that encode the relevant signals generated by an optimal feedback controller during simulated BMI experiments. The optimal feedback controller relies on state estimation that integrates both visual and proprioceptive feedback with prior estimations from an internal model. The processing required for optimal state estimation and control were conducted in the state-space, and neural recording was simulated by modeling two populations of neurons that encode either only the estimated state or also the control signal. Spike counts were generated as realizations of doubly stochastic Poisson processes with linear tuning curves. The model successfully reconstructs the main features of the kinematics and neural activity during regular reaching movements. Most importantly, the activity of the simulated neurons successfully reproduces the observed changes in neural modulations upon switching to brain control. Further theoretical analysis and simulations indicate that increasing the process noise during normal reaching movement results in similar changes in neural modulations. Thus, we conclude that the observed changes in neural modulations during BMI experiments can be attributed to increasing process noise associated with the imperfect BMI filter, and, more directly, to the resulting increase in the variance of the encoded signals associated with state estimation and the required control signal.

Optimal feedback control successfully explains changes in neural modulations during experiments with brain-machine interfaces

PubMed Central

Benyamini, Miri; Zacksenhouse, Miriam

2015-01-01

Recent experiments with brain-machine-interfaces (BMIs) indicate that the extent of neural modulations increased abruptly upon starting to operate the interface, and especially after the monkey stopped moving its hand. In contrast, neural modulations that are correlated with the kinematics of the movement remained relatively unchanged. Here we demonstrate that similar changes are produced by simulated neurons that encode the relevant signals generated by an optimal feedback controller during simulated BMI experiments. The optimal feedback controller relies on state estimation that integrates both visual and proprioceptive feedback with prior estimations from an internal model. The processing required for optimal state estimation and control were conducted in the state-space, and neural recording was simulated by modeling two populations of neurons that encode either only the estimated state or also the control signal. Spike counts were generated as realizations of doubly stochastic Poisson processes with linear tuning curves. The model successfully reconstructs the main features of the kinematics and neural activity during regular reaching movements. Most importantly, the activity of the simulated neurons successfully reproduces the observed changes in neural modulations upon switching to brain control. Further theoretical analysis and simulations indicate that increasing the process noise during normal reaching movement results in similar changes in neural modulations. Thus, we conclude that the observed changes in neural modulations during BMI experiments can be attributed to increasing process noise associated with the imperfect BMI filter, and, more directly, to the resulting increase in the variance of the encoded signals associated with state estimation and the required control signal. PMID:26042002

Model validation of untethered, ultrasonic neural dust motes for cortical recording.

PubMed

Seo, Dongjin; Carmena, Jose M; Rabaey, Jan M; Maharbiz, Michel M; Alon, Elad

2015-04-15

A major hurdle in brain-machine interfaces (BMI) is the lack of an implantable neural interface system that remains viable for a substantial fraction of the user's lifetime. Recently, sub-mm implantable, wireless electromagnetic (EM) neural interfaces have been demonstrated in an effort to extend system longevity. However, EM systems do not scale down in size well due to the severe inefficiency of coupling radio-waves at those scales within tissue. This paper explores fundamental system design trade-offs as well as size, power, and bandwidth scaling limits of neural recording systems built from low-power electronics coupled with ultrasonic power delivery and backscatter communication. Such systems will require two fundamental technology innovations: (1) 10-100 μm scale, free-floating, independent sensor nodes, or neural dust, that detect and report local extracellular electrophysiological data via ultrasonic backscattering and (2) a sub-cranial ultrasonic interrogator that establishes power and communication links with the neural dust. We provide experimental verification that the predicted scaling effects follow theory; (127 μm)(3) neural dust motes immersed in water 3 cm from the interrogator couple with 0.002064% power transfer efficiency and 0.04246 ppm backscatter, resulting in a maximum received power of ∼0.5 μW with ∼1 nW of change in backscatter power with neural activity. The high efficiency of ultrasonic transmission can enable the scaling of the sensing nodes down to 10s of micrometer. We conclude with a brief discussion of the application of neural dust for both central and peripheral nervous system recordings, and perspectives on future research directions. Copyright © 2014 Elsevier B.V. All rights reserved.

Intelligent subsystem interface for modular hardware system

NASA Technical Reports Server (NTRS)

Caffrey, Robert T. (Inventor); Krening, Douglas N. (Inventor); Lannan, Gregory B. (Inventor); Schneiderwind, Michael J. (Inventor); Schneiderwind, Robert A. (Inventor)

2000-01-01

A single chip application specific integrated circuit (ASIC) which provides a flexible, modular interface between a subsystem and a standard system bus. The ASIC includes a microcontroller/microprocessor, a serial interface for connection to the bus, and a variety of communications interface devices available for coupling to the subsystem. A three-bus architecture, utilizing arbitration, provides connectivity within the ASIC and between the ASIC and the subsystem. The communication interface devices include UART (serial), parallel, analog, and external device interface utilizing bus connections paired with device select signals. A low power (sleep) mode is provided as is a processor disable option.

Engineering platform and experimental protocol for design and evaluation of a neurally-controlled powered transfemoral prosthesis.

PubMed

Zhang, Fan; Liu, Ming; Harper, Stephen; Lee, Michael; Huang, He

2014-07-22

To enable intuitive operation of powered artificial legs, an interface between user and prosthesis that can recognize the user's movement intent is desired. A novel neural-machine interface (NMI) based on neuromuscular-mechanical fusion developed in our previous study has demonstrated a great potential to accurately identify the intended movement of transfemoral amputees. However, this interface has not yet been integrated with a powered prosthetic leg for true neural control. This study aimed to report (1) a flexible platform to implement and optimize neural control of powered lower limb prosthesis and (2) an experimental setup and protocol to evaluate neural prosthesis control on patients with lower limb amputations. First a platform based on a PC and a visual programming environment were developed to implement the prosthesis control algorithms, including NMI training algorithm, NMI online testing algorithm, and intrinsic control algorithm. To demonstrate the function of this platform, in this study the NMI based on neuromuscular-mechanical fusion was hierarchically integrated with intrinsic control of a prototypical transfemoral prosthesis. One patient with a unilateral transfemoral amputation was recruited to evaluate our implemented neural controller when performing activities, such as standing, level-ground walking, ramp ascent, and ramp descent continuously in the laboratory. A novel experimental setup and protocol were developed in order to test the new prosthesis control safely and efficiently. The presented proof-of-concept platform and experimental setup and protocol could aid the future development and application of neurally-controlled powered artificial legs.

Flexible neural interfaces with integrated stiffening shank

DOEpatents

Tooker, Angela C.; Felix, Sarah H.; Pannu, Satinderpall S.; Shah, Kedar G.; Sheth, Heeral; Tolosa, Vanessa

2016-07-26

A neural interface includes a first dielectric material having at least one first opening for a first electrical conducting material, a first electrical conducting material in the first opening, and at least one first interconnection trace electrical conducting material connected to the first electrical conducting material. A stiffening shank material is located adjacent the first dielectric material, the first electrical conducting material, and the first interconnection trace electrical conducting material.

Nanowire-Based Electrode for Acute In Vivo Neural Recordings in the Brain

PubMed Central

Suyatin, Dmitry B.; Wallman, Lars; Thelin, Jonas; Prinz, Christelle N.; Jörntell, Henrik; Samuelson, Lars; Montelius, Lars; Schouenborg, Jens

2013-01-01

We present an electrode, based on structurally controlled nanowires, as a first step towards developing a useful nanostructured device for neurophysiological measurements in vivo. The sensing part of the electrode is made of a metal film deposited on top of an array of epitaxially grown gallium phosphide nanowires. We achieved the first functional testing of the nanowire-based electrode by performing acute in vivo recordings in the rat cerebral cortex and withstanding multiple brain implantations. Due to the controllable geometry of the nanowires, this type of electrode can be used as a model system for further analysis of the functional properties of nanostructured neuronal interfaces in vivo. PMID:23431387

Interfacing with Neural Activity via Femtosecond Laser Stimulation of Drug-Encapsulating Liposomal Nanostructures

PubMed Central

Mackay, Sean M.; Wui Tan, Eng

2016-01-01

External control over rapid and precise release of chemicals in the brain potentially provides a powerful interface with neural activity. Optical manipulation techniques, such as optogenetics and caged compounds, enable remote control of neural activity and behavior with fine spatiotemporal resolution. However, these methods are limited to chemicals that are naturally present in the brain or chemically suitable for caging. Here, we demonstrate the ability to interface with neural functioning via a wide range of neurochemicals released by stimulating loaded liposomal nanostructures with femtosecond lasers. Using a commercial two-photon microscope, we released inhibitory or excitatory neurochemicals to evoke subthreshold and suprathreshold changes in membrane potential in a live mouse brain slice. The responses were repeatable and could be controlled by adjusting laser stimulation characteristics. We also demonstrate the release of a wider range of chemicals—which previously were impossible to release by optogenetics or uncaging—including synthetic analogs of naturally occurring neurochemicals. In particular, we demonstrate the release of a synthetic receptor-specific agonist that exerts physiological effects on long-term synaptic plasticity. Further, we show that the loaded liposomal nanostructures remain functional for weeks in a live mouse. In conclusion, we demonstrate new techniques capable of interfacing with live neurons, and extendable to in vivo applications. PMID:27896311

Boolean and brain-inspired computing using spin-transfer torque devices

NASA Astrophysics Data System (ADS)

Fan, Deliang

Several completely new approaches (such as spintronic, carbon nanotube, graphene, TFETs, etc.) to information processing and data storage technologies are emerging to address the time frame beyond current Complementary Metal-Oxide-Semiconductor (CMOS) roadmap. The high speed magnetization switching of a nano-magnet due to current induced spin-transfer torque (STT) have been demonstrated in recent experiments. Such STT devices can be explored in compact, low power memory and logic design. In order to truly leverage STT devices based computing, researchers require a re-think of circuit, architecture, and computing model, since the STT devices are unlikely to be drop-in replacements for CMOS. The potential of STT devices based computing will be best realized by considering new computing models that are inherently suited to the characteristics of STT devices, and new applications that are enabled by their unique capabilities, thereby attaining performance that CMOS cannot achieve. The goal of this research is to conduct synergistic exploration in architecture, circuit and device levels for Boolean and brain-inspired computing using nanoscale STT devices. Specifically, we first show that the non-volatile STT devices can be used in designing configurable Boolean logic blocks. We propose a spin-memristor threshold logic (SMTL) gate design, where memristive cross-bar array is used to perform current mode summation of binary inputs and the low power current mode spintronic threshold device carries out the energy efficient threshold operation. Next, for brain-inspired computing, we have exploited different spin-transfer torque device structures that can implement the hard-limiting and soft-limiting artificial neuron transfer functions respectively. We apply such STT based neuron (or 'spin-neuron') in various neural network architectures, such as hierarchical temporal memory and feed-forward neural network, for performing "human-like" cognitive computing, which show more than two orders of lower energy consumption compared to state of the art CMOS implementation. Finally, we show the dynamics of injection locked Spin Hall Effect Spin-Torque Oscillator (SHE-STO) cluster can be exploited as a robust multi-dimensional distance metric for associative computing, image/ video analysis, etc. Our simulation results show that the proposed system architecture with injection locked SHE-STOs and the associated CMOS interface circuits can be suitable for robust and energy efficient associative computing and pattern matching.

ANNarchy: a code generation approach to neural simulations on parallel hardware

PubMed Central

Vitay, Julien; Dinkelbach, Helge Ü.; Hamker, Fred H.

2015-01-01

Many modern neural simulators focus on the simulation of networks of spiking neurons on parallel hardware. Another important framework in computational neuroscience, rate-coded neural networks, is mostly difficult or impossible to implement using these simulators. We present here the ANNarchy (Artificial Neural Networks architect) neural simulator, which allows to easily define and simulate rate-coded and spiking networks, as well as combinations of both. The interface in Python has been designed to be close to the PyNN interface, while the definition of neuron and synapse models can be specified using an equation-oriented mathematical description similar to the Brian neural simulator. This information is used to generate C++ code that will efficiently perform the simulation on the chosen parallel hardware (multi-core system or graphical processing unit). Several numerical methods are available to transform ordinary differential equations into an efficient C++code. We compare the parallel performance of the simulator to existing solutions. PMID:26283957

RatCar system for estimating locomotion states using neural signals with parameter monitoring: Vehicle-formed brain-machine interfaces for rat.

PubMed

Fukayama, Osamu; Taniguchi, Noriyuki; Suzuki, Takafumi; Mabuchi, Kunihiko

2008-01-01

An online brain-machine interface (BMI) in the form of a small vehicle, the 'RatCar,' has been developed. A rat had neural electrodes implanted in its primary motor cortex and basal ganglia regions to continuously record neural signals. Then, a linear state space model represents a correlation between the recorded neural signals and locomotion states (i.e., moving velocity and azimuthal variances) of the rat. The model parameters were set so as to minimize estimation errors, and the locomotion states were estimated from neural firing rates using a Kalman filter algorithm. The results showed a small oscillation to achieve smooth control of the vehicle in spite of fluctuating firing rates with noises applied to the model. Major variation of the model variables converged in a first 30 seconds of the experiments and lasted for the entire one hour session.

Miniaturized neural interfaces and implants

NASA Astrophysics Data System (ADS)

Stieglitz, Thomas; Boretius, Tim; Ordonez, Juan; Hassler, Christina; Henle, Christian; Meier, Wolfgang; Plachta, Dennis T. T.; Schuettler, Martin

2012-03-01

Neural prostheses are technical systems that interface nerves to treat the symptoms of neurological diseases and to restore sensory of motor functions of the body. Success stories have been written with the cochlear implant to restore hearing, with spinal cord stimulators to treat chronic pain as well as urge incontinence, and with deep brain stimulators in patients suffering from Parkinson's disease. Highly complex neural implants for novel medical applications can be miniaturized either by means of precision mechanics technologies using known and established materials for electrodes, cables, and hermetic packages or by applying microsystems technologies. Examples for both approaches will be introduced and discussed. Electrode arrays for recording of electrocorticograms during presurgical epilepsy diagnosis have been manufactured using approved materials and a marking laser to achieve an integration density that is adequate in the context of brain machine interfaces, e.g. on the motor cortex. Microtechnologies have to be used for further miniaturization to develop polymer-based flexible and light weighted electrode arrays to interface the peripheral and central nervous system. Polyimide as substrate and insulation material will be discussed as well as several application examples for nerve interfaces like cuffs, filament like electrodes and large arrays for subdural implantation.

Encapsulating Elastically Stretchable Neural Interfaces: Yield, Resolution, and Recording/Stimulation of Neural Activity

PubMed Central

Morrison, Barclay; Goletiani, Cezar; Yu, Zhe; Wagner, Sigurd

2013-01-01

A high resolution elastically stretchable microelectrode array (SMEA) to interface with neural tissue is described. The SMEA consists of an elastomeric substrate, such as poly(dimethylsiloxane) (PDMS), elastically stretchable gold conductors, and an electrically insulating encapsulating layer in which contact holes are opened. We demonstrate the feasibility of producing contact holes with 40 µm × 40 µm openings, show why the adhesion of the encapsulation layer to the underlying silicone substrate is weakened during contact hole fabrication, and provide remedies. These improvements result in greatly increased fabrication yield and reproducibility. An SMEA with 28 microelectrodes was fabricated. The contact holes (100 µm × 100 µm) in the encapsulation layer are only ~10% the size of the previous generation, allowing a larger number of microelectrodes per unit area, thus affording the capability to interface with a smaller neural population per electrode. This new SMEA is used to record spontaneous and evoked activity in organotypic hippocampal tissue slices at 0% strain before stretching, at 5 % and 10 % equibiaxial strain, and again at 0% strain after relaxation. The noise of the recordings increases with increasing strain. The frequency of spontaneous neural activity also increases when the SMEA is stretched. Upon relaxation, the noise returns to pre-stretch levels, while the frequency of neural activity remains elevated. Stimulus-response curves at each strain level are measured. The SMEA shows excellent biocompatibility for at least two weeks. PMID:24093006

Efficient Decoding With Steady-State Kalman Filter in Neural Interface Systems

PubMed Central

Malik, Wasim Q.; Truccolo, Wilson; Brown, Emery N.; Hochberg, Leigh R.

2011-01-01

The Kalman filter is commonly used in neural interface systems to decode neural activity and estimate the desired movement kinematics. We analyze a low-complexity Kalman filter implementation in which the filter gain is approximated by its steady-state form, computed offline before real-time decoding commences. We evaluate its performance using human motor cortical spike train data obtained from an intracortical recording array as part of an ongoing pilot clinical trial. We demonstrate that the standard Kalman filter gain converges to within 95% of the steady-state filter gain in 1.5 ± 0.5 s (mean ± s.d.). The difference in the intended movement velocity decoded by the two filters vanishes within 5 s, with a correlation coefficient of 0.99 between the two decoded velocities over the session length. We also find that the steady-state Kalman filter reduces the computational load (algorithm execution time) for decoding the firing rates of 25 ± 3 single units by a factor of 7.0 ± 0.9. We expect that the gain in computational efficiency will be much higher in systems with larger neural ensembles. The steady-state filter can thus provide substantial runtime efficiency at little cost in terms of estimation accuracy. This far more efficient neural decoding approach will facilitate the practical implementation of future large-dimensional, multisignal neural interface systems. PMID:21078582

Estimation of Muscle Force Based on Neural Drive in a Hemispheric Stroke Survivor.

PubMed

Dai, Chenyun; Zheng, Yang; Hu, Xiaogang

2018-01-01

Robotic assistant-based therapy holds great promise to improve the functional recovery of stroke survivors. Numerous neural-machine interface techniques have been used to decode the intended movement to control robotic systems for rehabilitation therapies. In this case report, we tested the feasibility of estimating finger extensor muscle forces of a stroke survivor, based on the decoded descending neural drive through population motoneuron discharge timings. Motoneuron discharge events were obtained by decomposing high-density surface electromyogram (sEMG) signals of the finger extensor muscle. The neural drive was extracted from the normalized frequency of the composite discharge of the motoneuron pool. The neural-drive-based estimation was also compared with the classic myoelectric-based estimation. Our results showed that the neural-drive-based approach can better predict the force output, quantified by lower estimation errors and higher correlations with the muscle force, compared with the myoelectric-based estimation. Our findings suggest that the neural-drive-based approach can potentially be used as a more robust interface signal for robotic therapies during the stroke rehabilitation.

Neural electrode resilience against dielectric damage may be improved by use of highly doped silicon as a conductive material.

PubMed

Caldwell, Ryan; Sharma, Rohit; Takmakov, Pavel; Street, Matthew G; Solzbacher, Florian; Tathireddy, Prashant; Rieth, Loren

2018-01-01

Dielectric damage occurring in vivo to neural electrodes, leading to conductive material exposure and impedance reduction over time, limits the functional lifetime and clinical viability of neuroprosthetics. We used silicon micromachined Utah Electrode Arrays (UEAs) with iridium oxide (IrO x ) tip metallization and parylene C dielectric encapsulation to understand the factors affecting device resilience and drive improvements. In vitro impedance measurements and finite element analyses were conducted to evaluate how exposed surface area of silicon and IrO x affect UEA properties. Through an aggressive in vitro reactive accelerated aging (RAA) protocol, in vivo parylene degradation was simulated on UEAs to explore agreement with our models. Electrochemical properties of silicon and other common electrode materials were compared to help inform material choice in future neural electrode designs. Exposure of silicon on UEAs was found to primarily affect impedance at frequencies >1kHz, while characteristics at 1 kHz and below were largely unchanged. Post-RAA impedance reduction of UEAs was mitigated in cases where dielectric damage was more likely to expose silicon instead of IrO x . Silicon was found to have a per-area electrochemical impedance >10×higher than many common electrode materials regardless of doping level and resistivity, making it best suited for use as a low-shunting conductor. Non-semiconductor electrode materials commonly used in neural electrode design are more susceptible to shunting neural interface signals through dielectric defects, compared to highly doped silicon. Strategic use of silicon and similar materials may increase neural electrode robustness against encapsulation failures. Copyright © 2017 Elsevier B.V. All rights reserved.

Fast Neural Solution Of A Nonlinear Wave Equation

NASA Technical Reports Server (NTRS)

Barhen, Jacob; Toomarian, Nikzad

1996-01-01

Neural algorithm for simulation of class of nonlinear wave phenomena devised. Numerically solves special one-dimensional case of Korteweg-deVries equation. Intended to be executed rapidly by neural network implemented as charge-coupled-device/charge-injection device, very-large-scale integrated-circuit analog data processor of type described in "CCD/CID Processors Would Offer Greater Precision" (NPO-18972).

Polyhydroxyalkanoate/carbon nanotube nanocomposites: flexible electrically conducting elastomers for neural applications.

PubMed

Vallejo-Giraldo, Catalina; Pugliese, Eugenia; Larrañaga, Aitor; Fernandez-Yague, Marc A; Britton, James J; Trotier, Alexandre; Tadayyon, Ghazal; Kelly, Adriona; Rago, Ilaria; Sarasua, Jose-Ramon; Dowd, Eilís; Quinlan, Leo R; Pandit, Abhay; Biggs, Manus Jp

2016-10-01

Medium chain length-polyhydroxyalkanoate/multi-walled carbon nanotube (MWCNTs) nanocomposites with a range of mechanical and electrochemical properties were fabricated via assisted dispersion and solvent casting, and their suitability as neural interface biomaterials was investigated. Mechanical and electrical properties of medium chain length-polyhydroxyalkanoate/MWCNTs nanocomposite films were evaluated by tensile test and electrical impedance spectroscopy, respectively. Primary rat mesencephalic cells were seeded on the composites and quantitative immunostaining of relevant neural biomarkers, and electrical stimulation studies were performed. Incorporation of MWCNTs to the polymeric matrix modulated the mechanical and electrical properties of resulting composites, and promoted differential cell viability, morphology and function as a function of MWCNT concentration. This study demonstrates the feasibility of a green thermoplastic MWCNTs nanocomposite for potential use in neural interfacing applications.

Engineering the Brain: Ethical Issues and the Introduction of Neural Devices.

PubMed

Klein, Eran; Brown, Tim; Sample, Matthew; Truitt, Anjali R; Goering, Sara

2015-01-01

Neural devices now under development stand to interact with and alter the human brain in ways that may challenge standard notions of identity, normality, authority, responsibility, privacy and justice.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Konz, Daniel W. (Inventor); Winkelmann, Joseph P. (Inventor); Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor)

2007-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is converted into digital signals and transmitted to the controller. In some embodiments, network device interfaces associated with different data channels coordinate communications with the other interfaces based on either a transition in a command message sent by the bus controller or a synchronous clock signal.

Brain-Computer Interface with Inhibitory Neurons Reveals Subtype-Specific Strategies.

PubMed

Mitani, Akinori; Dong, Mingyuan; Komiyama, Takaki

2018-01-08

Brain-computer interfaces have seen an increase in popularity due to their potential for direct neuroprosthetic applications for amputees and disabled individuals. Supporting this promise, animals-including humans-can learn even arbitrary mapping between the activity of cortical neurons and movement of prosthetic devices [1-4]. However, the performance of neuroprosthetic device control has been nowhere near that of limb control in healthy individuals, presenting a dire need to improve the performance. One potential limitation is the fact that previous work has not distinguished diverse cell types in the neocortex, even though different cell types possess distinct functions in cortical computations [5-7] and likely distinct capacities to control brain-computer interfaces. Here, we made a first step in addressing this issue by tracking the plastic changes of three major types of cortical inhibitory neurons (INs) during a neuron-pair operant conditioning task using two-photon imaging of IN subtypes expressing GCaMP6f. Mice were rewarded when the activity of the positive target neuron (N+) exceeded that of the negative target neuron (N-) beyond a set threshold. Mice improved performance with all subtypes, but the strategies were subtype specific. When parvalbumin (PV)-expressing INs were targeted, the activity of N- decreased. However, targeting of somatostatin (SOM)- and vasoactive intestinal peptide (VIP)-expressing INs led to an increase of the N+ activity. These results demonstrate that INs can be individually modulated in a subtype-specific manner and highlight the versatility of neural circuits in adapting to new demands by using cell-type-specific strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Electronic device aspects of neural network memories

NASA Technical Reports Server (NTRS)

Lambe, J.; Moopenn, A.; Thakoor, A. P.

1985-01-01

The basic issues related to the electronic implementation of the neural network model (NNM) for content addressable memories are examined. A brief introduction to the principles of the NNM is followed by an analysis of the information storage of the neural network in the form of a binary connection matrix and the recall capability of such matrix memories based on a hardware simulation study. In addition, materials and device architecture issues involved in the future realization of such networks in VLSI-compatible ultrahigh-density memories are considered. A possible space application of such devices would be in the area of large-scale information storage without mechanical devices.

Development of a simulated smart pump interface.

PubMed

Elias, Beth L; Moss, Jacqueline A; Shih, Alan; Dillavou, Marcus

2014-01-01

Medical device user interfaces are increasingly complex, resulting in a need for evaluation in clinicallyaccurate settings. Simulation of these interfaces can allow for evaluation, training, and use for research without the risk of harming patients and with a significant cost reduction over using the actual medical devices. This pilot project was phase 1 of a study to define and evaluate a methodology for development of simulated medical device interface technology to be used for education, device development, and research. Digital video and audio recordings of interface interactions were analyzed to develop a model of a smart intravenous medication infusion pump user interface. This model was used to program a high-fidelity simulated smart intravenous medication infusion pump user interface on an inexpensive netbook platform.

Wireless Power Transfer Strategies for Implantable Bioelectronics.

PubMed

Agarwal, Kush; Jegadeesan, Rangarajan; Guo, Yong-Xin; Thakor, Nitish V

2017-01-01

Neural implants have emerged over the last decade as highly effective solutions for the treatment of dysfunctions and disorders of the nervous system. These implants establish a direct, often bidirectional, interface to the nervous system, both sensing neural signals and providing therapeutic treatments. As a result of the technological progress and successful clinical demonstrations, completely implantable solutions have become a reality and are now commercially available for the treatment of various functional disorders. Central to this development is the wireless power transfer (WPT) that has enabled implantable medical devices (IMDs) to function for extended durations in mobile subjects. In this review, we present the theory, link design, and challenges, along with their probable solutions for the traditional near-field resonant inductively coupled WPT, capacitively coupled short-ranged WPT, and more recently developed ultrasonic, mid-field, and far-field coupled WPT technologies for implantable applications. A comparison of various power transfer methods based on their power budgets and WPT range follows. Power requirements of specific implants like cochlear, retinal, cortical, and peripheral are also considered and currently available IMD solutions are discussed. Patient's safety concerns with respect to electrical, biological, physical, electromagnetic interference, and cyber security from an implanted neurotech device are also explored in this review. Finally, we discuss and anticipate future developments that will enhance the capabilities of current-day wirelessly powered implants and make them more efficient and integrable with other electronic components in IMDs.

The development of neural stimulators: a review of preclinical safety and efficacy studies.

PubMed

Shepherd, Robert K; Villalobos, Joel; Burns, Owen; Nayagam, David

2018-05-14

Given the rapid expansion of the field of neural stimulation and the rigorous regulatory approval requirements required before these devices can be applied clinically, it is important that there is clarity around conducting preclinical safety and efficacy studies required for the development of this technology. The present review examines basic design principles associated with the development of a safe neural stimulator and describes the suite of preclinical safety studies that need to be considered when taking a device to clinical trial. Neural stimulators are active implantable devices that provide therapeutic intervention, sensory feedback or improved motor control via electrical stimulation of neural or neuro-muscular tissue in response to trauma or disease. Because of their complexity, regulatory bodies classify these devices in the highest risk category (Class III), and they are therefore required to go through a rigorous regulatory approval process before progressing to market. The successful development of these devices is achieved through close collaboration across disciplines including engineers, scientists and a surgical/clinical team, and the adherence to clear design principles. Preclinical studies form one of several key components in the development pathway from concept to product release of neural stimulators. Importantly, these studies provide iterative feedback in order to optimise the final design of the device. Key components of any preclinical evaluation include: in vitro studies that are focussed on device reliability and include accelerated testing under highly controlled environments; in vivo studies using animal models of the disease or injury in order to assess safety and, given an appropriate animal model, the efficacy of the technology under both passive and electrically active conditions; and human cadaver and ex vivo studies designed to ensure the device's form factor conforms to human anatomy, to optimise the surgical approach and to develop any specialist surgical tooling required. The pipeline from concept to commercialisation of these devices is long and expensive; careful attention to both device design and its preclinical evaluation will have significant impact on the duration and cost associated with taking a device through to commercialisation. Carefully controlled in vitro and in vivo studies together with ex vivo and human cadaver trials are key components of a thorough preclinical evaluation of any new neural stimulator. © 2018 IOP Publishing Ltd.

Modeling the Electrode-Neuron Interface of Cochlear Implants: Effects of Neural Survival, Electrode Placement, and the Partial Tripolar Configuration

PubMed Central

Goldwyn, Joshua H.; Bierer, Steven M.; Bierer, Julie A.

2010-01-01

The partial tripolar electrode configuration is a relatively novel stimulation strategies that can generate more spatially focused electric fields than the commonly used monopolar configuration. Focused stimulation strategies should improve spectral resolution in cochlear implant users, but may also be more sensitive to local irregularities in the electrode-neuron interface. In this study, we develop a practical computer model of cochlear implant stimulation that can simulate neural activation in a simplified cochlear geometry and we relate the resulting patterns of neural activity to basic psychophysical measures. We examine how two types of local irregularities in the electrode-neuron interface, variations in spiral ganglion nerve density and electrode position within the scala tympani, affect the simulated neural activation patterns and how these patterns change with electrode configuration. The model shows that higher partial tripolar fractions activate more spatially restricted populations of neurons at all current levels and require higher current levels to excite a given number of neurons. We find that threshold levels are more sensitive at high partial tripolar fractions to both types of irregularities, but these effects are not independent. In particular, at close electrode-neuron distances, activation is typically more spatially localized which leads to a greater influence of neural dead regions. PMID:20580801

A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

PubMed Central

Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2014-01-01

Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

Spectral feature extraction of EEG signals and pattern recognition during mental tasks of 2-D cursor movements for BCI using SVM and ANN.

PubMed

Bascil, M Serdar; Tesneli, Ahmet Y; Temurtas, Feyzullah

2016-09-01

Brain computer interface (BCI) is a new communication way between man and machine. It identifies mental task patterns stored in electroencephalogram (EEG). So, it extracts brain electrical activities recorded by EEG and transforms them machine control commands. The main goal of BCI is to make available assistive environmental devices for paralyzed people such as computers and makes their life easier. This study deals with feature extraction and mental task pattern recognition on 2-D cursor control from EEG as offline analysis approach. The hemispherical power density changes are computed and compared on alpha-beta frequency bands with only mental imagination of cursor movements. First of all, power spectral density (PSD) features of EEG signals are extracted and high dimensional data reduced by principle component analysis (PCA) and independent component analysis (ICA) which are statistical algorithms. In the last stage, all features are classified with two types of support vector machine (SVM) which are linear and least squares (LS-SVM) and three different artificial neural network (ANN) structures which are learning vector quantization (LVQ), multilayer neural network (MLNN) and probabilistic neural network (PNN) and mental task patterns are successfully identified via k-fold cross validation technique.

EDITORIAL: Special issue on medical bionics Special issue on medical bionics

NASA Astrophysics Data System (ADS)

Shepherd, Robert K.; D, Ph

2009-12-01

This special section of the Journal of Neural Engineering contains eight invited papers presented as part of the inaugural conference `Medical Bionics: A New Paradigm for Human Health' held in the beautiful seaside village of Lorne, Victoria, Australia from 16-19 November 2008. This meeting formed part of the Sir Mark Oliphant International Conference Series (www.oliphant.org.au) and was generously supported by the Department of Innovation, Industry, Science and Research of the Australian Government, the Australian Academy of Science and the Australian Academy of Technological Sciences and Engineering. This meeting was designed to bring experts from a variety of scientific, engineering and clinical disciplines together in a unique environment to discuss current progress in the field of medical bionics and to develop the concepts and techniques required to build the next generation of devices. The field is rapidly expanding, with new engineering solutions for neurological disorders being developed at an astonishing rate. Successful application of emerging engineering technologies into medical bionics devices requires a multidisciplinary research environment in order to deliver clinical solutions that are both safe and effective. Clinical success stories to date include spinal cord stimulators for the management of chronic neurological pain; auditory prostheses that allow the profoundly deaf to hear; and deep brain stimulation to negate movement disorders in Parkinson's disease. Other research programs currently undergoing clinical trials include devices that allow paraplegics to stand and even walk; brain-machine interfaces that provide quadriplegic patients with rudimentary control of a computer but may ultimately provide control of wheel chairs and artificial limbs; devices that detect and suppress epileptic seizures using brief trains of electrical stimulation; and retinal prostheses that will provide vision to the blind. The future for medical bionics is indeed stimulating! A key component to developing successful medical bionic solutions is a good understanding of the technological developments in the many enabling technologies that contribute to this field. Meetings such as this one are designed to provide that cross-discipline background. Conference themes included: smarter devices—the role of information and communication, and other enabling, technologies in medical bionics; smarter materials—intelligent polymers and nanotechnology in medical bionics; neural interfaces for central nervous system and spinal cord stimulation; retinal and auditory prostheses; and cell-based therapies for neural generation and protection. The eight articles arising from this meeting cover these broad research themes. Neural prostheses typically stimulate neural tissue that has undergone atrophic or pathological changes as a result of an underlying disease process, therefore technologies designed to minimise ongoing degenerative changes and improve the electrode-neural interface are important for improving device efficacy. Skinner and colleagues describe the use of cell-based therapies designed to deliver neurotrophic factors for long-term treatment of degenerative neurological disorders. A unique aspect of their research is the incorporation of neurotrophin releasing xenografts within alginate capsules designed to allow nutrients and neurotrophins to move freely across the alginate barrier while providing immunological isolation. Liu and colleagues describe the characterization of organic conducting polymers. These materials are attractive candidates for a number of biomedical applications including electrodes due to the inherent electrical conductivity, ease of fabrication and high surface area which facilitates ion exchange between the electrodes and surrounding tissues. These researchers demonstrate such materials can support and enhanced nerve cell differentiation via electrical stimulation in vitro. Shivdasani et al used sophisticated multichannel electrophysiological recordings of neurons within the ventral cochlear nucleus—part of the first relay centre within the auditory pathway—to demonstrate that neural synchrony in these neuron populations is predominantly a result of common excitatory input from the auditory nerve. Based on these studies the authors propose improved stimulation strategies for use in auditory brainstem implants. Ng and colleagues discuss various technologies needed to develop retinal prostheses with wireless power and data telemetry operation. They then describe the use of integrated circuits and microfabrication technologies for implementing these inductive links. Stieglitz summarizes the fundamental steps during the design and development of a micro-machined epiretinal vision prosthesis with emphasis on the electrode design, the cytotoxicity evaluation and hybrid assembly of the system. Seligman then uses the cochlear implant as a case study for the development of a commercial neural prosthesis. This overview considers issues of biocompatibility, extreme reliability, safety, patient fitting and surgical placement, and emphasises the importance of operating in a multidisciplinary environment. McDermott and Varsavsky applied perceptual models of acoustic and electric stimulation to estimate the loudness of sound signals when presented via a cochlear implant or hearing aid. The models' outputs were compared with published data from relevant psychophysical experiments. The findings led to better fitting and sound processing, particularly in cases where cochlear implants and hearing aids are used simultaneously by individuals with some residual hearing. Finally, Fallon and colleagues review the evidence of plastic changes in the central auditory system that contribute to improved performance with a cochlear implant, and discuss how these changes relate to electrophysiological and functional imaging studies in humans. This review finishes by examining the role of brain plasticity in neural prostheses in general. I would like to acknowledge our conference sponsors MiniFAB, National ICT Australia, School of Engineering University of Melbourne, Hearing CRC and the Bionic Ear Institute. Thanks to our conference participants, many of whom travelled great distances to be with us, the Scientific Advisory committee, the authors of the enclosed papers, the reviewers who ensured the publications were of high quality and the staff of IOP—particularly Jane Roscoe and Andrew Malloy—-who supported this conference from its outset and were instrumental in bringing this special section to fruition. Finally, I look forward to welcoming you to our next meeting scheduled for late 2012. Conference delegates

Data-driven model comparing the effects of glial scarring and interface interactions on chronic neural recordings in non-human primates

NASA Astrophysics Data System (ADS)

Malaga, Karlo A.; Schroeder, Karen E.; Patel, Paras R.; Irwin, Zachary T.; Thompson, David E.; Bentley, J. Nicole; Lempka, Scott F.; Chestek, Cynthia A.; Patil, Parag G.

2016-02-01

Objective. We characterized electrode stability over twelve weeks of impedance and neural recording data from four chronically-implanted Utah arrays in two rhesus macaques, and investigated the effects of glial scarring and interface interactions at the electrode recording site on signal quality using a computational model. Approach. A finite-element model of a Utah array microelectrode in neural tissue was coupled with a multi-compartmental model of a neuron to quantify the effects of encapsulation thickness, encapsulation resistivity, and interface resistivity on electrode impedance and waveform amplitude. The coupled model was then reconciled with the in vivo data. Histology was obtained seventeen weeks post-implantation to measure gliosis. Main results. From week 1-3, mean impedance and amplitude increased at rates of 115.8 kΩ/week and 23.1 μV/week, respectively. This initial ramp up in impedance and amplitude was observed across all arrays, and is consistent with biofouling (increasing interface resistivity) and edema clearing (increasing tissue resistivity), respectively, in the model. Beyond week 3, the trends leveled out. Histology showed that thin scars formed around the electrodes. In the model, scarring could not match the in vivo data. However, a thin interface layer at the electrode tip could. Despite having a large effect on impedance, interface resistivity did not have a noticeable effect on amplitude. Significance. This study suggests that scarring does not cause an electrical problem with regard to signal quality since it does not appear to be the main contributor to increasing impedance or significantly affect amplitude unless it displaces neurons. This, in turn, suggests that neural signals can be obtained reliably despite scarring as long as the recording site has sufficiently low impedance after accumulating a thin layer of biofouling. Therefore, advancements in microelectrode technology may be expedited by focusing on improvements to the recording site-tissue interface rather than elimination of the glial scar.

Braided Multi-Electrode Probes (BMEPs) for Neural Interfaces

NASA Astrophysics Data System (ADS)

Kim, Tae Gyo

Although clinical use of invasive neural interfaces is very limited, due to safety and reliability concerns, the potential benefits of their use in brain machine interfaces (BMIs) seem promising and so they have been widely used in the research field. Microelectrodes as invasive neural interfaces are the core tool to record neural activities and their failure is a critical issue for BMI systems. Possible sources of this failure are neural tissue motions and their interactions with stiff electrode arrays or probes fixed to the skull. To overcome these tissue motion problems, we have developed novel braided multi-electrode probes (BMEPs). By interweaving ultra-fine wires into a tubular braid structure, we obtained a highly flexible multi-electrode probe. In this thesis we described BMEP designs and how to fabricate BMEPs, and explore experiments to show the advantages of BMEPs through a mechanical compliance comparison and a chronic immunohistological comparison with single 50microm nichrome wires used as a reference electrode type. Results from the mechanical compliance test showed that the bodies of BMEPs have 4 to 21 times higher compliance than the single 50microm wire and the tethers of BMEPs were 6 to 96 times higher compliance, depending on combinations of the wire size (9.6microm or 12.7microm), the wire numbers (12 or 24), and the length of tether (3, 5 or 10 mm). Results from the immunohistological comparison showed that both BMEPs and 50microm wires anchored to the skull caused stronger tissue reactions than unanchored BMEPs and 50microm wires, and 50microm wires caused stronger tissue reactions than BMEPs. In in-vivo tests with BMEPs, we succeeded in chronic recordings from the spinal cord of freely jumping frogs and in acute recordings from the spinal cord of decerebrate rats during air stepping which was evoked by mesencephalic locomotor region (MLR) stimulation. This technology may provide a stable and reliable neural interface to spinal cord researches with freely moving animals as well as to BMI researches. In addition this is extensible to various applications.

Reprint of “Non-causal spike filtering improves decoding of movement intention for intracortical BCIs”☆

PubMed Central

Masse, Nicolas Y.; Jarosiewicz, Beata; Simeral, John D.; Bacher, Daniel; Stavisky, Sergey D.; Cash, Sydney S.; Oakley, Erin M.; Berhanu, Etsub; Eskandar, Emad; Friehs, Gerhard; Hochberg, Leigh R.; Donoghue, John P.

2015-01-01

Background Multiple types of neural signals are available for controlling assistive devices through brain–computer interfaces (BCIs). Intracortically recorded spiking neural signals are attractive for BCIs because they can in principle provide greater fidelity of encoded information compared to electrocorticographic (ECoG) signals and electroencephalograms (EEGs). Recent reports show that the information content of these spiking neural signals can be reliably extracted simply by causally band-pass filtering the recorded extracellular voltage signals and then applying a spike detection threshold, without relying on “sorting” action potentials. New method We show that replacing the causal filter with an equivalent non-causal filter increases the information content extracted from the extracellular spiking signal and improves decoding of intended movement direction. This method can be used for real-time BCI applications by using a 4 ms lag between recording and filtering neural signals. Results Across 18 sessions from two people with tetraplegia enrolled in the BrainGate2 pilot clinical trial, we found that threshold crossing events extracted using this non-causal filtering method were significantly more informative of each participant’s intended cursor kinematics compared to threshold crossing events derived from causally filtered signals. This new method decreased the mean angular error between the intended and decoded cursor direction by 9.7° for participant S3, who was implanted 5.4 years prior to this study, and by 3.5° for participant T2, who was implanted 3 months prior to this study. PMID:25681017

Evaluation of poly(3,4-ethylenedioxythiophene)/carbon nanotube neural electrode coatings for stimulation in the dorsal root ganglion

PubMed Central

Kolarcik, Christi L.; Catt, Kasey; Rost, Erika; Albrecht, Ingrid N.; Bourbeau, Dennis; Du, Zhanhong; Kozai, Takashi D.Y.; Luo, Xiliang; Weber, Douglas J.; Cui, X. Tracy

2015-01-01

Objective The dorsal root ganglion (DRG) is an attractive target for implanting neural electrode arrays that restore sensory function or provide therapy via stimulation. However, penetrating microelectrodes designed for these applications are small and deliver low currents. For long-term performance of microstimulation devices, novel coating materials are needed in part to decrease impedance values at the electrode-tissue interface and to increase charge storage capacity. Approach Conductive polymer poly(3,4-ethylenedioxythiophene) (PEDOT) and multiwall carbon nanotubes (CNTs) were coated on the electrode surface and doped with the anti-inflammatory drug, dexamethasone. Electrode characteristics and the tissue reaction around neural electrodes as the result of stimulation, coating and drug release were characterized. Hematoxylin and eosin staining along with antibodies recognizing Iba1 (microglia/macrophages), NF200 (neuronal axons), NeuN (neurons), vimentin (fibroblasts), caspase-3 (cell death) and L1 (neural cell adhesion molecule) were used. Quantitative image analyses were performed using MATLAB. Main Results Our results indicate that coated microelectrodes have lower in vitro and in vivo impedance values. Significantly less neuronal death/damage was observed with coated electrodes as compared to non-coated controls. The inflammatory response with the PEDOT/CNT-coated electrodes was also reduced. Significance This study is the first to report on the utility of these coatings in stimulation applications. Our results indicate PEDOT/CNT coatings may be valuable additions to implantable electrodes used as therapeutic modalities. PMID:25485675

Evaluation of poly(3,4-ethylenedioxythiophene)/carbon nanotube neural electrode coatings for stimulation in the dorsal root ganglion

NASA Astrophysics Data System (ADS)

Kolarcik, Christi L.; Catt, Kasey; Rost, Erika; Albrecht, Ingrid N.; Bourbeau, Dennis; Du, Zhanhong; Kozai, Takashi D. Y.; Luo, Xiliang; Weber, Douglas J.; Cui, X. Tracy

2015-02-01

Objective. The dorsal root ganglion is an attractive target for implanting neural electrode arrays that restore sensory function or provide therapy via stimulation. However, penetrating microelectrodes designed for these applications are small and deliver low currents. For long-term performance of microstimulation devices, novel coating materials are needed in part to decrease impedance values at the electrode-tissue interface and to increase charge storage capacity. Approach. Conductive polymer poly(3,4-ethylenedioxythiophene) (PEDOT) and multi-wall carbon nanotubes (CNTs) were coated on the electrode surface and doped with the anti-inflammatory drug, dexamethasone. Electrode characteristics and the tissue reaction around neural electrodes as a result of stimulation, coating and drug release were characterized. Hematoxylin and eosin staining along with antibodies recognizing Iba1 (microglia/macrophages), NF200 (neuronal axons), NeuN (neurons), vimentin (fibroblasts), caspase-3 (cell death) and L1 (neural cell adhesion molecule) were used. Quantitative image analyses were performed using MATLAB. Main results. Our results indicate that coated microelectrodes have lower in vitro and in vivo impedance values. Significantly less neuronal death/damage was observed with coated electrodes as compared to non-coated controls. The inflammatory response with the PEDOT/CNT-coated electrodes was also reduced. Significance. This study is the first to report on the utility of these coatings in stimulation applications. Our results indicate PEDOT/CNT coatings may be valuable additions to implantable electrodes used as therapeutic modalities.

Reliability Modeling of Microelectromechanical Systems Using Neural Networks

NASA Technical Reports Server (NTRS)

Perera. J. Sebastian

2000-01-01

Microelectromechanical systems (MEMS) are a broad and rapidly expanding field that is currently receiving a great deal of attention because of the potential to significantly improve the ability to sense, analyze, and control a variety of processes, such as heating and ventilation systems, automobiles, medicine, aeronautical flight, military surveillance, weather forecasting, and space exploration. MEMS are very small and are a blend of electrical and mechanical components, with electrical and mechanical systems on one chip. This research establishes reliability estimation and prediction for MEMS devices at the conceptual design phase using neural networks. At the conceptual design phase, before devices are built and tested, traditional methods of quantifying reliability are inadequate because the device is not in existence and cannot be tested to establish the reliability distributions. A novel approach using neural networks is created to predict the overall reliability of a MEMS device based on its components and each component's attributes. The methodology begins with collecting attribute data (fabrication process, physical specifications, operating environment, property characteristics, packaging, etc.) and reliability data for many types of microengines. The data are partitioned into training data (the majority) and validation data (the remainder). A neural network is applied to the training data (both attribute and reliability); the attributes become the system inputs and reliability data (cycles to failure), the system output. After the neural network is trained with sufficient data. the validation data are used to verify the neural networks provided accurate reliability estimates. Now, the reliability of a new proposed MEMS device can be estimated by using the appropriate trained neural networks developed in this work.

At the interface: convergence of neural regeneration and neural prostheses for restoration of function.

PubMed

Grill, W M; McDonald, J W; Peckham, P H; Heetderks, W; Kocsis, J; Weinrich, M

2001-01-01

The rapid pace of recent advances in development and application of electrical stimulation of the nervous system and in neural regeneration has created opportunities to combine these two approaches to restoration of function. This paper relates the discussion on this topic from a workshop at the International Functional Electrical Stimulation Society. The goals of this workshop were to discuss the current state of interaction between the fields of neural regeneration and neural prostheses and to identify potential areas of future research that would have the greatest impact on achieving the common goal of restoring function after neurological damage. Identified areas include enhancement of axonal regeneration with applied electric fields, development of hybrid neural interfaces combining synthetic silicon and biologically derived elements, and investigation of the role of patterned neural activity in regulating various neuronal processes and neurorehabilitation. Increased communication and cooperation between the two communities and recognition by each field that the other has something to contribute to their efforts are needed to take advantage of these opportunities. In addition, creative grants combining the two approaches and more flexible funding mechanisms to support the convergence of their perspectives are necessary to achieve common objectives.

Localizing Tortoise Nests by Neural Networks.

PubMed

Barbuti, Roberto; Chessa, Stefano; Micheli, Alessio; Pucci, Rita

2016-01-01

The goal of this research is to recognize the nest digging activity of tortoises using a device mounted atop the tortoise carapace. The device classifies tortoise movements in order to discriminate between nest digging, and non-digging activity (specifically walking and eating). Accelerometer data was collected from devices attached to the carapace of a number of tortoises during their two-month nesting period. Our system uses an accelerometer and an activity recognition system (ARS) which is modularly structured using an artificial neural network and an output filter. For the purpose of experiment and comparison, and with the aim of minimizing the computational cost, the artificial neural network has been modelled according to three different architectures based on the input delay neural network (IDNN). We show that the ARS can achieve very high accuracy on segments of data sequences, with an extremely small neural network that can be embedded in programmable low power devices. Given that digging is typically a long activity (up to two hours), the application of ARS on data segments can be repeated over time to set up a reliable and efficient system, called Tortoise@, for digging activity recognition.

Laser-induced surface modification of biopolymers – micro/nanostructuring and functionalization

NASA Astrophysics Data System (ADS)

Stankova, N. E.; Atanasov, P. A.; Nedyalkov, N. N.; Tatchev, Dr; Kolev, K. N.; Valova, E. I.; Armyanov, St. A.; Grochowska, K.; Śliwiński, G.; Fukata, N.; Hirsch, D.; Rauschenbach, B.

2018-03-01

The medical-grade polydimethylsiloxane (PDMS) elastomer is a widely used biomaterial in medicine for preparation of high-tech devices because of its remarkable properties. In this paper, we present experimental results on surface modification of PDMS elastomer by using ultraviolet, visible, and near-infrared ns-laser system and investigation of the chemical composition and the morphological structure inside the treated area in dependence on the processing parameters – wavelength, laser fluence and number of pulses. Remarkable chemical transformations and changes of the morphological structure were observed, resulting in the formation of a highly catalytically active surface, which was successfully functionalized via electroless Ni and Pt deposition by a sensitizing-activation free process. The results obtained are very promising in view of applying the methods of laser-induced micro- and nano-structuring and activation of biopolymers’ surface and further electroless metal plating to the preparation of, e.g., multielectrode arrays (MEAs) devices in neural and muscular surface interfacing implantable systems.

Silicone Molding and Lifetime Testing of Peripheral Nerve Interfaces for Neuroprostheses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gupte, Kimaya; Tolosa, Vanessa

Implantable peripheral nerve cuffs have a large application in neuroprostheses as they can be used to restore sensation to those with upper limb amputations. Modern day prosthetics, while lessening the pain associated with phantom limb syndrome, have limited fine motor control and do not provide sensory feedback to patients. Sensory feedback with prosthetics requires communication between the nervous system and limbs, and is still a challenge to accomplish with amputees. Establishing this communication between the peripheral nerves in the arm and artificial limbs is vital as prosthetics research aims to provide sensory feedback to amputees. Peripheral nerve cuffs restore sensationmore » by electrically stimulating certain parts of the nerve in order to create feeling in the hand. Cuff electrodes have an advantage over standard electrodes as they have high selective stimulation by bringing the electrical interface close to the neural tissue in order to selectively activate targeted regions of a peripheral nerve. In order to further improve the selective stimulation of these nerve cuffs, there is need for finer spatial resolution among electrodes. One method to achieve a higher spatial resolution is to increase the electrode density on the cuff itself. Microfabrication techniques can be used to achieve this higher electrode density. Using L-Edit, a layout editor, microfabricated peripheral nerve cuffs were designed with a higher electrode density than the current model. This increase in electrode density translates to an increase in spatial resolution by at least one order of magnitude. Microfabricated devices also have two separate components that are necessary to understand before implantation: lifetime of the device and assembly to prevent nerve damage. Silicone molding procedures were optimized so that devices do not damage nerves in vivo, and lifetime testing was performed on test microfabricated devices to determine their lifetime in vivo. Future work of this project would include fabricating some of the designed devices and seeing how they compare to the current cuffs in terms of their electrical performance, lifetime, shape, and mechanical properties.« less

PCSIM: A Parallel Simulation Environment for Neural Circuits Fully Integrated with Python

PubMed Central

Pecevski, Dejan; Natschläger, Thomas; Schuch, Klaus

2008-01-01

The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle. The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof. In particular we will investigate how the automatically generated bidirectional interface and PCSIM's object-oriented modular framework enable the user to adopt a hybrid modeling approach: using and extending PCSIM's functionality either employing pure Python or C++ and thus combining the advantages of both worlds. Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations. PMID:19543450

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Konz, Daniel W. (Inventor); Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Winkelmann, Joseph P. (Inventor)

2006-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted into digital signals and transmitted back to the controller. In one embodiment, the bus controller sends commands and data a defined bit rate, and the network device interface senses this bit rate and sends data back to the bus controller using the defined bit rate.

Brain machine interfaces combining microelectrode arrays with nanostructured optical biochemical sensors

NASA Astrophysics Data System (ADS)

Hajj-Hassan, Mohamad; Gonzalez, Timothy; Ghafer-Zadeh, Ebrahim; Chodavarapu, Vamsy; Musallam, Sam; Andrews, Mark

2009-02-01

Neural microelectrodes are an important component of neural prosthetic systems which assist paralyzed patients by allowing them to operate computers or robots using their neural activity. These microelectrodes are also used in clinical settings to localize the locus of seizure initiation in epilepsy or to stimulate sub-cortical structures in patients with Parkinson's disease. In neural prosthetic systems, implanted microelectrodes record the electrical potential generated by specific thoughts and relay the signals to algorithms trained to interpret these thoughts. In this paper, we describe novel elongated multi-site neural electrodes that can record electrical signals and specific neural biomarkers and that can reach depths greater than 8mm in the sulcus of non-human primates (monkeys). We hypothesize that additional signals recorded by the multimodal probes will increase the information yield when compared to standard probes that record just electropotentials. We describe integration of optical biochemical sensors with neural microelectrodes. The sensors are made using sol-gel derived xerogel thin films that encapsulate specific biomarker responsive luminophores in their nanostructured pores. The desired neural biomarkers are O2, pH, K+, and Na+ ions. As a prototype, we demonstrate direct-write patterning to create oxygen-responsive xerogel waveguide structures on the neural microelectrodes. The recording of neural biomarkers along with electrical activity could help the development of intelligent and more userfriendly neural prosthesis/brain machine interfaces as well as aid in providing answers to complex brain diseases and disorders.

Development of human nervous tissue upon differentiation of embryonic stem cells in three-dimensional culture.

PubMed

Preynat-Seauve, Olivier; Suter, David M; Tirefort, Diderik; Turchi, Laurent; Virolle, Thierry; Chneiweiss, Herve; Foti, Michelangelo; Lobrinus, Johannes-Alexander; Stoppini, Luc; Feki, Anis; Dubois-Dauphin, Michel; Krause, Karl Heinz

2009-03-01

Researches on neural differentiation using embryonic stem cells (ESC) require analysis of neurogenesis in conditions mimicking physiological cellular interactions as closely as possible. In this study, we report an air-liquid interface-based culture of human ESC. This culture system allows three-dimensional cell expansion and neural differentiation in the absence of added growth factors. Over a 3-month period, a macroscopically visible, compact tissue developed. Histological coloration revealed a dense neural-like neural tissue including immature tubular structures. Electron microscopy, immunochemistry, and electrophysiological recordings demonstrated a dense network of neurons, astrocytes, and oligodendrocytes able to propagate signals. Within this tissue, tubular structures were niches of cells resembling germinal layers of human fetal brain. Indeed, the tissue contained abundant proliferating cells expressing markers of neural progenitors. Finally, the capacity to generate neural tissues on air-liquid interface differed for different ESC lines, confirming variations of their neurogenic potential. In conclusion, this study demonstrates in vitro engineering of a human neural-like tissue with an organization that bears resemblance to early developing brain. As opposed to previously described methods, this differentiation (a) allows three-dimensional organization, (b) yields dense interconnected neural tissue with structurally and functionally distinct areas, and (c) is spontaneously guided by endogenous developmental cues.

Nanoparticles: A Challenging Vehicle for Neural Stimulation

PubMed Central

Colombo, Elisabetta; Feyen, Paul; Antognazza, Maria Rosa; Lanzani, Guglielmo; Benfenati, Fabio

2016-01-01

Neurostimulation represents a powerful and well-established tool for the treatment of several diseases affecting the central nervous system. Although, effective in reducing the symptoms or the progression of brain disorders, the poor accessibility of the deepest areas of the brain currently hampers the possibility of a more specific and controlled therapeutic stimulation, depending on invasive surgical approaches and long-term stability, and biocompatibility issues. The massive research of the last decades on nanomaterials and nanoscale devices favored the development of new tools to address the limitations of the available neurostimulation approaches. This mini-review focuses on the employment of nanoparticles for the modulation of the electrophysiological activity of neuronal networks and the related transduction mechanisms underlying the nanostructure-neuron interfaces. PMID:27047327

A procedure concept for local reflex control of grasping

NASA Technical Reports Server (NTRS)

Fiorini, Paolo; Chang, Jeffrey

1989-01-01

An architecture is proposed for the control of robotic devices, and in particular of anthropomorphic hands, characterized by a hierarchical structure in which every level of the architecture contains data and control function with varying degree of abstraction. Bottom levels of the hierarchy interface directly with sensors and actuators, and process raw data and motor commands. Higher levels perform more symbolic types of tasks, such as application of boolean rules and general planning operations. Layers implementation has to be consistent with the type of operation and its requirements for real time control. It is proposed to implement the rule level with a Boolean Artificial Neural Network characterized by a response time sufficient for producing reflex corrective action at the actuator level.

A freely-moving monkey treadmill model

NASA Astrophysics Data System (ADS)

Foster, Justin D.; Nuyujukian, Paul; Freifeld, Oren; Gao, Hua; Walker, Ross; Ryu, Stephen I.; Meng, Teresa H.; Murmann, Boris; Black, Michael J.; Shenoy, Krishna V.

2014-08-01

Objective. Motor neuroscience and brain-machine interface (BMI) design is based on examining how the brain controls voluntary movement, typically by recording neural activity and behavior from animal models. Recording technologies used with these animal models have traditionally limited the range of behaviors that can be studied, and thus the generality of science and engineering research. We aim to design a freely-moving animal model using neural and behavioral recording technologies that do not constrain movement. Approach. We have established a freely-moving rhesus monkey model employing technology that transmits neural activity from an intracortical array using a head-mounted device and records behavior through computer vision using markerless motion capture. We demonstrate the flexibility and utility of this new monkey model, including the first recordings from motor cortex while rhesus monkeys walk quadrupedally on a treadmill. Main results. Using this monkey model, we show that multi-unit threshold-crossing neural activity encodes the phase of walking and that the average firing rate of the threshold crossings covaries with the speed of individual steps. On a population level, we find that neural state-space trajectories of walking at different speeds have similar rotational dynamics in some dimensions that evolve at the step rate of walking, yet robustly separate by speed in other state-space dimensions. Significance. Freely-moving animal models may allow neuroscientists to examine a wider range of behaviors and can provide a flexible experimental paradigm for examining the neural mechanisms that underlie movement generation across behaviors and environments. For BMIs, freely-moving animal models have the potential to aid prosthetic design by examining how neural encoding changes with posture, environment and other real-world context changes. Understanding this new realm of behavior in more naturalistic settings is essential for overall progress of basic motor neuroscience and for the successful translation of BMIs to people with paralysis.

Analysis of Al2O3—parylene C bilayer coatings and impact of microelectrode topography on long term stability of implantable neural arrays

NASA Astrophysics Data System (ADS)

Caldwell, Ryan; Mandal, Himadri; Sharma, Rohit; Solzbacher, Florian; Tathireddy, Prashant; Rieth, Loren

2017-08-01

Objective. Performance of many dielectric coatings for neural electrodes degrades over time, contributing to loss of neural signals and evoked percepts. Studies using planar test substrates have found that a novel bilayer coating of atomic-layer deposited (ALD) Al2O3 and parylene C is a promising candidate for neural electrode applications, exhibiting superior stability to parylene C alone. However, initial results from bilayer encapsulation testing on non-planar devices have been less positive. Our aim was to evaluate ALD Al2O3-parylene C coatings using novel test paradigms, to rigorously evaluate dielectric coatings for neural electrode applications by incorporating neural electrode topography into test structure design. Approach. Five test devices incorporated three distinct topographical features common to neural electrodes, derived from the utah electrode array (UEA). Devices with bilayer (52 nm Al2O3  +  6 µm parylene C) were evaluated against parylene C controls (N  ⩾  6 per device type). Devices were aged in phosphate buffered saline at 67 °C for up to 311 d, and monitored through: (1) leakage current to evaluate encapsulation lifetimes (>1 nA during 5VDC bias indicated failure), and (2) wideband (1-105 Hz) impedance. Main results. Mean-times-to-failure (MTTFs) ranged from 12 to 506 d for bilayer-coated devices, versus 10 to  >2310 d for controls. Statistical testing (log-rank test, α  =  0.05) of failure rates gave mixed results but favored the control condition. After failure, impedance loss for bilayer devices continued for months and manifested across the entire spectrum, whereas the effect was self-limiting after several days, and restricted to frequencies  <100 Hz for controls. These results correlated well with observations of UEAs encapsulated with bilayer and control films. Significance. We observed encapsulation failure modes and behaviors comparable to neural electrode performance which were undetected in studies with planar test devices. We found the impact of parylene C defects to be exacerbated by ALD Al2O3, and conclude that inferior bilayer performance arises from degradation of ALD Al2O3 when directly exposed to saline. This is an important consideration, given that neural electrodes with bilayer coatings are expected to have ALD Al2O3 exposed at dielectric boundaries that delineate electrode sites. Process improvements and use of different inorganic coatings to decrease dissolution in physiological fluids may improve performance. Testing frameworks which take neural electrode complexities into account will be well suited to reliably evaluate such encapsulation schemes.

Neuron Stimulation Device Integrated with Silicon Nanowire-Based Photodetection Circuit on a Flexible Substrate.

PubMed

Jung, Suk Won; Shin, Jong Yoon; Pi, Kilwha; Goo, Yong Sook; Cho, Dong-Il Dan

2016-12-01

This paper proposes a neural stimulation device integrated with a silicon nanowire (SiNW)-based photodetection circuit for the activation of neurons with light. The proposed device is comprised of a voltage divider and a current driver in which SiNWs are used as photodetector and field-effect transistors; it has the functions of detecting light, generating a stimulation signal in proportion to the light intensity, and transmitting the signal to a micro electrode. To show the applicability of the proposed neural stimulation device as a high-resolution retinal prosthesis system, a high-density neural stimulation device with a unit cell size of 110 × 110 μ m and a resolution of 32 × 32 was fabricated on a flexible film with a thickness of approximately 50 μm. Its effectiveness as a retinal stimulation device was then evaluated using a unit cell in an in vitro animal experiment involving the retinal tissue of retinal Degeneration 1 ( rd1 ) mice. Experiments wherein stimulation pulses were applied to the retinal tissues successfully demonstrate that the number of spikes in neural response signals increases in proportion to light intensity.

Modeling the electrode-neuron interface of cochlear implants: effects of neural survival, electrode placement, and the partial tripolar configuration.

PubMed

Goldwyn, Joshua H; Bierer, Steven M; Bierer, Julie Arenberg

2010-09-01

The partial tripolar electrode configuration is a relatively novel stimulation strategy that can generate more spatially focused electric fields than the commonly used monopolar configuration. Focused stimulation strategies should improve spectral resolution in cochlear implant users, but may also be more sensitive to local irregularities in the electrode-neuron interface. In this study, we develop a practical computer model of cochlear implant stimulation that can simulate neural activation in a simplified cochlear geometry and we relate the resulting patterns of neural activity to basic psychophysical measures. We examine how two types of local irregularities in the electrode-neuron interface, variations in spiral ganglion nerve density and electrode position within the scala tympani, affect the simulated neural activation patterns and how these patterns change with electrode configuration. The model shows that higher partial tripolar fractions activate more spatially restricted populations of neurons at all current levels and require higher current levels to excite a given number of neurons. We find that threshold levels are more sensitive at high partial tripolar fractions to both types of irregularities, but these effects are not independent. In particular, at close electrode-neuron distances, activation is typically more spatially localized which leads to a greater influence of neural dead regions. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Impact of Linearity and Write Noise of Analog Resistive Memory Devices in a Neural Algorithm Accelerator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jacobs-Gedrim, Robin B.; Agarwal, Sapan; Knisely, Kathrine E.

Resistive memory (ReRAM) shows promise for use as an analog synapse element in energy-efficient neural network algorithm accelerators. A particularly important application is the training of neural networks, as this is the most computationally-intensive procedure in using a neural algorithm. However, training a network with analog ReRAM synapses can significantly reduce the accuracy at the algorithm level. In order to assess this degradation, analog properties of ReRAM devices were measured and hand-written digit recognition accuracy was modeled for the training using backpropagation. Bipolar filamentary devices utilizing three material systems were measured and compared: one oxygen vacancy system, Ta-TaO x, andmore » two conducting metallization systems, Cu-SiO 2, and Ag/chalcogenide. Analog properties and conductance ranges of the devices are optimized by measuring the response to varying voltage pulse characteristics. Key analog device properties which degrade the accuracy are update linearity and write noise. Write noise may improve as a function of device manufacturing maturity, but write nonlinearity appears relatively consistent among the different device material systems and is found to be the most significant factor affecting accuracy. As a result, this suggests that new materials and/or fundamentally different resistive switching mechanisms may be required to improve device linearity and achieve higher algorithm training accuracy.« less

Impact of Linearity and Write Noise of Analog Resistive Memory Devices in a Neural Algorithm Accelerator

DOE PAGES

Jacobs-Gedrim, Robin B.; Agarwal, Sapan; Knisely, Kathrine E.; ...

2017-12-01

Resistive memory (ReRAM) shows promise for use as an analog synapse element in energy-efficient neural network algorithm accelerators. A particularly important application is the training of neural networks, as this is the most computationally-intensive procedure in using a neural algorithm. However, training a network with analog ReRAM synapses can significantly reduce the accuracy at the algorithm level. In order to assess this degradation, analog properties of ReRAM devices were measured and hand-written digit recognition accuracy was modeled for the training using backpropagation. Bipolar filamentary devices utilizing three material systems were measured and compared: one oxygen vacancy system, Ta-TaO x, andmore » two conducting metallization systems, Cu-SiO 2, and Ag/chalcogenide. Analog properties and conductance ranges of the devices are optimized by measuring the response to varying voltage pulse characteristics. Key analog device properties which degrade the accuracy are update linearity and write noise. Write noise may improve as a function of device manufacturing maturity, but write nonlinearity appears relatively consistent among the different device material systems and is found to be the most significant factor affecting accuracy. As a result, this suggests that new materials and/or fundamentally different resistive switching mechanisms may be required to improve device linearity and achieve higher algorithm training accuracy.« less

Controlling selective stimulations below a spinal cord hemisection using brain recordings with a neural interface system approach

NASA Astrophysics Data System (ADS)

Panetsos, Fivos; Sanchez-Jimenez, Abel; Torets, Carlos; Largo, Carla; Micera, Silvestro

2011-08-01

In this work we address the use of realtime cortical recordings for the generation of coherent, reliable and robust motor activity in spinal-lesioned animals through selective intraspinal microstimulation (ISMS). The spinal cord of adult rats was hemisectioned and groups of multielectrodes were implanted in both the central nervous system (CNS) and the spinal cord below the lesion level to establish a neural system interface (NSI). To test the reliability of this new NSI connection, highly repeatable neural responses recorded from the CNS were used as a pattern generator of an open-loop control strategy for selective ISMS of the spinal motoneurons. Our experimental procedure avoided the spontaneous non-controlled and non-repeatable neural activity that could have generated spurious ISMS and the consequent undesired muscle contractions. Combinations of complex CNS patterns generated precisely coordinated, reliable and robust motor actions.

[Not Available].

PubMed

Pecevski, Dejan; Natschläger, Thomas; Schuch, Klaus

2009-01-01

The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle. The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof. In particular we will investigate how the automatically generated bidirectional interface and PCSIM's object-oriented modular framework enable the user to adopt a hybrid modeling approach: using and extending PCSIM's functionality either employing pure Python or C++ and thus combining the advantages of both worlds. Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations.

Neural interface methods and apparatus to provide artificial sensory capabilities to a subject

DOEpatents

Buerger, Stephen P.; Olsson, III, Roy H.; Wojciechowski, Kenneth E.; Novick, David K.; Kholwadwala, Deepesh K.

2017-01-24

Embodiments of neural interfaces according to the present invention comprise sensor modules for sensing environmental attributes beyond the natural sensory capability of a subject, and communicating the attributes wirelessly to an external (ex-vivo) portable module attached to the subject. The ex-vivo module encodes and communicates the attributes via a transcutaneous inductively coupled link to an internal (in-vivo) module implanted within the subject. The in-vivo module converts the attribute information into electrical neural stimuli that are delivered to a peripheral nerve bundle within the subject, via an implanted electrode. Methods and apparatus according to the invention incorporate implantable batteries to power the in-vivo module allowing for transcutaneous bidirectional communication of low voltage (e.g. on the order of 5 volts) encoded signals as stimuli commands and neural responses, in a robust, low-error rate, communication channel with minimal effects to the subjects' skin.

Evolvable Neural Software System

NASA Technical Reports Server (NTRS)

Curtis, Steven A.

2009-01-01

The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

Human facial neural activities and gesture recognition for machine-interfacing applications.

PubMed

Hamedi, M; Salleh, Sh-Hussain; Tan, T S; Ismail, K; Ali, J; Dee-Uam, C; Pavaganun, C; Yupapin, P P

2011-01-01

The authors present a new method of recognizing different human facial gestures through their neural activities and muscle movements, which can be used in machine-interfacing applications. Human-machine interface (HMI) technology utilizes human neural activities as input controllers for the machine. Recently, much work has been done on the specific application of facial electromyography (EMG)-based HMI, which have used limited and fixed numbers of facial gestures. In this work, a multipurpose interface is suggested that can support 2-11 control commands that can be applied to various HMI systems. The significance of this work is finding the most accurate facial gestures for any application with a maximum of eleven control commands. Eleven facial gesture EMGs are recorded from ten volunteers. Detected EMGs are passed through a band-pass filter and root mean square features are extracted. Various combinations of gestures with a different number of gestures in each group are made from the existing facial gestures. Finally, all combinations are trained and classified by a Fuzzy c-means classifier. In conclusion, combinations with the highest recognition accuracy in each group are chosen. An average accuracy >90% of chosen combinations proved their ability to be used as command controllers.

MEART: The Semi-Living Artist

PubMed Central

Bakkum, Douglas J.; Gamblen, Philip M.; Ben-Ary, Guy; Chao, Zenas C.; Potter, Steve M.

2007-01-01

Here, we and others describe an unusual neurorobotic project, a merging of art and science called MEART, the semi-living artist. We built a pneumatically actuated robotic arm to create drawings, as controlled by a living network of neurons from rat cortex grown on a multi-electrode array (MEA). Such embodied cultured networks formed a real-time closed-loop system which could now behave and receive electrical stimulation as feedback on its behavior. We used MEART and simulated embodiments, or animats, to study the network mechanisms that produce adaptive, goal-directed behavior. This approach to neural interfacing will help instruct the design of other hybrid neural-robotic systems we call hybrots. The interfacing technologies and algorithms developed have potential applications in responsive deep brain stimulation systems and for motor prosthetics using sensory components. In a broader context, MEART educates the public about neuroscience, neural interfaces, and robotics. It has paved the way for critical discussions on the future of bio-art and of biotechnology. PMID:18958276

Neuroadhesive L1 coating attenuates acute microglial attachment to neural electrodes as revealed by live two-photon microscopy.

PubMed

Eles, James R; Vazquez, Alberto L; Snyder, Noah R; Lagenaur, Carl; Murphy, Matthew C; Kozai, Takashi D Y; Cui, X Tracy

2017-01-01

Implantable neural electrode technologies for chronic neural recordings can restore functional control to paralysis and limb loss victims through brain-machine interfaces. These probes, however, have high failure rates partly due to the biological responses to the probe which generate an inflammatory scar and subsequent neuronal cell death. L1 is a neuronal specific cell adhesion molecule and has been shown to minimize glial scar formation and promote electrode-neuron integration when covalently attached to the surface of neural probes. In this work, the acute microglial response to L1-coated neural probes was evaluated in vivo by implanting coated devices into the cortex of mice with fluorescently labeled microglia, and tracking microglial dynamics with multi-photon microscopy for the ensuing 6 h in order to understand L1's cellular mechanisms of action. Microglia became activated immediately after implantation, extending processes towards both L1-coated and uncoated control probes at similar velocities. After the processes made contact with the probes, microglial processes expanded to cover 47.7% of the control probes' surfaces. For L1-coated probes, however, there was a statistically significant 83% reduction in microglial surface coverage. This effect was sustained through the experiment. At 6 h post-implant, the radius of microglia activation was reduced for the L1 probes by 20%, shifting from 130.0 to 103.5 μm with the coating. Microglia as far as 270 μm from the implant site displayed significantly lower morphological characteristics of activation for the L1 group. These results suggest that the L1 surface treatment works in an acute setting by microglial mediated mechanisms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spectroscopic Studies of the Electronic Structure of Metal-Semiconductor and Vacuum-Semiconductor Interfaces.

DTIC Science & Technology

1982-12-31

interfaces which are of importance in such semi- conductor devices as MOSFETS, CCD devices, photovoltaic devices, DD I jAN 73 1473 EDITION OF INOV 66 if...interfaces is interesting for the study of electrolytic cells . Our photoemission study reveals for the first time how the electronic structure of water

Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

PubMed

Tam, Wing-Kin; Yang, Zhi

2018-05-01

Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

Distributed user interfaces for clinical ubiquitous computing applications.

PubMed

Bång, Magnus; Larsson, Anders; Berglund, Erik; Eriksson, Henrik

2005-08-01

Ubiquitous computing with multiple interaction devices requires new interface models that support user-specific modifications to applications and facilitate the fast development of active workspaces. We have developed NOSTOS, a computer-augmented work environment for clinical personnel to explore new user interface paradigms for ubiquitous computing. NOSTOS uses several devices such as digital pens, an active desk, and walk-up displays that allow the system to track documents and activities in the workplace. We present the distributed user interface (DUI) model that allows standalone applications to distribute their user interface components to several devices dynamically at run-time. This mechanism permit clinicians to develop their own user interfaces and forms to clinical information systems to match their specific needs. We discuss the underlying technical concepts of DUIs and show how service discovery, component distribution, events and layout management are dealt with in the NOSTOS system. Our results suggest that DUIs--and similar network-based user interfaces--will be a prerequisite of future mobile user interfaces and essential to develop clinical multi-device environments.

Physical interface dynamics alter how robotic exosuits augment human movement: implications for optimizing wearable assistive devices.

PubMed

Yandell, Matthew B; Quinlivan, Brendan T; Popov, Dmitry; Walsh, Conor; Zelik, Karl E

2017-05-18

Wearable assistive devices have demonstrated the potential to improve mobility outcomes for individuals with disabilities, and to augment healthy human performance; however, these benefits depend on how effectively power is transmitted from the device to the human user. Quantifying and understanding this power transmission is challenging due to complex human-device interface dynamics that occur as biological tissues and physical interface materials deform and displace under load, absorbing and returning power. Here we introduce a new methodology for quickly estimating interface power dynamics during movement tasks using common motion capture and force measurements, and then apply this method to quantify how a soft robotic ankle exosuit interacts with and transfers power to the human body during walking. We partition exosuit end-effector power (i.e., power output from the device) into power that augments ankle plantarflexion (termed augmentation power) vs. power that goes into deformation and motion of interface materials and underlying soft tissues (termed interface power). We provide empirical evidence of how human-exosuit interfaces absorb and return energy, reshaping exosuit-to-human power flow and resulting in three key consequences: (i) During exosuit loading (as applied forces increased), about 55% of exosuit end-effector power was absorbed into the interfaces. (ii) However, during subsequent exosuit unloading (as applied forces decreased) most of the absorbed interface power was returned viscoelastically. Consequently, the majority (about 75%) of exosuit end-effector work over each stride contributed to augmenting ankle plantarflexion. (iii) Ankle augmentation power (and work) was delayed relative to exosuit end-effector power, due to these interface energy absorption and return dynamics. Our findings elucidate the complexities of human-exosuit interface dynamics during transmission of power from assistive devices to the human body, and provide insight into improving the design and control of wearable robots. We conclude that in order to optimize the performance of wearable assistive devices it is important, throughout design and evaluation phases, to account for human-device interface dynamics that affect power transmission and thus human augmentation benefits.

Remapping residual coordination for controlling assistive devices and recovering motor functions

PubMed Central

Pierella, Camilla; Abdollahi, Farnaz; Farshchiansadegh, Ali; Pedersen, Jessica; Thorp, Elias; Mussa-Ivaldi, Ferdinando A.; Casadio, Maura

2015-01-01

The concept of human motor redundancy attracted much attention since the early studies of motor control, as it highlights the ability of the motor system to generate a great variety of movements to achieve any single well-defined goal. The abundance of degrees of freedom in the human body may be a fundamental resource in the learning and remapping problems that are encountered in human–machine interfaces (HMIs) developments. The HMI can act at different levels decoding brain signals or body signals to control an external device. The transformation from neural signals to device commands is the core of research on brain-machine interfaces (BMIs). However, while BMIs bypass completely the final path of the motor system, body-machine interfaces (BoMIs) take advantage of motor skills that are still available to the user and have the potential to enhance these skills through their consistent use. BoMIs empower people with severe motor disabilities with the possibility to control external devices, and they concurrently offer the opportunity to focus on achieving rehabilitative goals. In this study we describe a theoretical paradigm for the use of a BoMI in rehabilitation. The proposed BoMI remaps the user’s residual upper body mobility to the two coordinates of a cursor on a computer screen. This mapping is obtained by principal component analysis (PCA). We hypothesize that the BoMI can be specifically programmed to engage the users in functional exercises aimed at partial recovery of motor skills, while simultaneously controlling the cursor and carrying out functional tasks, e.g. playing games. Specifically, PCA allows us to select not only the subspace that is most comfortable for the user to act upon, but also the degrees of freedom and coordination patterns that the user has more difficulty engaging. In this article, we describe a family of map modifications that can be made to change the motor behavior of the user. Depending on the characteristics of the impairment of each high-level spinal cord injury (SCI) survivor, we can make modifications to restore a higher level of symmetric mobility (left versus right), or to increase the strength and range of motion of the upper body that was spared by the injury. Results showed that this approach restored symmetry between left and right side of the body, with an increase of mobility and strength of all the degrees of freedom in the participants involved in the control of the interface. This is a proof of concept that our BoMI may be used concurrently to control assistive devices and reach specific rehabilitative goals. Engaging the users in functional and entertaining tasks while practicing the interface and changing the map in the proposed ways is a novel approach to rehabilitation treatments facilitated by portable and low-cost technologies. PMID:26341935

Remapping residual coordination for controlling assistive devices and recovering motor functions.

PubMed

Pierella, Camilla; Abdollahi, Farnaz; Farshchiansadegh, Ali; Pedersen, Jessica; Thorp, Elias B; Mussa-Ivaldi, Ferdinando A; Casadio, Maura

2015-12-01

The concept of human motor redundancy attracted much attention since the early studies of motor control, as it highlights the ability of the motor system to generate a great variety of movements to achieve any well-defined goal. The abundance of degrees of freedom in the human body may be a fundamental resource in the learning and remapping problems that are encountered in human-machine interfaces (HMIs) developments. The HMI can act at different levels decoding brain signals or body signals to control an external device. The transformation from neural signals to device commands is the core of research on brain-machine interfaces (BMIs). However, while BMIs bypass completely the final path of the motor system, body-machine interfaces (BoMIs) take advantage of motor skills that are still available to the user and have the potential to enhance these skills through their consistent use. BoMIs empower people with severe motor disabilities with the possibility to control external devices, and they concurrently offer the opportunity to focus on achieving rehabilitative goals. In this study we describe a theoretical paradigm for the use of a BoMI in rehabilitation. The proposed BoMI remaps the user's residual upper body mobility to the two coordinates of a cursor on a computer screen. This mapping is obtained by principal component analysis (PCA). We hypothesize that the BoMI can be specifically programmed to engage the users in functional exercises aimed at partial recovery of motor skills, while simultaneously controlling the cursor and carrying out functional tasks, e.g. playing games. Specifically, PCA allows us to select not only the subspace that is most comfortable for the user to act upon, but also the degrees of freedom and coordination patterns that the user has more difficulty engaging. In this article, we describe a family of map modifications that can be made to change the motor behavior of the user. Depending on the characteristics of the impairment of each high-level spinal cord injury (SCI) survivor, we can make modifications to restore a higher level of symmetric mobility (left versus right), or to increase the strength and range of motion of the upper body that was spared by the injury. Results showed that this approach restored symmetry between left and right side of the body, with an increase of mobility and strength of all the degrees of freedom in the participants involved in the control of the interface. This is a proof of concept that our BoMI may be used concurrently to control assistive devices and reach specific rehabilitative goals. Engaging the users in functional and entertaining tasks while practicing the interface and changing the map in the proposed ways is a novel approach to rehabilitation treatments facilitated by portable and low-cost technologies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Towards a miniaturized brain-machine-spinal cord interface (BMSI) for restoration of function after spinal cord injury.

PubMed

Shahdoost, Shahab; Frost, Shawn; Van Acker, Gustaf; DeJong, Stacey; Dunham, Caleb; Barbay, Scott; Nudo, Randolph; Mohseni, Pedram

2014-01-01

Nearly 6 million people in the United States are currently living with paralysis in which 23% of the cases are related to spinal cord injury (SCI). Miniaturized closed-loop neural interfaces have the potential for restoring function and mobility lost to debilitating neural injuries such as SCI by leveraging recent advancements in bioelectronics and a better understanding of the processes that underlie functional and anatomical reorganization in an injured nervous system. This paper describes our current progress towards developing a miniaturized brain-machine-spinal cord interface (BMSI) that is envisioned to convert in real time the neural command signals recorded from the brain to electrical stimuli delivered to the spinal cord below the injury level. Specifically, the paper reports on a corticospinal interface integrated circuit (IC) as a core building block for such a BMSI that is capable of low-noise recording of extracellular neural spikes from the cerebral cortex as well as muscle activation using intraspinal microstimulation (ISMS) in a rat with contusion injury to the thoracic spinal cord. The paper further presents results from a neurobiological study conducted in both normal and SCI rats to investigate the effect of various ISMS parameters on movement thresholds in the rat hindlimb. Coupled with proper signal-processing algorithms in the future for the transformation between the cortically recorded data and ISMS parameters, such a BMSI has the potential to facilitate functional recovery after an SCI by re-establishing corticospinal communication channels lost due to the injury.

Engineering-Aligned 3D Neural Circuit in Microfluidic Device.

PubMed

Bang, Seokyoung; Na, Sangcheol; Jang, Jae Myung; Kim, Jinhyun; Jeon, Noo Li

2016-01-07

The brain is one of the most important and complex organs in the human body. Although various neural network models have been proposed for in vitro 3D neuronal networks, it has been difficult to mimic functional and structural complexity of the in vitro neural circuit. Here, a microfluidic model of a simplified 3D neural circuit is reported. First, the microfluidic device is filled with Matrigel and continuous flow is delivered across the device during gelation. The fluidic flow aligns the extracellular matrix (ECM) components along the flow direction. Following the alignment of ECM fibers, neurites of primary rat cortical neurons are grown into the Matrigel at the average speed of 250 μm d(-1) and form axon bundles approximately 1500 μm in length at 6 days in vitro (DIV). Additionally, neural networks are developed from presynaptic to postsynaptic neurons at 14 DIV. The establishment of aligned 3D neural circuits is confirmed with the immunostaining of PSD-95 and synaptophysin and the observation of calcium signal transmission. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Integration of Nanobots Into Neural Circuits As a Future Therapy for Treating Neurodegenerative Disorders.

PubMed

Saniotis, Arthur; Henneberg, Maciej; Sawalma, Abdul-Rahman

2018-01-01

Recent neuroscientific research demonstrates that the human brain is becoming altered by technological devices. Improvements in biotechnologies and computer based technologies are now increasing the likelihood for the development of brain augmentation devices in the next 20 years. We have developed the idea of an "Endomyccorhizae like interface" (ELI) nanocognitive device as a new kind of future neuroprosthetic which aims to facilitate neuronal network properties in individuals with neurodegenerative disorders. The design of our ELI may overcome the problems of invasive neuroprosthetics, post-operative inflammation, and infection and neuroprosthetic degradation. The method in which our ELI is connected and integrated to neuronal networks is based on a mechanism similar to endomyccorhizae which is the oldest and most widespread form of plant symbiosis. We propose that the principle of Endomyccorhizae could be relevant for developing a crossing point between the ELI and neuronal networks. Similar to endomyccorhizae the ELI will be designed to form webs, each of which connects multiple neurons together. The ELI will function to sense action potentials and deliver it to the neurons it connects to. This is expected to compensate for neuronal loss in some neurodegenerative disorders, such as Alzheimer's disease and Parkinson's disease.

Stochastic Spiking Neural Networks Enabled by Magnetic Tunnel Junctions: From Nontelegraphic to Telegraphic Switching Regimes

NASA Astrophysics Data System (ADS)

Liyanagedera, Chamika M.; Sengupta, Abhronil; Jaiswal, Akhilesh; Roy, Kaushik

2017-12-01

Stochastic spiking neural networks based on nanoelectronic spin devices can be a possible pathway to achieving "brainlike" compact and energy-efficient cognitive intelligence. The computational model attempt to exploit the intrinsic device stochasticity of nanoelectronic synaptic or neural components to perform learning or inference. However, there has been limited analysis on the scaling effect of stochastic spin devices and its impact on the operation of such stochastic networks at the system level. This work attempts to explore the design space and analyze the performance of nanomagnet-based stochastic neuromorphic computing architectures for magnets with different barrier heights. We illustrate how the underlying network architecture must be modified to account for the random telegraphic switching behavior displayed by magnets with low barrier heights as they are scaled into the superparamagnetic regime. We perform a device-to-system-level analysis on a deep neural-network architecture for a digit-recognition problem on the MNIST data set.

The roles of carrier concentration and interface, bulk, and grain-boundary recombination for 25% efficient CdTe solar cells

DOE PAGES

Kanevce, A.; Reese, Matthew O.; Barnes, T. M.; ...

2017-06-06

CdTe devices have reached efficiencies of 22% due to continuing improvements in bulk material properties, including minority carrier lifetime. Device modeling has helped to guide these device improvements by quantifying the impacts of material properties and different device designs on device performance. One of the barriers to truly predictive device modeling is the interdependence of these material properties. For example, interfaces become more critical as bulk properties, particularly, hole density and carrier lifetime, increase. We present device-modeling analyses that describe the effects of recombination at the interfaces and grain boundaries as lifetime and doping of the CdTe layer change. Themore » doping and lifetime should be priorities for maximizing open-circuit voltage (V oc) and efficiency improvements. However, interface and grain boundary recombination become bottlenecks for device performance at increased lifetime and doping levels. In conclusion, this work quantifies and discusses these emerging challenges for next-generation CdTe device efficiency.« less

An FPGA Platform for Real-Time Simulation of Spiking Neuronal Networks

PubMed Central

Pani, Danilo; Meloni, Paolo; Tuveri, Giuseppe; Palumbo, Francesca; Massobrio, Paolo; Raffo, Luigi

2017-01-01

In the last years, the idea to dynamically interface biological neurons with artificial ones has become more and more urgent. The reason is essentially due to the design of innovative neuroprostheses where biological cell assemblies of the brain can be substituted by artificial ones. For closed-loop experiments with biological neuronal networks interfaced with in silico modeled networks, several technological challenges need to be faced, from the low-level interfacing between the living tissue and the computational model to the implementation of the latter in a suitable form for real-time processing. Field programmable gate arrays (FPGAs) can improve flexibility when simple neuronal models are required, obtaining good accuracy, real-time performance, and the possibility to create a hybrid system without any custom hardware, just programming the hardware to achieve the required functionality. In this paper, this possibility is explored presenting a modular and efficient FPGA design of an in silico spiking neural network exploiting the Izhikevich model. The proposed system, prototypically implemented on a Xilinx Virtex 6 device, is able to simulate a fully connected network counting up to 1,440 neurons, in real-time, at a sampling rate of 10 kHz, which is reasonable for small to medium scale extra-cellular closed-loop experiments. PMID:28293163

The Use of Semitranslucent Rubber Pledgets During Microsurgical Dissection of Cerebellopontine Angle Tumors: Technical Note.

PubMed

Mazur, Marcus D; Gurgel, Richard; MacDonald, Joel D

2018-01-01

Dissection of cerebellopontine angle (CPA) tumors that abut or adhere to the brainstem or cranial nerves can be a challenging surgical endeavor. We describe the use of semitranslucent latex rubber pledgets in the tumor-brain interface as a method to improve visualization and protection of vital tissue during microsurgical dissection of CPA masses. The rubber pledgets are fashioned by cutting circular discs out of the cuff portion of talc-free, partially opaque latex gloves. These pledgets provide a semitranslucent, nonadherent membrane that can be placed between vital neural tissues and a tumor capsule to minimize trauma during dissection. The semitranslucent latex enables visualization of the underlying anatomical structures while also providing a protective surface onto which a suction device can be rested to facilitate clearance of the surgical field. A 56-yr-old woman with left ear tinnitus presented with a 3-cm CPA meningioma. During microsurgical dissection, rubber pledgets were used to preserve the interface between the brain stem, cranial nerves, and tumor capsule. The use of the rubber pledgets appeared to secure the interface between to tumor and the brain while at the same time protecting the cranial nerves, brainstem, and cerebellum. Semitranslucent rubber pledgets may facilitate microsurgical dissection of CPA tumors. Copyright © 2017 by the Congress of Neurological Surgeons

Spatial light modulators and applications III; Proceedings of the Meeting, San Diego, CA, Aug. 7, 8, 1989

NASA Astrophysics Data System (ADS)

Efron, Uzi

Recent advances in the technology and applications of spatial light modulators (SLMs) are discussed in review essays by leading experts. Topics addressed include materials for SLMs, SLM devices and device technology, applications to optical data processing, and applications to artificial neural networks. Particular attention is given to nonlinear optical polymers, liquid crystals, magnetooptic SLMs, multiple-quantum-well SLMs, deformable-mirror SLMs, three-dimensional optical memories, applications of photorefractive devices to optical computing, photonic neurocomputers and learning machines, holographic associative memories, SLMs as parallel memories for optoelectronic neural networks, and coherent-optics implementations of neural-network models.

Spatial light modulators and applications III; Proceedings of the Meeting, San Diego, CA, Aug. 7, 8, 1989

NASA Technical Reports Server (NTRS)

Efron, Uzi (Editor)

1990-01-01

Recent advances in the technology and applications of spatial light modulators (SLMs) are discussed in review essays by leading experts. Topics addressed include materials for SLMs, SLM devices and device technology, applications to optical data processing, and applications to artificial neural networks. Particular attention is given to nonlinear optical polymers, liquid crystals, magnetooptic SLMs, multiple-quantum-well SLMs, deformable-mirror SLMs, three-dimensional optical memories, applications of photorefractive devices to optical computing, photonic neurocomputers and learning machines, holographic associative memories, SLMs as parallel memories for optoelectronic neural networks, and coherent-optics implementations of neural-network models.

Programmable Nano-Bio Interfaces for Functional Biointegrated Devices.

PubMed

Cai, Pingqiang; Leow, Wan Ru; Wang, Xiaoyuan; Wu, Yun-Long; Chen, Xiaodong

2017-07-01

A large amount of evidence has demonstrated the revolutionary role of nanosystems in the screening and shielding of biological systems. The explosive development of interfacing bioentities with programmable nanomaterials has conveyed the intriguing concept of nano-bio interfaces. Here, recent advances in functional biointegrated devices through the precise programming of nano-bio interactions are outlined, especially with regard to the rational assembly of constituent nanomaterials on multiple dimension scales (e.g., nanoparticles, nanowires, layered nanomaterials, and 3D-architectured nanomaterials), in order to leverage their respective intrinsic merits for different functions. Emerging nanotechnological strategies at nano-bio interfaces are also highlighted, such as multimodal diagnosis or "theragnostics", synergistic and sequential therapeutics delivery, and stretchable and flexible nanoelectronic devices, and their implementation into a broad range of biointegrated devices (e.g., implantable, minimally invasive, and wearable devices). When utilized as functional modules of biointegrated devices, these programmable nano-bio interfaces will open up a new chapter for precision nanomedicine. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

DARPA challenge: developing new technologies for brain and spinal injuries

NASA Astrophysics Data System (ADS)

Macedonia, Christian; Zamisch, Monica; Judy, Jack; Ling, Geoffrey

2012-06-01

The repair of traumatic injuries to the central nervous system remains among the most challenging and exciting frontiers in medicine. In both traumatic brain injury and spinal cord injuries, the ultimate goals are to minimize damage and foster recovery. Numerous DARPA initiatives are in progress to meet these goals. The PREventing Violent Explosive Neurologic Trauma program focuses on the characterization of non-penetrating brain injuries resulting from explosive blast, devising predictive models and test platforms, and creating strategies for mitigation and treatment. To this end, animal models of blast induced brain injury are being established, including swine and non-human primates. Assessment of brain injury in blast injured humans will provide invaluable information on brain injury associated motor and cognitive dysfunctions. The Blast Gauge effort provided a device to measure warfighter's blast exposures which will contribute to diagnosing the level of brain injury. The program Cavitation as a Damage Mechanism for Traumatic Brain Injury from Explosive Blast developed mathematical models that predict stresses, strains, and cavitation induced from blast exposures, and is devising mitigation technologies to eliminate injuries resulting from cavitation. The Revolutionizing Prosthetics program is developing an avant-garde prosthetic arm that responds to direct neural control and provides sensory feedback through electrical stimulation. The Reliable Neural-Interface Technology effort will devise technologies to optimally extract information from the nervous system to control next generation prosthetic devices with high fidelity. The emerging knowledge and technologies arising from these DARPA programs will significantly improve the treatment of brain and spinal cord injured patients.

Brain-Computer Interface for Clinical Purposes: Cognitive Assessment and Rehabilitation.

PubMed

Carelli, Laura; Solca, Federica; Faini, Andrea; Meriggi, Paolo; Sangalli, Davide; Cipresso, Pietro; Riva, Giuseppe; Ticozzi, Nicola; Ciammola, Andrea; Silani, Vincenzo; Poletti, Barbara

2017-01-01

Alongside the best-known applications of brain-computer interface (BCI) technology for restoring communication abilities and controlling external devices, we present the state of the art of BCI use for cognitive assessment and training purposes. We first describe some preliminary attempts to develop verbal-motor free BCI-based tests for evaluating specific or multiple cognitive domains in patients with Amyotrophic Lateral Sclerosis, disorders of consciousness, and other neurological diseases. Then we present the more heterogeneous and advanced field of BCI-based cognitive training, which has its roots in the context of neurofeedback therapy and addresses patients with neurological developmental disorders (autism spectrum disorder and attention-deficit/hyperactivity disorder), stroke patients, and elderly subjects. We discuss some advantages of BCI for both assessment and training purposes, the former concerning the possibility of longitudinally and reliably evaluating cognitive functions in patients with severe motor disabilities, the latter regarding the possibility of enhancing patients' motivation and engagement for improving neural plasticity. Finally, we discuss some present and future challenges in the BCI use for the described purposes.

Next generation brain implant coatings and nerve regeneration via novel conductive nanocomposite development.

PubMed

Antoniadou, Eleni V; Ahmad, Rezal K; Jackman, Richard B; Seifalian, Alexander M

2011-01-01

Composite materials based on the coupling of conductive organic polymers and carbon nanotubes have shown that they possess properties of the individual components with a synergistic effect. Multi-wall carbon nanotube (MWCNT)/ polymer composites are hybrid materials that combine numerous mechanical, electrical and chemical properties and thus, constitute ideal biomaterials for a wide range of regenerative medicine applications. Although, complete dispersion of CNT in a polymer matrix has rarely been achieved, in this study we have succeeded high dispersibility of CNT in POSS-PCU and POSS-PCL, novel polymers based on polyprolactone and polycarbonate polyurethane (PCU) and poly(caprolactoneurea)urethane both having incorporated polyhedral oligomeric silsesquioxane (POSS). We report the synthesis and characterization of a novel biomaterial that possesses unique properties of being electrically conducting and thus being capable of electronic interfacing with tissue. To this end, POSS-PCU/MWCNT composite can be used as a biomaterial for the development of nerve guidance channels to promote nerve regeneration and POSS-PCL/MWCNT as a substrate to increase electronic interfacing between neurons and micro-machined electrodes for potential applications in neural probes, prosthetic devices and brain implants.

3D silicon neural probe with integrated optical fibers for optogenetic modulation.

PubMed

Kim, Eric G R; Tu, Hongen; Luo, Hao; Liu, Bin; Bao, Shaowen; Zhang, Jinsheng; Xu, Yong

2015-07-21

Optogenetics is a powerful modality for neural modulation that can be useful for a wide array of biomedical studies. Penetrating microelectrode arrays provide a means of recording neural signals with high spatial resolution. It is highly desirable to integrate optics with neural probes to allow for functional study of neural tissue by optogenetics. In this paper, we report the development of a novel 3D neural probe coupled simply and robustly to optical fibers using a hollow parylene tube structure. The device shanks are hollow tubes with rigid silicon tips, allowing the insertion and encasement of optical fibers within the shanks. The position of the fiber tip can be precisely controlled relative to the electrodes on the shank by inherent design features. Preliminary in vivo rat studies indicate that these devices are capable of optogenetic modulation simultaneously with 3D neural signal recording.

Nonvolatile Ionic Two-Terminal Memory Device

NASA Technical Reports Server (NTRS)

Williams, Roger M.

1990-01-01

Conceptual solid-state memory device nonvolatile and erasable and has only two terminals. Proposed device based on two effects: thermal phase transition and reversible intercalation of ions. Transfer of sodium ions between source of ions and electrical switching element increases or decreases electrical conductance of element, turning switch "on" or "off". Used in digital computers and neural-network computers. In neural networks, many small, densely packed switches function as erasable, nonvolatile synaptic elements.

A Multi-purpose Brain-Computer Interface Output Device

PubMed Central

Thompson, David E; Huggins, Jane E

2012-01-01

While brain-computer interfaces (BCIs) are a promising alternative access pathway for individuals with severe motor impairments, many BCI systems are designed as standalone communication and control systems, rather than as interfaces to existing systems built for these purposes. While an individual communication and control system may be powerful or flexible, no single system can compete with the variety of options available in the commercial assistive technology (AT) market. BCIs could instead be used as an interface to these existing AT devices and products, which are designed for improving access and agency of people with disabilities and are highly configurable to individual user needs. However, interfacing with each AT device and program requires significant time and effort on the part of researchers and clinicians. This work presents the Multi-Purpose BCI Output Device (MBOD), a tool to help researchers and clinicians provide BCI control of many forms of AT in a plug-and-play fashion, i.e. without the installation of drivers or software on the AT device, and a proof-of-concept of the practicality of such an approach. The MBOD was designed to meet the goals of target device compatibility, BCI input device compatibility, convenience, and intuitive command structure. The MBOD was successfully used to interface a BCI with multiple AT devices (including two wheelchair seating systems), as well as computers running Windows (XP and 7), Mac and Ubuntu Linux operating systems. PMID:22208120

A multi-purpose brain-computer interface output device.

PubMed

Thompson, David E; Huggins, Jane E

2011-10-01

While brain-computer interfaces (BCIs) are a promising alternative access pathway for individuals with severe motor impairments, many BCI systems are designed as stand-alone communication and control systems, rather than as interfaces to existing systems built for these purposes. An individual communication and control system may be powerful or flexible, but no single system can compete with the variety of options available in the commercial assistive technology (AT) market. BCls could instead be used as an interface to these existing AT devices and products, which are designed for improving access and agency of people with disabilities and are highly configurable to individual user needs. However, interfacing with each AT device and program requires significant time and effort on the part of researchers and clinicians. This work presents the Multi-Purpose BCI Output Device (MBOD), a tool to help researchers and clinicians provide BCI control of many forms of AT in a plug-and-play fashion, i.e., without the installation of drivers or software on the AT device, and a proof-of-concept of the practicality of such an approach. The MBOD was designed to meet the goals of target device compatibility, BCI input device compatibility, convenience, and intuitive command structure. The MBOD was successfully used to interface a BCI with multiple AT devices (including two wheelchair seating systems), as well as computers running Windows (XP and 7), Mac and Ubuntu Linux operating systems.

Synergistic Gating of Electro-Iono-Photoactive 2D Chalcogenide Neuristors: Coexistence of Hebbian and Homeostatic Synaptic Metaplasticity.

PubMed

John, Rohit Abraham; Liu, Fucai; Chien, Nguyen Anh; Kulkarni, Mohit R; Zhu, Chao; Fu, Qundong; Basu, Arindam; Liu, Zheng; Mathews, Nripan

2018-06-01

Emulation of brain-like signal processing with thin-film devices can lay the foundation for building artificially intelligent learning circuitry in future. Encompassing higher functionalities into single artificial neural elements will allow the development of robust neuromorphic circuitry emulating biological adaptation mechanisms with drastically lesser neural elements, mitigating strict process challenges and high circuit density requirements necessary to match the computational complexity of the human brain. Here, 2D transition metal di-chalcogenide (MoS 2 ) neuristors are designed to mimic intracellular ion endocytosis-exocytosis dynamics/neurotransmitter-release in chemical synapses using three approaches: (i) electronic-mode: a defect modulation approach where the traps at the semiconductor-dielectric interface are perturbed; (ii) ionotronic-mode: where electronic responses are modulated via ionic gating; and (iii) photoactive-mode: harnessing persistent photoconductivity or trap-assisted slow recombination mechanisms. Exploiting a novel multigated architecture incorporating electrical and optical biases, this incarnation not only addresses different charge-trapping probabilities to finely modulate the synaptic weights, but also amalgamates neuromodulation schemes to achieve "plasticity of plasticity-metaplasticity" via dynamic control of Hebbian spike-time dependent plasticity and homeostatic regulation. Coexistence of such multiple forms of synaptic plasticity increases the efficacy of memory storage and processing capacity of artificial neuristors, enabling design of highly efficient novel neural architectures. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A VLSI Neural Monitoring System With Ultra-Wideband Telemetry for Awake Behaving Subjects.

PubMed

Greenwald, E; Mollazadeh, M; Hu, C; Wei Tang; Culurciello, E; Thakor, V

2011-04-01

Long-term monitoring of neuronal activity in awake behaving subjects can provide fundamental information about brain dynamics for neuroscience and neuroengineering applications. Here, we present a miniature, lightweight, and low-power recording system for monitoring neural activity in awake behaving animals. The system integrates two custom designed very-large-scale integrated chips, a neural interface module fabricated in 0.5 μm complementary metal-oxide semiconductor technology and an ultra-wideband transmitter module fabricated in a 0.5 μm silicon-on-sapphire (SOS) technology. The system amplifies, filters, digitizes, and transmits 16 channels of neural data at a rate of 1 Mb/s. The entire system, which includes the VLSI circuits, a digital interface board, a battery, and a custom housing, is small and lightweight (24 g) and, thus, can be chronically mounted on small animals. The system consumes 4.8 mA and records continuously for up to 40 h powered by a 3.7-V, 200-mAh rechargeable lithium-ion battery. Experimental benchtop characterizations as well as in vivo multichannel neural recordings from awake behaving rats are presented here.

Device USB interface and software development for electric parameter measuring instrument

NASA Astrophysics Data System (ADS)

Li, Deshi; Chen, Jian; Wu, Yadong

2003-09-01

Aimed at general devices development, this paper discussed the development of USB interface and software development. With an example, using PDIUSBD12 which support parallel interface, the paper analyzed its technical characteristics. Designed different interface circuit with 80C52 singlechip microcomputer and TMS320C54 series digital signal processor, analyzed the address allocation, register access. According to USB1.1 standard protocol, designed the device software and application layer protocol. The paper designed the data exchange protocol, and carried out system functions.

The 128-channel fully differential digital integrated neural recording and stimulation interface.

PubMed

Shahrokhi, Farzaneh; Abdelhalim, Karim; Serletis, Demitre; Carlen, Peter L; Genov, Roman

2010-06-01

We present a fully differential 128-channel integrated neural interface. It consists of an array of 8 X 16 low-power low-noise signal-recording and generation circuits for electrical neural activity monitoring and stimulation, respectively. The recording channel has two stages of signal amplification and conditioning with and a fully differential 8-b column-parallel successive approximation (SAR) analog-to-digital converter (ADC). The total measured power consumption of each recording channel, including the SAR ADC, is 15.5 ¿W. The measured input-referred noise is 6.08 ¿ Vrms over a 5-kHz bandwidth, resulting in a noise efficiency factor of 5.6. The stimulation channel performs monophasic or biphasic voltage-mode stimulation, with a maximum stimulation current of 5 mA and a quiescent power dissipation of 51.5 ¿W. The design is implemented in 0.35-¿m complementary metal-oxide semiconductor technology with the channel pitch of 200 ¿m for a total die size of 3.4 mm × 2.5 mm and a total power consumption of 9.33 mW. The neural interface was validated in in vitro recording of a low-Mg(2+)/high-K(+) epileptic seizure model in an intact hippocampus of a mouse.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Winkelmann, Joseph P. (Inventor); Konz, Daniel W. (Inventor)

2009-01-01

A communications system and method are provided for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is converted into digital signals and transmitted to the controller. Network device interfaces associated with different data channels can coordinate communications with the other interfaces based on either a transition in a command message sent by the bus controller or a synchronous clock signal.

A Sub-millimeter, Inductively Powered Neural Stimulator

PubMed Central

Freeman, Daniel K.; O'Brien, Jonathan M.; Kumar, Parshant; Daniels, Brian; Irion, Reed A.; Shraytah, Louis; Ingersoll, Brett K.; Magyar, Andrew P.; Czarnecki, Andrew; Wheeler, Jesse; Coppeta, Jonathan R.; Abban, Michael P.; Gatzke, Ronald; Fried, Shelley I.; Lee, Seung Woo; Duwel, Amy E.; Bernstein, Jonathan J.; Widge, Alik S.; Hernandez-Reynoso, Ana; Kanneganti, Aswini; Romero-Ortega, Mario I.; Cogan, Stuart F.

2017-01-01

Wireless neural stimulators are being developed to address problems associated with traditional lead-based implants. However, designing wireless stimulators on the sub-millimeter scale (<1 mm3) is challenging. As device size shrinks, it becomes difficult to deliver sufficient wireless power to operate the device. Here, we present a sub-millimeter, inductively powered neural stimulator consisting only of a coil to receive power, a capacitor to tune the resonant frequency of the receiver, and a diode to rectify the radio-frequency signal to produce neural excitation. By replacing any complex receiver circuitry with a simple rectifier, we have reduced the required voltage levels that are needed to operate the device from 0.5 to 1 V (e.g., for CMOS) to ~0.25–0.5 V. This reduced voltage allows the use of smaller receive antennas for power, resulting in a device volume of 0.3–0.5 mm3. The device was encapsulated in epoxy, and successfully passed accelerated lifetime tests in 80°C saline for 2 weeks. We demonstrate a basic proof-of-concept using stimulation with tens of microamps of current delivered to the sciatic nerve in rat to produce a motor response. PMID:29230164

Studying the glial cell response to biomaterials and surface topography for improving the neural electrode interface

NASA Astrophysics Data System (ADS)

Ereifej, Evon S.

Neural electrode devices hold great promise to help people with the restoration of lost functions, however, research is lacking in the biomaterial design of a stable, long-term device. Current devices lack long term functionality, most have been found unable to record neural activity within weeks after implantation due to the development of glial scar tissue (Polikov et al., 2006; Zhong and Bellamkonda, 2008). The long-term effect of chronically implanted electrodes is the formation of a glial scar made up of reactive astrocytes and the matrix proteins they generate (Polikov et al., 2005; Seil and Webster, 2008). Scarring is initiated when a device is inserted into brain tissue and is associated with an inflammatory response. Activated astrocytes are hypertrophic, hyperplastic, have an upregulation of intermediate filaments GFAP and vimentin expression, and filament formation (Buffo et al., 2010; Gervasi et al., 2008). Current approaches towards inhibiting the initiation of glial scarring range from altering the geometry, roughness, size, shape and materials of the device (Grill et al., 2009; Kotov et al., 2009; Kotzar et al., 2002; Szarowski et al., 2003). Literature has shown that surface topography modifications can alter cell alignment, adhesion, proliferation, migration, and gene expression (Agnew et al., 1983; Cogan et al., 2005; Cogan et al., 2006; Merrill et al., 2005). Thus, the goals of the presented work are to study the cellular response to biomaterials used in neural electrode fabrication and assess surface topography effects on minimizing astrogliosis. Initially, to examine astrocyte response to various materials used in neural electrode fabrication, astrocytes were cultured on platinum, silicon, PMMA, and SU-8 surfaces, with polystyrene as the control surface. Cell proliferation, viability, morphology and gene expression was measured for seven days in vitro. Results determined the cellular characteristics, reactions and growth rates of astrocytes grown on PMMA resembled closely to that of cells grown on the control surface, thus confirming the biocompatibility of PMMA. Additionally, the astrocyte GFAP gene expressions of cells grown on PMMA were lower than the control, signifying a lack of astrocyte reactivity. Based on the findings from the biomaterials study, it was decided to optimize PMMA by changing the surface characteristic of the material. Through the process of hot embossing, nanopatterns were placed on the surface in order to test the hypothesis that nanopatterning can improve the cellular response to the material. Results of this study agreed with current literature showing that topography effects protein and cell behavior. It was concluded that for the use in neural electrode fabrication and design, the 3600mm/gratings pattern feature sizes were optimal. The 3600 mm/gratings pattern depicted cell alignment along the nanopattern, less protein adsorption, less cell adhesion, proliferation and viability, inhibition of GFAP and MAP2k1 compared to all other substrates tested. Results from the initial biomaterials study also indicated platinum was negatively affected the cells and may not be a suitable material for neural electrodes. This lead to pursuing studies with iridium oxide and platinum alloy wires for the glial scar assay. Iridium oxide advantages of lower impedance and higher charge injection capacity would appear to make iridium oxide more favorable for neural electrode fabrication. However, results of this study demonstrate iridium oxide wires exhibited a more significant reactive response as compared to platinum alloy wires. Astrocytes cultured with platinum alloy wires had less GFAP gene expression, lower average GFAP intensity, and smaller glial scar thickness. Results from the nanopatterning PMMA study prompted a more thorough investigation of the nanopatterning effects using an organotypic brain slice model. PDMS was utilized as the substrate due to its optimal physical properties. Confocal and SEM imaging illustrated cells from the brain tissue slices were aligned along the nanopattern on the PDMS pins. Decreases in several inflammatory markers (GFAP, TNFα, IL-1beta) determined from gene expression analysis, was shown with the nanopatterned PDMS pins. Results of this study confirm nanopatterning not only influences cell morphology, but alters molecular cascades within the cells as well. The results of these studies provide essential information for the neural electrode research community. There is a lack of information available in the scientific community on acceptable and effective materials for neural electrode fabrication. The results of the presented studies provide more information which could lead to classifying guidelines to create biocompatible neural electrode materials. This research project was partially supported by the Wayne State University President's Translational Enhancement Award and by the Kales Scholarship for Biomedical Engineering students.

Quantum neural networks: Current status and prospects for development

NASA Astrophysics Data System (ADS)

Altaisky, M. V.; Kaputkina, N. E.; Krylov, V. A.

2014-11-01

The idea of quantum artificial neural networks, first formulated in [34], unites the artificial neural network concept with the quantum computation paradigm. Quantum artificial neural networks were first systematically considered in the PhD thesis by T. Menneer (1998). Based on the works of Menneer and Narayanan [42, 43], Kouda, Matsui, and Nishimura [35, 36], Altaisky [2, 68], Zhou [67], and others, quantum-inspired learning algorithms for neural networks were developed, and are now used in various training programs and computer games [29, 30]. The first practically realizable scaled hardware-implemented model of the quantum artificial neural network is obtained by D-Wave Systems, Inc. [33]. It is a quantum Hopfield network implemented on the basis of superconducting quantum interference devices (SQUIDs). In this work we analyze possibilities and underlying principles of an alternative way to implement quantum neural networks on the basis of quantum dots. A possibility of using quantum neural network algorithms in automated control systems, associative memory devices, and in modeling biological and social networks is examined.

Rehabilitation of gait after stroke: a review towards a top-down approach

PubMed Central

2011-01-01

This document provides a review of the techniques and therapies used in gait rehabilitation after stroke. It also examines the possible benefits of including assistive robotic devices and brain-computer interfaces in this field, according to a top-down approach, in which rehabilitation is driven by neural plasticity. The methods reviewed comprise classical gait rehabilitation techniques (neurophysiological and motor learning approaches), functional electrical stimulation (FES), robotic devices, and brain-computer interfaces (BCI). From the analysis of these approaches, we can draw the following conclusions. Regarding classical rehabilitation techniques, there is insufficient evidence to state that a particular approach is more effective in promoting gait recovery than other. Combination of different rehabilitation strategies seems to be more effective than over-ground gait training alone. Robotic devices need further research to show their suitability for walking training and their effects on over-ground gait. The use of FES combined with different walking retraining strategies has shown to result in improvements in hemiplegic gait. Reports on non-invasive BCIs for stroke recovery are limited to the rehabilitation of upper limbs; however, some works suggest that there might be a common mechanism which influences upper and lower limb recovery simultaneously, independently of the limb chosen for the rehabilitation therapy. Functional near infrared spectroscopy (fNIRS) enables researchers to detect signals from specific regions of the cortex during performance of motor activities for the development of future BCIs. Future research would make possible to analyze the impact of rehabilitation on brain plasticity, in order to adapt treatment resources to meet the needs of each patient and to optimize the recovery process. PMID:22165907

Role of point defects and HfO2/TiN interface stoichiometry on effective work function modulation in ultra-scaled complementary metal-oxide-semiconductor devices

NASA Astrophysics Data System (ADS)

Pandey, R. K.; Sathiyanarayanan, Rajesh; Kwon, Unoh; Narayanan, Vijay; Murali, K. V. R. M.

2013-07-01

We investigate the physical properties of a portion of the gate stack of an ultra-scaled complementary metal-oxide-semiconductor (CMOS) device. The effects of point defects, such as oxygen vacancy, oxygen, and aluminum interstitials at the HfO2/TiN interface, on the effective work function of TiN are explored using density functional theory. We compute the diffusion barriers of such point defects in the bulk TiN and across the HfO2/TiN interface. Diffusion of these point defects across the HfO2/TiN interface occurs during the device integration process. This results in variation of the effective work function and hence in the threshold voltage variation in the devices. Further, we simulate the effects of varying the HfO2/TiN interface stoichiometry on the effective work function modulation in these extremely-scaled CMOS devices. Our results show that the interface rich in nitrogen gives higher effective work function, whereas the interface rich in titanium gives lower effective work function, compared to a stoichiometric HfO2/TiN interface. This theoretical prediction is confirmed by the experiment, demonstrating over 700 meV modulation in the effective work function.

Defining brain-machine interface applications by matching interface performance with device requirements.

PubMed

Tonet, Oliver; Marinelli, Martina; Citi, Luca; Rossini, Paolo Maria; Rossini, Luca; Megali, Giuseppe; Dario, Paolo

2008-01-15

Interaction with machines is mediated by human-machine interfaces (HMIs). Brain-machine interfaces (BMIs) are a particular class of HMIs and have so far been studied as a communication means for people who have little or no voluntary control of muscle activity. In this context, low-performing interfaces can be considered as prosthetic applications. On the other hand, for able-bodied users, a BMI would only be practical if conceived as an augmenting interface. In this paper, a method is introduced for pointing out effective combinations of interfaces and devices for creating real-world applications. First, devices for domotics, rehabilitation and assistive robotics, and their requirements, in terms of throughput and latency, are described. Second, HMIs are classified and their performance described, still in terms of throughput and latency. Then device requirements are matched with performance of available interfaces. Simple rehabilitation and domotics devices can be easily controlled by means of BMI technology. Prosthetic hands and wheelchairs are suitable applications but do not attain optimal interactivity. Regarding humanoid robotics, the head and the trunk can be controlled by means of BMIs, while other parts require too much throughput. Robotic arms, which have been controlled by means of cortical invasive interfaces in animal studies, could be the next frontier for non-invasive BMIs. Combining smart controllers with BMIs could improve interactivity and boost BMI applications.

Devices and circuits for nanoelectronic implementation of artificial neural networks

NASA Astrophysics Data System (ADS)

Turel, Ozgur

Biological neural networks perform complicated information processing tasks at speeds better than conventional computers based on conventional algorithms. This has inspired researchers to look into the way these networks function, and propose artificial networks that mimic their behavior. Unfortunately, most artificial neural networks, either software or hardware, do not provide either the speed or the complexity of a human brain. Nanoelectronics, with high density and low power dissipation that it provides, may be used in developing more efficient artificial neural networks. This work consists of two major contributions in this direction. First is the proposal of the CMOL concept, hybrid CMOS-molecular hardware [1-8]. CMOL may circumvent most of the problems in posed by molecular devices, such as low yield, vet provide high active device density, ˜1012/cm 2. The second contribution is CrossNets, artificial neural networks that are based on CMOL. We showed that CrossNets, with their fault tolerance, exceptional speed (˜ 4 to 6 orders of magnitude faster than biological neural networks) can perform any task any artificial neural network can perform. Moreover, there is a hope that if their integration scale is increased to that of human cerebral cortex (˜ 1010 neurons and ˜ 1014 synapses), they may be capable of performing more advanced tasks.

Flexible Architecture for FPGAs in Embedded Systems

NASA Technical Reports Server (NTRS)

Clark, Duane I.; Lim, Chester N.

2012-01-01

Commonly, field-programmable gate arrays (FPGAs) being developed in cPCI embedded systems include the bus interface in the FPGA. This complicates the development because the interface is complicated and requires a lot of development time and FPGA resources. In addition, flight qualification requires a substantial amount of time be devoted to just this interface. Another complication of putting the cPCI interface into the FPGA being developed is that configuration information loaded into the device by the cPCI microprocessor is lost when a new bit file is loaded, requiring cumbersome operations to return the system to an operational state. Finally, SRAM-based FPGAs are typically programmed via specialized cables and software, with programming files being loaded either directly into the FPGA, or into PROM devices. This can be cumbersome when doing FPGA development in an embedded environment, and does not have an easy path to flight. Currently, FPGAs used in space applications are usually programmed via multiple space-qualified PROM devices that are physically large and require extra circuitry (typically including a separate one-time programmable FPGA) to enable them to be used for this application. This technology adds a cPCI interface device with a simple, flexible, high-performance backend interface supporting multiple backend FPGAs. It includes a mechanism for programming the FPGAs directly via the microprocessor in the embedded system, eliminating specialized hardware, software, and PROM devices and their associated circuitry. It has a direct path to flight, and no extra hardware and minimal software are required to support reprogramming in flight. The device added is currently a small FPGA, but an advantage of this technology is that the design of the device does not change, regardless of the application in which it is being used. This means that it needs to be qualified for flight only once, and is suitable for one-time programmable devices or an application specific integrated circuit (ASIC). An application programming interface (API) further reduces the development time needed to use the interface device in a system.

The upregulation of specific interleukin (IL) receptor antagonists and paradoxical enhancement of neuronal apoptosis due to electrode induced strain and brain micromotion.

PubMed

Karumbaiah, Lohitash; Norman, Sharon E; Rajan, Nithish B; Anand, Sanjay; Saxena, Tarun; Betancur, Martha; Patkar, Radhika; Bellamkonda, Ravi V

2012-09-01

The high mechanical mismatch between stiffness of silicon and metal microelectrodes and soft cortical tissue, induces strain at the neural interface which likely contributes to failure of the neural interface. However, little is known about the molecular outcomes of electrode induced low-magnitude strain (1-5%) on primary astrocytes, microglia and neurons. In this study we simulated brain micromotion at the electrode-brain interface by subjecting astrocytes, microglia and primary cortical neurons to low-magnitude cyclical strain using a biaxial stretch device, and investigated the molecular outcomes of induced strain in vitro. In addition, we explored the functional consequence of astrocytic and microglial strain on neural health, when they are themselves subjected to strain. Quantitative real-time PCR array (qRT-PCR Array) analysis of stretched astrocytes and microglia showed strain specific upregulation of an Interleukin receptor antagonist - IL-36Ra (previously IL-1F5), to ≈ 1018 and ≈ 236 fold respectively. Further, IL-36Ra gene expression remained unchanged in astrocytes and microglia treated with bacterial lipopolysaccharide (LPS) indicating that the observed upregulation in stretched astrocytes and microglia is potentially strain specific. Zymogram and western blot analysis revealed that mechanically strained astrocytes and microglia upregulated matrix metalloproteinases (MMPs) 2 and 9, and other markers of reactive gliosis such as glial fibrillary acidic protein (GFAP) and neurocan when compared to controls. Primary cortical neurons when stretched with and without IL-36Ra, showed a ≈ 400 fold downregulation of tumor necrosis factor receptor superfamily, member 11b (TNFRSF11b). Significant upregulation of members of the caspase cysteine proteinase family and other pro-apoptotic genes was also observed in the presence of IL-36Ra than in the absence of IL-36Ra. Adult rats when implanted with microwire electrodes showed upregulation of IL-36Ra (≈ 20 fold) and IL-1Ra (≈ 1500 fold) 3 days post-implantation (3 DPI), corroborating in vitro results, although these transcripts were drastically down regulated by ≈ 20 fold and ≈ 1488 fold relative to expression levels 3 DPI, at the end of 12 weeks post-implantation (12 WPI). These results demonstrate that IL receptor antagonists may be negatively contributing to neuronal health at acute time-points post-electrode implantation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Development and Implementation of the X.25 Protocol for the Universal Network Interface Device (UNID) II. Volume 1.

DTIC Science & Technology

1985-12-01

development of an improved Universal Network Interface Device (UNID II). The UNID II’s architecture was based on a preliminary design project at...interface device, performing all functions required ,: the multi-ring LAN. The device depicted by RADC’s studies would connect a highly variable group of host...used the ISO Open Systems Ilterconnection (OSI) seven layer model as the basic structure for data flow and program development . In 1982 Cuomo

APRON: A Cellular Processor Array Simulation and Hardware Design Tool

NASA Astrophysics Data System (ADS)

Barr, David R. W.; Dudek, Piotr

2009-12-01

We present a software environment for the efficient simulation of cellular processor arrays (CPAs). This software (APRON) is used to explore algorithms that are designed for massively parallel fine-grained processor arrays, topographic multilayer neural networks, vision chips with SIMD processor arrays, and related architectures. The software uses a highly optimised core combined with a flexible compiler to provide the user with tools for the design of new processor array hardware architectures and the emulation of existing devices. We present performance benchmarks for the software processor array implemented on standard commodity microprocessors. APRON can be configured to use additional processing hardware if necessary and can be used as a complete graphical user interface and development environment for new or existing CPA systems, allowing more users to develop algorithms for CPA systems.

Hand-in-hand advances in biomedical engineering and sensorimotor restoration.

PubMed

Pisotta, Iolanda; Perruchoud, David; Ionta, Silvio

2015-05-15

Living in a multisensory world entails the continuous sensory processing of environmental information in order to enact appropriate motor routines. The interaction between our body and our brain is the crucial factor for achieving such sensorimotor integration ability. Several clinical conditions dramatically affect the constant body-brain exchange, but the latest developments in biomedical engineering provide promising solutions for overcoming this communication breakdown. The ultimate technological developments succeeded in transforming neuronal electrical activity into computational input for robotic devices, giving birth to the era of the so-called brain-machine interfaces. Combining rehabilitation robotics and experimental neuroscience the rise of brain-machine interfaces into clinical protocols provided the technological solution for bypassing the neural disconnection and restore sensorimotor function. Based on these advances, the recovery of sensorimotor functionality is progressively becoming a concrete reality. However, despite the success of several recent techniques, some open issues still need to be addressed. Typical interventions for sensorimotor deficits include pharmaceutical treatments and manual/robotic assistance in passive movements. These procedures achieve symptoms relief but their applicability to more severe disconnection pathologies is limited (e.g. spinal cord injury or amputation). Here we review how state-of-the-art solutions in biomedical engineering are continuously increasing expectances in sensorimotor rehabilitation, as well as the current challenges especially with regards to the translation of the signals from brain-machine interfaces into sensory feedback and the incorporation of brain-machine interfaces into daily activities. Copyright © 2015 Elsevier B.V. All rights reserved.

Towards a real-time interface between a biomimetic model of sensorimotor cortex and a robotic arm

PubMed Central

Dura-Bernal, Salvador; Chadderdon, George L; Neymotin, Samuel A; Francis, Joseph T; Lytton, William W

2015-01-01

Brain-machine interfaces can greatly improve the performance of prosthetics. Utilizing biomimetic neuronal modeling in brain machine interfaces (BMI) offers the possibility of providing naturalistic motor-control algorithms for control of a robotic limb. This will allow finer control of a robot, while also giving us new tools to better understand the brain’s use of electrical signals. However, the biomimetic approach presents challenges in integrating technologies across multiple hardware and software platforms, so that the different components can communicate in real-time. We present the first steps in an ongoing effort to integrate a biomimetic spiking neuronal model of motor learning with a robotic arm. The biomimetic model (BMM) was used to drive a simple kinematic two-joint virtual arm in a motor task requiring trial-and-error convergence on a single target. We utilized the output of this model in real time to drive mirroring motion of a Barrett Technology WAM robotic arm through a user datagram protocol (UDP) interface. The robotic arm sent back information on its joint positions, which was then used by a visualization tool on the remote computer to display a realistic 3D virtual model of the moving robotic arm in real time. This work paves the way towards a full closed-loop biomimetic brain-effector system that can be incorporated in a neural decoder for prosthetic control, to be used as a platform for developing biomimetic learning algorithms for controlling real-time devices. PMID:26709323

Neural constraints on learning.

PubMed

Sadtler, Patrick T; Quick, Kristin M; Golub, Matthew D; Chase, Steven M; Ryu, Stephen I; Tyler-Kabara, Elizabeth C; Yu, Byron M; Batista, Aaron P

2014-08-28

Learning, whether motor, sensory or cognitive, requires networks of neurons to generate new activity patterns. As some behaviours are easier to learn than others, we asked if some neural activity patterns are easier to generate than others. Here we investigate whether an existing network constrains the patterns that a subset of its neurons is capable of exhibiting, and if so, what principles define this constraint. We employed a closed-loop intracortical brain-computer interface learning paradigm in which Rhesus macaques (Macaca mulatta) controlled a computer cursor by modulating neural activity patterns in the primary motor cortex. Using the brain-computer interface paradigm, we could specify and alter how neural activity mapped to cursor velocity. At the start of each session, we observed the characteristic activity patterns of the recorded neural population. The activity of a neural population can be represented in a high-dimensional space (termed the neural space), wherein each dimension corresponds to the activity of one neuron. These characteristic activity patterns comprise a low-dimensional subspace (termed the intrinsic manifold) within the neural space. The intrinsic manifold presumably reflects constraints imposed by the underlying neural circuitry. Here we show that the animals could readily learn to proficiently control the cursor using neural activity patterns that were within the intrinsic manifold. However, animals were less able to learn to proficiently control the cursor using activity patterns that were outside of the intrinsic manifold. These results suggest that the existing structure of a network can shape learning. On a timescale of hours, it seems to be difficult to learn to generate neural activity patterns that are not consistent with the existing network structure. These findings offer a network-level explanation for the observation that we are more readily able to learn new skills when they are related to the skills that we already possess.

A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm.

PubMed

Dethier, Julie; Nuyujukian, Paul; Eliasmith, Chris; Stewart, Terry; Elassaad, Shauki A; Shenoy, Krishna V; Boahen, Kwabena

2011-01-01

Motor prostheses aim to restore function to disabled patients. Despite compelling proof of concept systems, barriers to clinical translation remain. One challenge is to develop a low-power, fully-implantable system that dissipates only minimal power so as not to damage tissue. To this end, we implemented a Kalman-filter based decoder via a spiking neural network (SNN) and tested it in brain-machine interface (BMI) experiments with a rhesus monkey. The Kalman filter was trained to predict the arm's velocity and mapped on to the SNN using the Neural Engineering Framework (NEF). A 2,000-neuron embedded Matlab SNN implementation runs in real-time and its closed-loop performance is quite comparable to that of the standard Kalman filter. The success of this closed-loop decoder holds promise for hardware SNN implementations of statistical signal processing algorithms on neuromorphic chips, which may offer power savings necessary to overcome a major obstacle to the successful clinical translation of neural motor prostheses.

Next-generation probes, particles, and proteins for neural interfacing

PubMed Central

Rivnay, Jonathan; Wang, Huiliang; Fenno, Lief; Deisseroth, Karl; Malliaras, George G.

2017-01-01

Bidirectional interfacing with the nervous system enables neuroscience research, diagnosis, and therapy. This two-way communication allows us to monitor the state of the brain and its composite networks and cells as well as to influence them to treat disease or repair/restore sensory or motor function. To provide the most stable and effective interface, the tools of the trade must bridge the soft, ion-rich, and evolving nature of neural tissue with the largely rigid, static realm of microelectronics and medical instruments that allow for readout, analysis, and/or control. In this Review, we describe how the understanding of neural signaling and material-tissue interactions has fueled the expansion of the available tool set. New probe architectures and materials, nanoparticles, dyes, and designer genetically encoded proteins push the limits of recording and stimulation lifetime, localization, and specificity, blurring the boundary between living tissue and engineered tools. Understanding these approaches, their modality, and the role of cross-disciplinary development will support new neurotherapies and prostheses and provide neuroscientists and neurologists with unprecedented access to the brain. PMID:28630894

A Feasibility Study of Synthesizing Subsurfaces Modeled with Computational Neural Networks

NASA Technical Reports Server (NTRS)

Wang, John T.; Housner, Jerrold M.; Szewczyk, Z. Peter

1998-01-01

This paper investigates the feasibility of synthesizing substructures modeled with computational neural networks. Substructures are modeled individually with computational neural networks and the response of the assembled structure is predicted by synthesizing the neural networks. A superposition approach is applied to synthesize models for statically determinate substructures while an interface displacement collocation approach is used to synthesize statically indeterminate substructure models. Beam and plate substructures along with components of a complicated Next Generation Space Telescope (NGST) model are used in this feasibility study. In this paper, the limitations and difficulties of synthesizing substructures modeled with neural networks are also discussed.

In vivo testing of a 3D bifurcating microchannel scaffold inducing separation of regenerating axon bundles in peripheral nerves

NASA Astrophysics Data System (ADS)

Stoyanova, Irina I.; van Wezel, Richard J. A.; Rutten, Wim L. C.

2013-12-01

Artificial nerve guidance channels enhance the regenerative effectiveness in an injured peripheral nerve but the existing design so far has been limited to basic straight tubes simply guiding the growth to bridge the gap. Hence, one of the goals in development of more effective neuroprostheses is to create bidirectional highly selective neuro-electronic interface between a prosthetic device and the severed nerve. A step towards improving selectivity for both recording and stimulation have been made with some recent in vitro studies which showed that three-dimensional (3D) bifurcating microchannels can separate neurites growing on a planar surface and bring them into contact with individual electrodes. Since the growing axons in vivo have the innate tendency to group in bundles surrounded by connective tissue, one of the big challenges in neuro-prosthetic interface design is how to overcome it. Therefore, we performed experiments with 3D bifurcating guidance scaffolds implanted in the sciatic nerve of rats to test if this new channel architecture could trigger separation pattern of ingrowth also in vivo. Our results showed that this new method enabled the re-growth of neurites into channels with gradually diminished width (80, 40 and 20 µm) and facilitated the separation of the axonal bundles with 91% success. It seems that the 3D bifurcating scaffold might contribute towards conveying detailed neural control and sensory feedback to users of prosthetic devices, and thus could improve the quality of their daily life.

An Empirical Study on Operator Interface Design for Handheld Devices to Control Micro Aerial Vehicles

DTIC Science & Technology

2010-10-01

An Empirical Study on Operator Interface Design for Handheld Devices to Control Micro Aerial Vehicles Ming Hou...Report DRDC Toronto TR 2010-075 October 2010 An Empirical Study on Operator Interface Design for Handheld Devices to...drives the need for a small and light controller which will not hinder a soldier carrying it. This requirement brings an issue of designing an

Neural Control of a Tracking Task via Attention-Gated Reinforcement Learning for Brain-Machine Interfaces.

PubMed

Wang, Yiwen; Wang, Fang; Xu, Kai; Zhang, Qiaosheng; Zhang, Shaomin; Zheng, Xiaoxiang

2015-05-01

Reinforcement learning (RL)-based brain machine interfaces (BMIs) enable the user to learn from the environment through interactions to complete the task without desired signals, which is promising for clinical applications. Previous studies exploited Q-learning techniques to discriminate neural states into simple directional actions providing the trial initial timing. However, the movements in BMI applications can be quite complicated, and the action timing explicitly shows the intention when to move. The rich actions and the corresponding neural states form a large state-action space, imposing generalization difficulty on Q-learning. In this paper, we propose to adopt attention-gated reinforcement learning (AGREL) as a new learning scheme for BMIs to adaptively decode high-dimensional neural activities into seven distinct movements (directional moves, holdings and resting) due to the efficient weight-updating. We apply AGREL on neural data recorded from M1 of a monkey to directly predict a seven-action set in a time sequence to reconstruct the trajectory of a center-out task. Compared to Q-learning techniques, AGREL could improve the target acquisition rate to 90.16% in average with faster convergence and more stability to follow neural activity over multiple days, indicating the potential to achieve better online decoding performance for more complicated BMI tasks.

Flexible microelectrode array for interfacing with the surface of neural ganglia

NASA Astrophysics Data System (ADS)

Sperry, Zachariah J.; Na, Kyounghwan; Parizi, Saman S.; Chiel, Hillel J.; Seymour, John; Yoon, Euisik; Bruns, Tim M.

2018-06-01

Objective. The dorsal root ganglia (DRG) are promising nerve structures for sensory neural interfaces because they provide centralized access to primary afferent cell bodies and spinal reflex circuitry. In order to harness this potential, new electrode technologies are needed which take advantage of the unique properties of DRG, specifically the high density of neural cell bodies at the dorsal surface. Here we report initial in vivo results from the development of a flexible non-penetrating polyimide electrode array interfacing with the surface of ganglia. Approach. Multiple layouts of a 64-channel iridium electrode (420 µm2) array were tested, with pitch as small as 25 µm. The buccal ganglia of invertebrate sea slug Aplysia californica were used to develop handling and recording techniques with ganglionic surface electrode arrays (GSEAs). We also demonstrated the GSEA’s capability to record single- and multi-unit activity from feline lumbosacral DRG related to a variety of sensory inputs, including cutaneous brushing, joint flexion, and bladder pressure. Main results. We recorded action potentials from a variety of Aplysia neurons activated by nerve stimulation, and units were observed firing simultaneously on closely spaced electrode sites. We also recorded single- and multi-unit activity associated with sensory inputs from feline DRG. We utilized spatial oversampling of action potentials on closely-spaced electrode sites to estimate the location of neural sources at between 25 µm and 107 µm below the DRG surface. We also used the high spatial sampling to demonstrate a possible spatial sensory map of one feline’s DRG. We obtained activation of sensory fibers with low-amplitude stimulation through individual or groups of GSEA electrode sites. Significance. Overall, the GSEA has been shown to provide a variety of information types from ganglia neurons and to have significant potential as a tool for neural mapping and interfacing.

Optical-to-optical interface device

NASA Technical Reports Server (NTRS)

Jacobson, A. D.; Bleha, W. P.; Miller, L.; Grinberg, J.; Fraas, L.; Margerum, D.

1975-01-01

An investigation was conducted to develop an optical-to-optical interface device capable of performing real-time incoherent-to-incoherent optical image conversion. The photoactivated liquid crystal light valve developed earlier represented a prototype liquid crystal light valve device capable of performing these functions. A device was developed which had high performance and extended lifetime.

47 CFR 15.115 - TV interface devices, including cable system terminal devices.

Code of Federal Regulations, 2010 CFR

2010-10-01

... output terminal(s) of the device terminated by a resistance equal to the rated output impedance. The... ohms) matching the rated output impedance of the TV interface device, shall not exceed the following... during maximum amplitude peaks across a resistance (R in ohms) matching the rated output impedance of the...

47 CFR 15.115 - TV interface devices, including cable system terminal devices.

Code of Federal Regulations, 2011 CFR

2011-10-01

... output terminal(s) of the device terminated by a resistance equal to the rated output impedance. The... ohms) matching the rated output impedance of the TV interface device, shall not exceed the following... during maximum amplitude peaks across a resistance (R in ohms) matching the rated output impedance of the...

The Integration of Bacteriorhodopsin Proteins with Semiconductor Heterostructure Devices

NASA Astrophysics Data System (ADS)

Xu, Jian

2008-03-01

Bioelectronics has emerged as one of the most rapidly developing fields among the active frontiers of interdisciplinary research. A major thrust in this field is aimed at the coupling of the technologically-unmatched performance of biological systems, such as neural and sensing functions, with the well developed technology of microelectronics and optoelectronics. To this end we have studied the integration of a suitably engineered protein, bacteriorhodopsin (BR), with semiconductor optoelectronic devices and circuits. Successful integration will potentially lead to ultrasensitive sensors with polarization selectivity and built-in preprocessing capabilities that will be useful for high speed tracking, motion and edge detection, biological detection, and artificial vision systems. In this presentation we will summarize our progresses in this area, which include fundamental studies on the transient dynamics of photo-induced charge shift in BR and the coupling mechanism at protein-semiconductor interface for effective immobilizing and selectively integrating light sensitive proteins with microelectronic devices and circuits, and the device engineering of BR-transistor-integrated optical sensors as well as their applications in phototransceiver circuits. Work done in collaboration with Pallab Bhattacharya, Jonghyun Shin, Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI; Robert R. Birge, Department of Chemistry, University of Connecticut, Storrs, CT 06269; and György V'ar'o, Institute of Biophysics, Biological Research Center of the Hungarian Academy of Science, H-6701 Szeged, Hungary.

The effect of visualizing the flow of multimedia content among and inside devices.

PubMed

Lee, Dong-Seok

2009-05-01

This study introduces a user interface, referred to as the flow interface, which provides a graphical representation of the movement of content among and inside audio/video devices. The proposed interface provides a different frame of reference with content-oriented visualization of the generation, manipulation, storage, and display of content as well as input and output. The flow interface was applied to a VCR/DVD recorder combo, one of the most complicated consumer products. A between-group experiment was performed to determine whether the flow interface helps users to perform various tasks and to examine the learning effect of the flow interface, particularly in regard to hooking up and recording tasks. The results showed that participants with access to the flow interface performed better in terms of success rate and elapsed time. In addition, the participants indicated that they could easily understand the flow interface. The potential of the flow interface for application to other audio video devices, and design issues requiring further consideration, are discussed.

Restoring motor control and sensory feedback in people with upper extremity amputations using arrays of 96 microelectrodes implanted in the median and ulnar nerves.

PubMed

Davis, T S; Wark, H A C; Hutchinson, D T; Warren, D J; O'Neill, K; Scheinblum, T; Clark, G A; Normann, R A; Greger, B

2016-06-01

An important goal of neuroprosthetic research is to establish bidirectional communication between the user and new prosthetic limbs that are capable of controlling >20 different movements. One strategy for achieving this goal is to interface the prosthetic limb directly with efferent and afferent fibres in the peripheral nervous system using an array of intrafascicular microelectrodes. This approach would provide access to a large number of independent neural pathways for controlling high degree-of-freedom prosthetic limbs, as well as evoking multiple-complex sensory percepts. Utah Slanted Electrode Arrays (USEAs, 96 recording/stimulating electrodes) were implanted for 30 days into the median (Subject 1-M, 31 years post-amputation) or ulnar (Subject 2-U, 1.5 years post-amputation) nerves of two amputees. Neural activity was recorded during intended movements of the subject's phantom fingers and a linear Kalman filter was used to decode the neural data. Microelectrode stimulation of varying amplitudes and frequencies was delivered via single or multiple electrodes to investigate the number, size and quality of sensory percepts that could be evoked. Device performance over time was assessed by measuring: electrode impedances, signal-to-noise ratios (SNRs), stimulation thresholds, number and stability of evoked percepts. The subjects were able to proportionally, control individual fingers of a virtual robotic hand, with 13 different movements decoded offline (r = 0.48) and two movements decoded online. Electrical stimulation across one USEA evoked >80 sensory percepts. Varying the stimulation parameters modulated percept quality. Devices remained intrafascicularly implanted for the duration of the study with no significant changes in the SNRs or percept thresholds. This study demonstrated that an array of 96 microelectrodes can be implanted into the human peripheral nervous system for up to 1 month durations. Such an array could provide intuitive control of a virtual prosthetic hand with broad sensory feedback.

Restoring motor control and sensory feedback in people with upper extremity amputations using arrays of 96 microelectrodes implanted in the median and ulnar nerves

NASA Astrophysics Data System (ADS)

Davis, T. S.; Wark, H. A. C.; Hutchinson, D. T.; Warren, D. J.; O'Neill, K.; Scheinblum, T.; Clark, G. A.; Normann, R. A.; Greger, B.

2016-06-01

Objective. An important goal of neuroprosthetic research is to establish bidirectional communication between the user and new prosthetic limbs that are capable of controlling >20 different movements. One strategy for achieving this goal is to interface the prosthetic limb directly with efferent and afferent fibres in the peripheral nervous system using an array of intrafascicular microelectrodes. This approach would provide access to a large number of independent neural pathways for controlling high degree-of-freedom prosthetic limbs, as well as evoking multiple-complex sensory percepts. Approach. Utah Slanted Electrode Arrays (USEAs, 96 recording/stimulating electrodes) were implanted for 30 days into the median (Subject 1-M, 31 years post-amputation) or ulnar (Subject 2-U, 1.5 years post-amputation) nerves of two amputees. Neural activity was recorded during intended movements of the subject’s phantom fingers and a linear Kalman filter was used to decode the neural data. Microelectrode stimulation of varying amplitudes and frequencies was delivered via single or multiple electrodes to investigate the number, size and quality of sensory percepts that could be evoked. Device performance over time was assessed by measuring: electrode impedances, signal-to-noise ratios (SNRs), stimulation thresholds, number and stability of evoked percepts. Main results. The subjects were able to proportionally, control individual fingers of a virtual robotic hand, with 13 different movements decoded offline (r = 0.48) and two movements decoded online. Electrical stimulation across one USEA evoked >80 sensory percepts. Varying the stimulation parameters modulated percept quality. Devices remained intrafascicularly implanted for the duration of the study with no significant changes in the SNRs or percept thresholds. Significance. This study demonstrated that an array of 96 microelectrodes can be implanted into the human peripheral nervous system for up to 1 month durations. Such an array could provide intuitive control of a virtual prosthetic hand with broad sensory feedback.

Eye-gaze and intent: Application in 3D interface control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schryver, J.C.; Goldberg, J.H.

1993-06-01

Computer interface control is typically accomplished with an input ``device`` such as keyboard, mouse, trackball, etc. An input device translates a users input actions, such as mouse clicks and key presses, into appropriate computer commands. To control the interface, the user must first convert intent into the syntax of the input device. A more natural means of computer control is possible when the computer can directly infer user intent, without need of intervening input devices. We describe an application of eye-gaze-contingent control of an interactive three-dimensional (3D) user interface. A salient feature of the user interface is natural input, withmore » a heightened impression of controlling the computer directly by the mind. With this interface, input of rotation and translation are intuitive, whereas other abstract features, such as zoom, are more problematic to match with user intent. This paper describes successes with implementation to date, and ongoing efforts to develop a more sophisticated intent inferencing methodology.« less

Eye-gaze and intent: Application in 3D interface control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schryver, J.C.; Goldberg, J.H.

1993-01-01

Computer interface control is typically accomplished with an input device'' such as keyboard, mouse, trackball, etc. An input device translates a users input actions, such as mouse clicks and key presses, into appropriate computer commands. To control the interface, the user must first convert intent into the syntax of the input device. A more natural means of computer control is possible when the computer can directly infer user intent, without need of intervening input devices. We describe an application of eye-gaze-contingent control of an interactive three-dimensional (3D) user interface. A salient feature of the user interface is natural input, withmore » a heightened impression of controlling the computer directly by the mind. With this interface, input of rotation and translation are intuitive, whereas other abstract features, such as zoom, are more problematic to match with user intent. This paper describes successes with implementation to date, and ongoing efforts to develop a more sophisticated intent inferencing methodology.« less

Programmable neural processing on a smartdust for brain-computer interfaces.

PubMed

Yuwen Sun; Shimeng Huang; Oresko, Joseph J; Cheng, Allen C

2010-10-01

Brain-computer interfaces (BCIs) offer tremendous promise for improving the quality of life for disabled individuals. BCIs use spike sorting to identify the source of each neural firing. To date, spike sorting has been performed by either using off-chip analysis, which requires a wired connection penetrating the skull to a bulky external power/processing unit, or via custom application-specific integrated circuits that lack the programmability to perform different algorithms and upgrades. In this research, we propose and test the feasibility of performing on-chip, real-time spike sorting on a programmable smartdust, including feature extraction, classification, compression, and wireless transmission. A detailed power/performance tradeoff analysis using DVFS is presented. Our experimental results show that the execution time and power density meet the requirements to perform real-time spike sorting and wireless transmission on a single neural channel.

Cerebellar neurocontroller project, for aerospace applications, in a civilian neurocomputing initiative in the 'decade of the brain'

NASA Technical Reports Server (NTRS)

Pellionisz, Andras J.; Jorgensen, Charles C.; Werbos, Paul J.

1992-01-01

A key question is how to utilize civilian government agencies along with an industrial consortium to successfully complement the so far primarily defense-oriented neural network research. Civilian artificial neural system projects, such as artificial cerebellar neurocontrollers aimed at duplicating nature's existing neural network solutions for adaptive sensorimotor coordination, are proposed by such a synthesis. The cerebellum provides an intelligent interface between higher possibly symbolic levels of human intelligence and repetitious demands of real world conventional controllers. The generation of such intelligent interfaces could be crucial to the economic feasibility of the human settlement of space and an improvement in telerobotics techniques to permit the cost-effective exploitation of nonterrestrial materials and planetary exploration and monitoring. The authors propose a scientific framework within which such interagency activities could effectively cooperate.

The connector space reduction mechanism

NASA Technical Reports Server (NTRS)

Milam, M. Bruce

1990-01-01

The Connector Space Reduction Mechanism (CSRM) is a simple device that can reduce the number of electromechanical devices on the Payload Interface Adapter/Station Interface Adapter (PIA/SIA) from 4 to 1. The device uses simplicity to attack the heart of the connector mating problem for large interfaces. The CSRM allows blind mate connector mating with minimal alignment required over short distances. This eliminates potential interface binding problems and connector damage. The CSRM is compatible with G and H connectors and Moog Rotary Shutoff fluid couplings. The CSRM can be used also with less forgiving connectors, as was demonstrated in the lab. The CSRM is NASA-Goddard exclusive design with patent applied for. The CSRM is the correct mechanism for the PIA/SIA interface as well as other similar berthing interfaces.

Programmable synaptic devices for electronic neural nets

NASA Technical Reports Server (NTRS)

Moopenn, A.; Thakoor, A. P.

1990-01-01

The architecture, design, and operational characteristics of custom VLSI and thin film synaptic devices are described. The devices include CMOS-based synaptic chips containing 1024 reprogrammable synapses with a 6-bit dynamic range, and nonvolatile, write-once, binary synaptic arrays based on memory switching in hydrogenated amorphous silicon films. Their suitability for embodiment of fully parallel and analog neural hardware is discussed. Specifically, a neural network solution to an assignment problem of combinatorial global optimization, implemented in fully parallel hardware using the synaptic chips, is described. The network's ability to provide optimal and near optimal solutions over a time scale of few neuron time constants has been demonstrated and suggests a speedup improvement of several orders of magnitude over conventional search methods.

Nested Neural Networks

NASA Technical Reports Server (NTRS)

Baram, Yoram

1992-01-01

Report presents analysis of nested neural networks, consisting of interconnected subnetworks. Analysis based on simplified mathematical models more appropriate for artificial electronic neural networks, partly applicable to biological neural networks. Nested structure allows for retrieval of individual subpatterns. Requires fewer wires and connection devices than fully connected networks, and allows for local reconstruction of damaged subnetworks without rewiring entire network.

A Neural Network Aero Design System for Advanced Turbo-Engines

NASA Technical Reports Server (NTRS)

Sanz, Jose M.

1999-01-01

An inverse design method calculates the blade shape that produces a prescribed input pressure distribution. By controlling this input pressure distribution the aerodynamic design objectives can easily be met. Because of the intrinsic relationship between pressure distribution and airfoil physical properties, a neural network can be trained to choose the optimal pressure distribution that would meet a set of physical requirements. The neural network technique works well not only as an interpolating device but also as an extrapolating device to achieve blade designs from a given database. Two validating test cases are discussed.

Tuning the Seebeck effect in C60-based hybrid thermoelectric devices through temperature-dependent surface polarization and thermally-modulated interface dipoles.

PubMed

Liu, Yuchun; Xu, Ling; Zhao, Chen; Shao, Ming; Hu, Bin

2017-06-07

Fullerene (C 60 ) is an important n-type organic semiconductor with high electron mobility and low thermal conductivity. In this work, we report the experimental results on the tunable Seebeck effect of C 60 hybrid thin-film devices by adopting different oxide layers. After inserting n-type high-dielectric constant titanium oxide (TiO x ) and zinc oxide (ZnO) layers, we observed a significantly enhanced n-type Seebeck effect in oxide/C 60 hybrid devices with Seebeck coefficients of -5.8 mV K -1 for TiO x /C 60 and -2.08 mV K -1 for ZnO/C 60 devices at 100 °C, compared with the value of -400 μV K -1 for the pristine C 60 device. However, when a p-type nickel oxide (NiO) layer is inserted, the C 60 hybrid devices show a p-type to n-type Seebeck effect transition when the temperature increases. The remarkable Seebeck effect and change in Seebeck coefficient in different oxide/C 60 hybrid devices can be attributed to two reasons: the temperature-dependent surface polarization difference and thermally-dependent interface dipoles. Firstly, the surface polarization difference due to temperature-dependent electron-phonon coupling can be enhanced by inserting an oxide layer and functions as an additional driving force for the Seebeck effect development. Secondly, thermally-dependent interface dipoles formed at the electrode/oxide interface play an important role in modifying the density of interface states and affecting the charge diffusion in hybrid devices. The surface polarization difference and interface dipoles function in the same direction in hybrid devices with TiO x and ZnO dielectric layers, leading to enhanced n-type Seebeck effect, while the surface polarization difference and interface dipoles generate the opposite impact on electron diffusion in ITO/NiO/C 60 /Al, leading to a p-type to n-type transition in the Seebeck effect. Therefore, inserting different oxide layers could effectively modulate the Seebeck effect of C 60 -based hybrid devices through the surface polarization difference and thermally-dependent interface dipoles, which represents an effective approach to tune the vertical Seebeck effect in organic functional devices.

The receptive field is dead. Long live the receptive field?

PubMed Central

Fairhall, Adrienne

2014-01-01

Advances in experimental techniques, including behavioral paradigms using rich stimuli under closed loop conditions and the interfacing of neural systems with external inputs and outputs, reveal complex dynamics in the neural code and require a revisiting of standard concepts of representation. High-throughput recording and imaging methods along with the ability to observe and control neuronal subpopulations allow increasingly detailed access to the neural circuitry that subserves these representations and the computations they support. How do we harness theory to build biologically grounded models of complex neural function? PMID:24618227

Local intelligent electronic device (IED) rendering templates over limited bandwidth communication link to manage remote IED

DOEpatents

Bradetich, Ryan; Dearien, Jason A; Grussling, Barry Jakob; Remaley, Gavin

2013-11-05

The present disclosure provides systems and methods for remote device management. According to various embodiments, a local intelligent electronic device (IED) may be in communication with a remote IED via a limited bandwidth communication link, such as a serial link. The limited bandwidth communication link may not support traditional remote management interfaces. According to one embodiment, a local IED may present an operator with a management interface for a remote IED by rendering locally stored templates. The local IED may render the locally stored templates using sparse data obtained from the remote IED. According to various embodiments, the management interface may be a web client interface and/or an HTML interface. The bandwidth required to present a remote management interface may be significantly reduced by rendering locally stored templates rather than requesting an entire management interface from the remote IED. According to various embodiments, an IED may comprise an encryption transceiver.

Interfacing 3D micro/nanochannels with a branch-shaped reservoir enhances fluid and mass transport

NASA Astrophysics Data System (ADS)

Kumar, Prasoon; Gandhi, Prasanna S.; Majumder, Mainak

2017-01-01

Three-dimensional (3D) micro/nanofluidic devices can accelerate progress in numerous fields such as tissue engineering, drug delivery, self-healing and cooling devices. However, efficient connections between networks of micro/nanochannels and external fluidic ports are key to successful applications of 3D micro/nanofluidic devices. Therefore, in this work, the extent of the role of reservoir geometry in interfacing with vascular (micro/nanochannel) networks, and in the enabling of connections with external fluidic ports while maintaining the compactness of devices, has been experimentally and theoretically investigated. A statistical modelling suggested that a branch-shaped reservoir demonstrates enhanced interfacing with vascular networks when compared to other regular geometries of reservoirs. Time-lapse dye flow experiments by capillary action through fabricated 3D micro/nanofluidic devices confirmed the connectivity of branch-shaped reservoirs with micro/nanochannel networks in fluidic devices. This demonstrated a ~2.2-fold enhancement of the volumetric flow rate in micro/nanofluidic networks when interfaced to branch-shaped reservoirs over rectangular reservoirs. The enhancement is due to a ~2.8-fold increase in the perimeter of the reservoirs. In addition, the mass transfer experiments exhibited a ~1.7-fold enhancement in solute flux across 3D micro/nanofluidic devices that interfaced with branch-shaped reservoirs when compared to rectangular reservoirs. The fabrication of 3D micro/nanofluidic devices and their efficient interfacing through branch-shaped reservoirs to an external fluidic port can potentially enable their use in complex applications, in which enhanced surface-to-volume interactions are desirable.

Implantable fiber-optic interface for parallel multisite long-term optical dynamic brain interrogation in freely moving mice

PubMed Central

Doronina-Amitonova, L. V.; Fedotov, I. V.; Ivashkina, O. I.; Zots, M. A.; Fedotov, A. B.; Anokhin, K. V.; Zheltikov, A. M.

2013-01-01

Seeing the big picture of functional responses within large neural networks in a freely functioning brain is crucial for understanding the cellular mechanisms behind the higher nervous activity, including the most complex brain functions, such as cognition and memory. As a breakthrough toward meeting this challenge, implantable fiber-optic interfaces integrating advanced optogenetic technologies and cutting-edge fiber-optic solutions have been demonstrated, enabling a long-term optogenetic manipulation of neural circuits in freely moving mice. Here, we show that a specifically designed implantable fiber-optic interface provides a powerful tool for parallel long-term optical interrogation of distinctly separate, functionally different sites in the brain of freely moving mice. This interface allows the same groups of neurons lying deeply in the brain of a freely behaving mouse to be reproducibly accessed and optically interrogated over many weeks, providing a long-term dynamic detection of genome activity in response to a broad variety of pharmacological and physiological stimuli. PMID:24253232

Implantable fiber-optic interface for parallel multisite long-term optical dynamic brain interrogation in freely moving mice

NASA Astrophysics Data System (ADS)

Doronina-Amitonova, L. V.; Fedotov, I. V.; Ivashkina, O. I.; Zots, M. A.; Fedotov, A. B.; Anokhin, K. V.; Zheltikov, A. M.

2013-11-01

Seeing the big picture of functional responses within large neural networks in a freely functioning brain is crucial for understanding the cellular mechanisms behind the higher nervous activity, including the most complex brain functions, such as cognition and memory. As a breakthrough toward meeting this challenge, implantable fiber-optic interfaces integrating advanced optogenetic technologies and cutting-edge fiber-optic solutions have been demonstrated, enabling a long-term optogenetic manipulation of neural circuits in freely moving mice. Here, we show that a specifically designed implantable fiber-optic interface provides a powerful tool for parallel long-term optical interrogation of distinctly separate, functionally different sites in the brain of freely moving mice. This interface allows the same groups of neurons lying deeply in the brain of a freely behaving mouse to be reproducibly accessed and optically interrogated over many weeks, providing a long-term dynamic detection of genome activity in response to a broad variety of pharmacological and physiological stimuli.

Enhanced PEDOT adhesion on solid substrates with electrografted P(EDOT-NH2)

PubMed Central

Ouyang, Liangqi; Wei, Bin; Kuo, Chin-chen; Pathak, Sheevangi; Farrell, Brendan; Martin, David C.

2017-01-01

Conjugated polymers, such as poly(3,4-ethylene dioxythiophene) (PEDOT), have emerged as promising materials for interfacing biomedical devices with tissue because of their relatively soft mechanical properties, versatile organic chemistry, and inherent ability to conduct both ions and electrons. However, their limited adhesion to substrates is a concern for in vivo applications. We report an electrografting method to create covalently bonded PEDOT on solid substrates. An amine-functionalized EDOT derivative (2,3-dihydrothieno[3,4-b][1,4]dioxin-2-yl)methanamine (EDOT-NH2), was synthesized and then electrografted onto conducting substrates including platinum, iridium, and indium tin oxide. The electrografting process was performed under slightly basic conditions with an overpotential of ~2 to 3 V. A nonconjugated, cross-linked, and well-adherent P(EDOT-NH2)–based polymer coating was obtained. We found that the P(EDOT-NH2) polymer coating did not block the charge transport through the interface. Subsequent PEDOT electrochemical deposition onto P(EDOT-NH2)–modified electrodes showed comparable electroactivity to pristine PEDOT coating. With P(EDOT-NH2) as an anchoring layer, PEDOT coating showed greatly enhanced adhesion. The modified coating could withstand extensive ultrasonication (1 hour) without significant cracking or delamination, whereas PEDOT typically delaminated after seconds of sonication. Therefore, this is an effective means to selectively modify microelectrodes with highly adherent and highly conductive polymer coatings as direct neural interfaces. PMID:28275726

Bridging the Divide between Neuroprosthetic Design, Tissue Engineering and Neurobiology

PubMed Central

Leach, Jennie B.; Achyuta, Anil Kumar H.; Murthy, Shashi K.

2009-01-01

Neuroprosthetic devices have made a major impact in the treatment of a variety of disorders such as paralysis and stroke. However, a major impediment in the advancement of this technology is the challenge of maintaining device performance during chronic implantation (months to years) due to complex intrinsic host responses such as gliosis or glial scarring. The objective of this review is to bring together research communities in neurobiology, tissue engineering, and neuroprosthetics to address the major obstacles encountered in the translation of neuroprosthetics technology into long-term clinical use. This article draws connections between specific challenges faced by current neuroprosthetics technology and recent advances in the areas of nerve tissue engineering and neurobiology. Within the context of the device–nervous system interface and central nervous system implants, areas of synergistic opportunity are discussed, including platforms to present cells with multiple cues, controlled delivery of bioactive factors, three-dimensional constructs and in vitro models of gliosis and brain injury, nerve regeneration strategies, and neural stem/progenitor cell biology. Finally, recent insights gained from the fields of developmental neurobiology and cancer biology are discussed as examples of exciting new biological knowledge that may provide fresh inspiration toward novel technologies to address the complexities associated with long-term neuroprosthetic device performance. PMID:20161810

Building Interfaces: Mechanisms, fabrication, and applications at the biotic/abiotic interface for silk fibroin based bioelectronic and biooptical devices

NASA Astrophysics Data System (ADS)

Brenckle, Mark

Recent efforts in bioelectronics and biooptics have led to a shift in the materials and form factors used to make medical devices, including high performance, implantable, and wearable sensors. In this context, biopolymer-based devices must be processed to interface the soft, curvilinear biological world with the rigid, inorganic world of traditional electronics and optics. This poses new material-specific fabrication challenges in designing such devices, which in turn requires further understanding of the fundamental physical behaviors of the materials in question. As a biopolymer, silk fibroin protein has remarkable promise in this space, due to its bioresorbability, mechanical strength, optical clarity, ability to be reshaped on the micro- and nano-scale, and ability to stabilize labile compounds. Application of this material to devices at the biotic/abiotic interface will require the development of fabrication techniques for nano-patterning, lithography, multilayer adhesion, and transfer printing in silk materials. In this work, we address this need through fundamental study of the thermal and diffusional properties of silk protein as it relates to these fabrication strategies. We then leverage these properties to fabricate devices well suited to the biotic/abiotic interface in three areas: shelf-ready sensing, implantable transient electronics, and wearable biosensing. These example devices will illustrate the advantages of silk in this class of bioelectronic and biooptical devices, from fundamentals through application, and contribute to a silk platform for the development of future devices that combine biology with high technology.

Design of a haptic device with grasp and push-pull force feedback for a master-slave surgical robot.

PubMed

Hu, Zhenkai; Yoon, Chae-Hyun; Park, Samuel Byeongjun; Jo, Yung-Ho

2016-07-01

We propose a portable haptic device providing grasp (kinesthetic) and push-pull (cutaneous) sensations for optical-motion-capture master interfaces. Although optical-motion-capture master interfaces for surgical robot systems can overcome the stiffness, friction, and coupling problems of mechanical master interfaces, it is difficult to add haptic feedback to an optical-motion-capture master interface without constraining the free motion of the operator's hands. Therefore, we utilized a Bowden cable-driven mechanism to provide the grasp and push-pull sensation while retaining the free hand motion of the optical-motion capture master interface. To evaluate the haptic device, we construct a 2-DOF force sensing/force feedback system. We compare the sensed force and the reproduced force of the haptic device. Finally, a needle insertion test was done to evaluate the performance of the haptic interface in the master-slave system. The results demonstrate that both the grasp force feedback and the push-pull force feedback provided by the haptic interface closely matched with the sensed forces of the slave robot. We successfully apply our haptic interface in the optical-motion-capture master-slave system. The results of the needle insertion test showed that our haptic feedback can provide more safety than merely visual observation. We develop a suitable haptic device to produce both kinesthetic grasp force feedback and cutaneous push-pull force feedback. Our future research will include further objective performance evaluations of the optical-motion-capture master-slave robot system with our haptic interface in surgical scenarios.

A novel neural prosthesis providing long-term electrocorticography recording and cortical stimulation for epilepsy and brain-computer interface.

PubMed

Romanelli, Pantaleo; Piangerelli, Marco; Ratel, David; Gaude, Christophe; Costecalde, Thomas; Puttilli, Cosimo; Picciafuoco, Mauro; Benabid, Alim; Torres, Napoleon

2018-05-11

OBJECTIVE Wireless technology is a novel tool for the transmission of cortical signals. Wireless electrocorticography (ECoG) aims to improve the safety and diagnostic gain of procedures requiring invasive localization of seizure foci and also to provide long-term recording of brain activity for brain-computer interfaces (BCIs). However, no wireless devices aimed at these clinical applications are currently available. The authors present the application of a fully implantable and externally rechargeable neural prosthesis providing wireless ECoG recording and direct cortical stimulation (DCS). Prolonged wireless ECoG monitoring was tested in nonhuman primates by using a custom-made device (the ECoG implantable wireless 16-electrode [ECOGIW-16E] device) containing a 16-contact subdural grid. This is a preliminary step toward large-scale, long-term wireless ECoG recording in humans. METHODS The authors implanted the ECOGIW-16E device over the left sensorimotor cortex of a nonhuman primate ( Macaca fascicularis), recording ECoG signals over a time span of 6 months. Daily electrode impedances were measured, aiming to maintain the impedance values below a threshold of 100 KΩ. Brain mapping was obtained through wireless cortical stimulation at fixed intervals (1, 3, and 6 months). After 6 months, the device was removed. The authors analyzed cortical tissues by using conventional histological and immunohistological investigation to assess whether there was evidence of damage after the long-term implantation of the grid. RESULTS The implant was well tolerated; no neurological or behavioral consequences were reported in the monkey, which resumed his normal activities within a few hours of the procedure. The signal quality of wireless ECoG remained excellent over the 6-month observation period. Impedance values remained well below the threshold value; the average impedance per contact remains approximately 40 KΩ. Wireless cortical stimulation induced movements of the upper and lower limbs, and elicited fine movements of the digits as well. After the monkey was euthanized, the grid was found to be encapsulated by a newly formed dural sheet. The grid removal was performed easily, and no direct adhesions of the grid to the cortex were found. Conventional histological studies showed no cortical damage in the brain region covered by the grid, except for a single microscopic spot of cortical necrosis (not visible to the naked eye) in a region that had undergone repeated procedures of electrical stimulation. Immunohistological studies of the cortex underlying the grid showed a mild inflammatory process. CONCLUSIONS This preliminary experience in a nonhuman primate shows that a wireless neuroprosthesis, with related long-term ECoG recording (up to 6 months) and multiple DCSs, was tolerated without sequelae. The authors predict that epilepsy surgery could realize great benefit from this novel prosthesis, providing an extended time span for ECoG recording.

Optical processing for semiconductor device fabrication

NASA Technical Reports Server (NTRS)

Sopori, Bhushan L.

1994-01-01

A new technique for semiconductor device processing is described that uses optical energy to produce local heating/melting in the vicinity of a preselected interface of the device. This process, called optical processing, invokes assistance of photons to enhance interface reactions such as diffusion and melting, as compared to the use of thermal heating alone. Optical processing is performed in a 'cold wall' furnace, and requires considerably lower energies than furnace or rapid thermal annealing. This technique can produce some device structures with unique properties that cannot be produced by conventional thermal processing. Some applications of optical processing involving semiconductor-metal interfaces are described.

Effect of two layouts on high technology AAC navigation and content location by people with aphasia.

PubMed

Wallace, Sarah E; Hux, Karen

2014-03-01

Navigating high-technology augmentative and alternative communication (AAC) devices with dynamic displays can be challenging for people with aphasia. The purpose of this study was to determine which of two AAC interfaces two people with aphasia could use most efficiently and accurately. The researchers used a BCB'C' alternating treatment design to provide device-use instruction to two people with severe aphasia regarding two personalised AAC interfaces that had different navigation layouts but identical content. One interface had static buttons for homepage and go-back features, and the other interface had static buttons in a navigation ring layout. Throughout treatment, the researchers monitored participants' mastery patterns regarding navigation efficiency and accuracy when locating target messages. Participants' accuracy and efficiency improved with both interfaces given intervention; however, the navigation ring layout appeared more transparent and better facilitated navigation than the homepage layout. People with aphasia can learn to navigate computerised devices; however, interface layout can substantially affect the efficiency and accuracy with which they locate messages. Given intervention incorporating errorless learning principles, people with chronic aphasia can learn to navigate across multiple device levels to locate target sentences. Both navigation ring and homepage interfaces may be used by people with aphasia. Some people with aphasia may be more consistent and efficient in finding target sentences using the navigation ring interface than the homepage interface. Additionally, the navigation ring interface may be more transparent and easier for people with aphasia to master--that is, they may require fewer intervention sessions to learn to navigate the navigation ring interface. Generalisation of learning may result from use of the navigation ring interface. Specifically, people with aphasia may improve navigation with the homepage interface as a result of instruction on the navigation interface, but not vice versa.

Navigating conjugated polymer actuated neural probes in a brain phantom

NASA Astrophysics Data System (ADS)

Daneshvar, Eugene D.; Kipke, Daryl; Smela, Elisabeth

2012-04-01

Neural probe insertion methods have a direct impact on the longevity of the device in the brain. Initial tissue and vascular damage caused by the probe entering the brain triggers a chronic tissue response that is known to attenuate neural recordings and ultimately encapsulate the probes. Smaller devices have been found to evoke reduced inflammatory response. One way to record from undamaged neural networks may be to position the electrode sites away from the probe. To investigate this approach, we are developing probes with controllably movable electrode projections, which would move outside of the zone that is damaged by the insertion of the larger probe. The objective of this study was to test the capability of conjugated polymer bilayer actuators to actuate neural electrode projections from a probe shank into a transparent brain phantom. Parylene neural probe devices, having five electrode projections with actuating segments and with varying widths (50 - 250 μm) and lengths (200 - 1000 μm) were fabricated. The electroactive polymer polypyrrole (PPy) was used to bend or flatten the projections. The devices were inserted into the brain phantom using an electronic microdrive while simultaneously activating the actuators. Deflections were quantified based on video images. The electrode projections were successfully controlled to either remain flat or to actuate out-of-plane and into the brain phantom during insertion. The projection width had a significant effect on their ability to deflect within the phantom, with thinner probes deflecting but not the wider ones. Thus, small integrated conjugated polymer actuators may enable multiple neuro-experiments and applications not possible before.

Aerospace Ground Equipment for model 4080 sequence programmer. A standard computer terminal is adapted to provide convenient operator to device interface

NASA Technical Reports Server (NTRS)

Nissley, L. E.

1979-01-01

The Aerospace Ground Equipment (AGE) provides an interface between a human operator and a complete spaceborne sequence timing device with a memory storage program. The AGE provides a means for composing, editing, syntax checking, and storing timing device programs. The AGE is implemented with a standard Hewlett-Packard 2649A terminal system and a minimum of special hardware. The terminal's dual tape interface is used to store timing device programs and to read in special AGE operating system software. To compose a new program for the timing device the keyboard is used to fill in a form displayed on the screen.

Improved selectivity from a wavelength addressable device for wireless stimulation of neural tissue

PubMed Central

Seymour, Elif Ç.; Freedman, David S.; Gökkavas, Mutlu; Özbay, Ekmel; Sahin, Mesut; Ünlü, M. Selim

2014-01-01

Electrical neural stimulation with micro electrodes is a promising technique for restoring lost functions in the central nervous system as a result of injury or disease. One of the problems related to current neural stimulators is the tissue response due to the connecting wires and the presence of a rigid electrode inside soft neural tissue. We have developed a novel, optically activated, microscale photovoltaic neurostimulator based on a custom layered compound semiconductor heterostructure that is both wireless and has a comparatively small volume (<0.01 mm3). Optical activation provides a wireless means of energy transfer to the neurostimulator, eliminating wires and the associated complications. This neurostimulator was shown to evoke action potentials and a functional motor response in the rat spinal cord. In this work, we extend our design to include wavelength selectivity and thus allowing independent activation of devices. As a proof of concept, we fabricated two different microscale devices with different spectral responsivities in the near-infrared region. We assessed the improved addressability of individual devices via wavelength selectivity as compared to spatial selectivity alone through on-bench optical measurements of the devices in combination with an in vivo light intensity profile in the rat cortex obtained in a previous study. We show that wavelength selectivity improves the individual addressability of the floating stimulators, thus increasing the number of devices that can be implanted in close proximity to each other. PMID:24600390

Hybrid intracerebral probe with integrated bare LED chips for optogenetic studies.

PubMed

Ayub, Suleman; Gentet, Luc J; Fiáth, Richárd; Schwaerzle, Michael; Borel, Mélodie; David, François; Barthó, Péter; Ulbert, István; Paul, Oliver; Ruther, Patrick

2017-09-01

This article reports on the development, i.e., the design, fabrication, and validation of an implantable optical neural probes designed for in vivo experiments relying on optogenetics. The probes comprise an array of ten bare light-emitting diode (LED) chips emitting at a wavelength of 460 nm and integrated along a flexible polyimide-based substrate stiffened using a micromachined ladder-like silicon structure. The resulting mechanical stiffness of the slender, 250-μm-wide, 65-μm-thick, and 5- and 8-mm-long probe shank facilitates its implantation into neural tissue. The LEDs are encapsulated by a fluropolymer coating protecting the implant against the physiological conditions in the brain. The electrical interface to the external control unit is provided by 10-μm-thick, highly flexible polyimide cables making the probes suitable for both acute and chronic in vivo experiments. Optical and electrical properties of the probes are reported, as well as their in vivo validation in acute optogenetic studies in transgenic mice. The depth-dependent optical stimulation of both excitatory and inhibitory neurons is demonstrated by altering the brain activity in the cortex and the thalamus. Local network responses elicited by 20-ms-long light pulses of different optical power (20 μW and 1 mW), as well as local modulation of single unit neuronal activity to 1-s-long light pulses with low optical intensity (17 μW) are presented. The ability to modulate neural activity makes these devices suitable for a broad variety of optogenetic experiments.

On Design and Implementation of Neural-Machine Interface for Artificial Legs

PubMed Central

Zhang, Xiaorong; Liu, Yuhong; Zhang, Fan; Ren, Jin; Sun, Yan (Lindsay); Yang, Qing

2011-01-01

The quality of life of leg amputees can be improved dramatically by using a cyber physical system (CPS) that controls artificial legs based on neural signals representing amputees’ intended movements. The key to the CPS is the neural-machine interface (NMI) that senses electromyographic (EMG) signals to make control decisions. This paper presents a design and implementation of a novel NMI using an embedded computer system to collect neural signals from a physical system - a leg amputee, provide adequate computational capability to interpret such signals, and make decisions to identify user’s intent for prostheses control in real time. A new deciphering algorithm, composed of an EMG pattern classifier and a post-processing scheme, was developed to identify the user’s intended lower limb movements. To deal with environmental uncertainty, a trust management mechanism was designed to handle unexpected sensor failures and signal disturbances. Integrating the neural deciphering algorithm with the trust management mechanism resulted in a highly accurate and reliable software system for neural control of artificial legs. The software was then embedded in a newly designed hardware platform based on an embedded microcontroller and a graphic processing unit (GPU) to form a complete NMI for real time testing. Real time experiments on a leg amputee subject and an able-bodied subject have been carried out to test the control accuracy of the new NMI. Our extensive experiments have shown promising results on both subjects, paving the way for clinical feasibility of neural controlled artificial legs. PMID:22389637

Organic electronic devices via interface engineering

NASA Astrophysics Data System (ADS)

Xu, Qianfei

This dissertation focuses on interface engineering and its influence on organic electronic devices. A comprehensive review of interface studies in organic electronic devices is presented in Chapter 1. By interface engineering at the cathode contact, an ultra-high efficiency green polymer light emitting diode is demonstrated in Chapter 2. The interface modification turns out to be solution processable by using calcium acetylacetonate, donated by Ca(acac)2. The device structure is Induim Tin Oxide (ITO)/3,4-polyethylenedioxythiophene-polystyrene-sulfonate (PEDOT)/Green polyfluorene/Ca(acac) 2/Al. Based on this structure, we obtained device efficiencies as high as 28 cd/A at 2650 cd/m2, which is about a 3 times improvement over previous devices. The mechanism of this nano-layer has been studied by I-L-V measurements, photovoltaic measurements, XPS/UPS studies, impedance measurements as well as transient EL studies. The interfacial layer plays a crucial role for the efficiency improvement. It is believed to work as a hole blocking layer as well as an electron injection layer. Meanwhile, a systematic study on ITO electrodes is also carried out in Chapter 4. By engineering the interface at ITO electrode, the device lifetime has been improved. In Chapter 5, very bright white emission PLEDs are fabricated based on blue polyfluorene (PF) doped with 1 wt% 6, 8, 15, 17-tetraphyenyl-1.18, 4.5, 9.10, 13.14-tetrabenzoheptacene (TBH). The maximum luminance exceeds 20,000 cd/m2. The maximum luminance efficiency is 3.55 cd/A at 4228 cd/m2 while the maximum power efficiency is 1.6 lm/W at 310 cd/m2. The white color is achieved by an incomplete energy transfer from blue PF to TBH. The devices show super stable CIE coordinates as a function of current density. The interface engineering is also applied to memory devices. In Chapter 6, a novel nonvolatile memory device is fabricated by inserting a buffer layer at the anode contact. Devices with the structure of Cu/Buffer-layer/organic layer/Cu show very attractive electrical bi-stability. The switching mechanism is believed to origin from by the different copper ion concentrations in the organic layer. This opens up a promising way to achieve high-performance organic electronic devices.

Digitally-bypassed transducers: interfacing digital mockups to real-time medical equipment.

PubMed

Sirowy, Scott; Givargis, Tony; Vahid, Frank

2009-01-01

Medical device software is sometimes initially developed by using a PC simulation environment that executes models of both the device and a physiological system, and then later by connecting the actual medical device to a physical mockup of the physiological system. An alternative is to connect the medical device to a digital mockup of the physiological system, such that the device believes it is interacting with a physiological system, but in fact all interaction is entirely digital. Developing medical device software by interfacing with a digital mockup enables development without costly or dangerous physical mockups, and enables execution that is faster or slower than real time. We introduce digitally-bypassed transducers, which involve a small amount of hardware and software additions, and which enable interfacing with digital mockups.

78 FR 77209 - Accessibility of User Interfaces, and Video Programming Guides and Menus

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-20

... user interfaces on digital apparatus and video programming guides and menus on navigation devices for... apparatus and navigation devices used to view video programming. The rules we adopt here will effectuate...--that is, devices and other equipment used by consumers to access multichannel video programming and...

A symbolic/subsymbolic interface protocol for cognitive modeling

PubMed Central

Simen, Patrick; Polk, Thad

2009-01-01

Researchers studying complex cognition have grown increasingly interested in mapping symbolic cognitive architectures onto subsymbolic brain models. Such a mapping seems essential for understanding cognition under all but the most extreme viewpoints (namely, that cognition consists exclusively of digitally implemented rules; or instead, involves no rules whatsoever). Making this mapping reduces to specifying an interface between symbolic and subsymbolic descriptions of brain activity. To that end, we propose parameterization techniques for building cognitive models as programmable, structured, recurrent neural networks. Feedback strength in these models determines whether their components implement classically subsymbolic neural network functions (e.g., pattern recognition), or instead, logical rules and digital memory. These techniques support the implementation of limited production systems. Though inherently sequential and symbolic, these neural production systems can exploit principles of parallel, analog processing from decision-making models in psychology and neuroscience to explain the effects of brain damage on problem solving behavior. PMID:20711520

Long term in vitro stability of fully integrated wireless neural interfaces based on Utah slant electrode array

NASA Astrophysics Data System (ADS)

Sharma, Asha; Rieth, Loren; Tathireddy, Prashant; Harrison, Reid; Solzbacher, Florian

2010-02-01

We herein report in vitro functional stability and recording longevity of a fully integrated wireless neural interface (INI). The INI uses biocompatible Parylene-C as an encapsulation layer, and was immersed in phosphate buffered saline (PBS) for a period of over 150 days. The full functionality (wireless radio-frequency power, command, and signal transmission) and the ability of INI to record artificial action potentials even after 150 days of PBS soaking without any change in signal/noise amplitude constitutes a major milestone in long term stability, and evaluate the encapsulation reliability, functional stability, and potential usefulness for future chronic implants.

Serial Interface through Stream Protocol on EPICS Platform for Distributed Control and Monitoring

NASA Astrophysics Data System (ADS)

Das Gupta, Arnab; Srivastava, Amit K.; Sunil, S.; Khan, Ziauddin

2017-04-01

Remote operation of any equipment or device is implemented in distributed systems in order to control and proper monitoring of process values. For such remote operations, Experimental Physics and Industrial Control System (EPICS) is used as one of the important software tool for control and monitoring of a wide range of scientific parameters. A hardware interface is developed for implementation of EPICS software so that different equipment such as data converters, power supplies, pump controllers etc. could be remotely operated through stream protocol. EPICS base was setup on windows as well as Linux operating system for control and monitoring while EPICS modules such as asyn and stream device were used to interface the equipment with standard RS-232/RS-485 protocol. Stream Device protocol communicates with the serial line with an interface to asyn drivers. Graphical user interface and alarm handling were implemented with Motif Editor and Display Manager (MEDM) and Alarm Handler (ALH) command line channel access utility tools. This paper will describe the developed application which was tested with different equipment and devices serially interfaced to the PCs on a distributed network.

Quantum neural network-based EEG filtering for a brain-computer interface.

PubMed

Gandhi, Vaibhav; Prasad, Girijesh; Coyle, Damien; Behera, Laxmidhar; McGinnity, Thomas Martin

2014-02-01

A novel neural information processing architecture inspired by quantum mechanics and incorporating the well-known Schrodinger wave equation is proposed in this paper. The proposed architecture referred to as recurrent quantum neural network (RQNN) can characterize a nonstationary stochastic signal as time-varying wave packets. A robust unsupervised learning algorithm enables the RQNN to effectively capture the statistical behavior of the input signal and facilitates the estimation of signal embedded in noise with unknown characteristics. The results from a number of benchmark tests show that simple signals such as dc, staircase dc, and sinusoidal signals embedded within high noise can be accurately filtered and particle swarm optimization can be employed to select model parameters. The RQNN filtering procedure is applied in a two-class motor imagery-based brain-computer interface where the objective was to filter electroencephalogram (EEG) signals before feature extraction and classification to increase signal separability. A two-step inner-outer fivefold cross-validation approach is utilized to select the algorithm parameters subject-specifically for nine subjects. It is shown that the subject-specific RQNN EEG filtering significantly improves brain-computer interface performance compared to using only the raw EEG or Savitzky-Golay filtered EEG across multiple sessions.

Feature extraction using extrema sampling of discrete derivatives for spike sorting in implantable upper-limb neural prostheses.

PubMed

Zamani, Majid; Demosthenous, Andreas

2014-07-01

Next generation neural interfaces for upper-limb (and other) prostheses aim to develop implantable interfaces for one or more nerves, each interface having many neural signal channels that work reliably in the stump without harming the nerves. To achieve real-time multi-channel processing it is important to integrate spike sorting on-chip to overcome limitations in transmission bandwidth. This requires computationally efficient algorithms for feature extraction and clustering suitable for low-power hardware implementation. This paper describes a new feature extraction method for real-time spike sorting based on extrema analysis (namely positive peaks and negative peaks) of spike shapes and their discrete derivatives at different frequency bands. Employing simulation across different datasets, the accuracy and computational complexity of the proposed method are assessed and compared with other methods. The average classification accuracy of the proposed method in conjunction with online sorting (O-Sort) is 91.6%, outperforming all the other methods tested with the O-Sort clustering algorithm. The proposed method offers a better tradeoff between classification error and computational complexity, making it a particularly strong choice for on-chip spike sorting.

An ovine model of cerebral catheter venography for implantation of an endovascular neural interface.

PubMed

Oxley, Thomas James; Opie, Nicholas Lachlan; Rind, Gil Simon; Liyanage, Kishan; John, Sam Emmanuel; Ronayne, Stephen; McDonald, Alan James; Dornom, Anthony; Lovell, Timothy John Haynes; Mitchell, Peter John; Bennett, Iwan; Bauquier, Sebastien; Warne, Leon Norris; Steward, Chris; Grayden, David Bruce; Desmond, Patricia; Davis, Stephen M; O'Brien, Terence John; May, Clive N

2018-04-01

OBJECTIVE Neural interface technology may enable the development of novel therapies to treat neurological conditions, including motor prostheses for spinal cord injury. Intracranial neural interfaces currently require a craniotomy to achieve implantation and may result in chronic tissue inflammation. Novel approaches are required that achieve less invasive implantation methods while maintaining high spatial resolution. An endovascular stent electrode array avoids direct brain trauma and is able to record electrocorticography in local cortical tissue from within the venous vasculature. The motor area in sheep runs in a parasagittal plane immediately adjacent to the superior sagittal sinus (SSS). The authors aimed to develop a sheep model of cerebral venography that would enable validation of an endovascular neural interface. METHODS Cerebral catheter venography was performed in 39 consecutive sheep. Contrast-enhanced MRI of the brain was performed on 13 animals. Multiple telescoping coaxial catheter systems were assessed to determine the largest wide-bore delivery catheter that could be delivered into the anterior SSS. Measurements of SSS diameter and distance from the motor area were taken. The location of the motor area was determined in relation to lateral and superior projections of digital subtraction venography images and confirmed on MRI. RESULTS The venous pathway from the common jugular vein (7.4 mm) to the anterior SSS (1.2 mm) was technically challenging to selectively catheterize. The SSS coursed immediately adjacent to the motor cortex (< 1 mm) for a length of 40 mm, or the anterior half of the SSS. Attempted access with 5-Fr and 6-Fr delivery catheters was associated with longer procedure times and higher complication rates. A 4-Fr catheter (internal lumen diameter 1.1 mm) was successful in accessing the SSS in 100% of cases with no associated complications. Complications included procedure-related venous dissection in two major areas: the torcular herophili, and the anterior formation of the SSS. The bifurcation of the cruciate sulcal veins with the SSS was a reliable predictor of the commencement of the motor area. CONCLUSIONS The ovine model for cerebral catheter venography has generalizability to the human cerebral venous system in relation to motor cortex location. This novel model may facilitate the development of the novel field of endovascular neural interfaces that may include preclinical investigations for cortical recording applications such as paralysis and epilepsy, as well as other potential applications in neuromodulation.

The effect of chronic intracortical microstimulation on the electrode-tissue interface.

PubMed

Chen, Kevin H; Dammann, John F; Boback, Jessica L; Tenore, Francesco V; Otto, Kevin J; Gaunt, Robert A; Bensmaia, Sliman J

2014-04-01

Somatosensation is critical for effective object manipulation, but current upper limb prostheses do not provide such feedback to the user. For individuals who require use of prosthetic limbs, this lack of feedback transforms a mundane task into one that requires extreme concentration and effort. Although vibrotactile motors and sensory substitution devices can be used to convey gross sensations, a direct neural interface is required to provide detailed and intuitive sensory feedback. The viability of intracortical microstimulation (ICMS) as a method to deliver feedback depends in part on the long-term reliability of implanted electrodes used to deliver the stimulation. The objective of the present study is to investigate the effects of chronic ICMS on the electrode-tissue interface. We stimulate the primary somatosensory cortex of three Rhesus macaques through chronically implanted electrodes for 4 h per day over a period of six months, with different electrodes subjected to different regimes of stimulation. We measure the impedance and voltage excursion as a function of time and of ICMS parameters. We also test the sensorimotor consequences of chronic ICMS by having animals grasp and manipulate small treats. We show that impedance and voltage excursion both decay with time but stabilize after 10-12 weeks. The magnitude of this decay is dependent on the amplitude of the ICMS and, to a lesser degree, the duration of individual pulse trains. Furthermore, chronic ICMS does not produce any deficits in fine motor control. The results suggest that chronic ICMS has only a minor effect on the electrode-tissue interface and may thus be a viable means to convey sensory feedback in neuroprosthetics.

Adaptive eye-gaze tracking using neural-network-based user profiles to assist people with motor disability.

PubMed

Sesin, Anaelis; Adjouadi, Malek; Cabrerizo, Mercedes; Ayala, Melvin; Barreto, Armando

2008-01-01

This study developed an adaptive real-time human-computer interface (HCI) that serves as an assistive technology tool for people with severe motor disability. The proposed HCI design uses eye gaze as the primary computer input device. Controlling the mouse cursor with raw eye coordinates results in sporadic motion of the pointer because of the saccadic nature of the eye. Even though eye movements are subtle and completely imperceptible under normal circumstances, they considerably affect the accuracy of an eye-gaze-based HCI. The proposed HCI system is novel because it adapts to each specific user's different and potentially changing jitter characteristics through the configuration and training of an artificial neural network (ANN) that is structured to minimize the mouse jitter. This task is based on feeding the ANN a user's initially recorded eye-gaze behavior through a short training session. The ANN finds the relationship between the gaze coordinates and the mouse cursor position based on the multilayer perceptron model. An embedded graphical interface is used during the training session to generate user profiles that make up these unique ANN configurations. The results with 12 subjects in test 1, which involved following a moving target, showed an average jitter reduction of 35%; the results with 9 subjects in test 2, which involved following the contour of a square object, showed an average jitter reduction of 53%. For both results, the outcomes led to trajectories that were significantly smoother and apt at reaching fixed or moving targets with relative ease and within a 5% error margin or deviation from desired trajectories. The positive effects of such jitter reduction are presented graphically for visual appreciation.

Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface.

PubMed

Lajoie, Guillaume; Krouchev, Nedialko I; Kalaska, John F; Fairhall, Adrienne L; Fetz, Eberhard E

2017-02-01

Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). When spikes from a neuron recorded at one MC site trigger stimuli at a second target site after a fixed delay, the connections between sites eventually strengthen. It was also found that effective spike-stimulus delays are consistent with experimentally derived spike-timing-dependent plasticity (STDP) rules, suggesting that STDP is key to drive these changes. However, the impact of STDP at the level of circuits, and the mechanisms governing its modification with neural implants remain poorly understood. The present work describes a recurrent neural network model with probabilistic spiking mechanisms and plastic synapses capable of capturing both neural and synaptic activity statistics relevant to BBCI conditioning protocols. Our model successfully reproduces key experimental results, both established and new, and offers mechanistic insights into spike-triggered conditioning. Using analytical calculations and numerical simulations, we derive optimal operational regimes for BBCIs, and formulate predictions concerning the efficacy of spike-triggered conditioning in different regimes of cortical activity.

Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface

PubMed Central

Lajoie, Guillaume; Kalaska, John F.; Fairhall, Adrienne L.; Fetz, Eberhard E.

2017-01-01

Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). When spikes from a neuron recorded at one MC site trigger stimuli at a second target site after a fixed delay, the connections between sites eventually strengthen. It was also found that effective spike-stimulus delays are consistent with experimentally derived spike-timing-dependent plasticity (STDP) rules, suggesting that STDP is key to drive these changes. However, the impact of STDP at the level of circuits, and the mechanisms governing its modification with neural implants remain poorly understood. The present work describes a recurrent neural network model with probabilistic spiking mechanisms and plastic synapses capable of capturing both neural and synaptic activity statistics relevant to BBCI conditioning protocols. Our model successfully reproduces key experimental results, both established and new, and offers mechanistic insights into spike-triggered conditioning. Using analytical calculations and numerical simulations, we derive optimal operational regimes for BBCIs, and formulate predictions concerning the efficacy of spike-triggered conditioning in different regimes of cortical activity. PMID:28151957

Brain control and information transfer.

PubMed

Tehovnik, Edward J; Chen, Lewis L

2015-12-01

In this review, we examine the importance of having a body as essential for the brain to transfer information about the outside world to generate appropriate motor responses. We discuss the context-dependent conditioning of the motor control neural circuits and its dependence on the completion of feedback loops, which is in close agreement with the insights of Hebb and colleagues, who have stressed that for learning to occur the body must be intact and able to interact with the outside world. Finally, we apply information theory to data from published studies to evaluate the robustness of the neuronal signals obtained by bypassing the body (as used for brain-machine interfaces) versus via the body to move in the world. We show that recording from a group of neurons that bypasses the body exhibits a vastly degraded level of transfer of information as compared to that of an entire brain using the body to engage in the normal execution of behaviour. We conclude that body sensations provide more than just feedback for movements; they sustain the necessary transfer of information as animals explore their environment, thereby creating associations through learning. This work has implications for the development of brain-machine interfaces used to move external devices.

Dissolution of Monocrystalline Silicon Nanomembranes and Their Use as Encapsulation Layers and Electrical Interfaces in Water-Soluble Electronics.

PubMed

Lee, Yoon Kyeung; Yu, Ki Jun; Song, Enming; Barati Farimani, Amir; Vitale, Flavia; Xie, Zhaoqian; Yoon, Younghee; Kim, Yerim; Richardson, Andrew; Luan, Haiwen; Wu, Yixin; Xie, Xu; Lucas, Timothy H; Crawford, Kaitlyn; Mei, Yongfeng; Feng, Xue; Huang, Yonggang; Litt, Brian; Aluru, Narayana R; Yin, Lan; Rogers, John A

2017-12-26

The chemistry that governs the dissolution of device-grade, monocrystalline silicon nanomembranes into benign end products by hydrolysis serves as the foundation for fully eco/biodegradable classes of high-performance electronics. This paper examines these processes in aqueous solutions with chemical compositions relevant to groundwater and biofluids. The results show that the presence of Si(OH) 4 and proteins in these solutions can slow the rates of dissolution and that ion-specific effects associated with Ca 2+ can significantly increase these rates. This information allows for effective use of silicon nanomembranes not only as active layers in eco/biodegradable electronics but also as water barriers capable of providing perfect encapsulation until their disappearance by dissolution. The time scales for this encapsulation can be controlled by introduction of dopants into the Si and by addition of oxide layers on the exposed surfaces.The former possibility also allows the doped silicon to serve as an electrical interface for measuring biopotentials, as demonstrated in fully bioresorbable platforms for in vivo neural recordings. This collection of findings is important for further engineering development of water-soluble classes of silicon electronics.

An optical brain computer interface for environmental control.

PubMed

Ayaz, Hasan; Shewokis, Patricia A; Bunce, Scott; Onaral, Banu

2011-01-01

A brain computer interface (BCI) is a system that translates neurophysiological signals detected from the brain to supply input to a computer or to control a device. Volitional control of neural activity and its real-time detection through neuroimaging modalities are key constituents of BCI systems. The purpose of this study was to develop and test a new BCI design that utilizes intention-related cognitive activity within the dorsolateral prefrontal cortex using functional near infrared (fNIR) spectroscopy. fNIR is a noninvasive, safe, portable and affordable optical technique with which to monitor hemodynamic changes, in the brain's cerebral cortex. Because of its portability and ease of use, fNIR is amenable to deployment in ecologically valid natural working environments. We integrated a control paradigm in a computerized 3D virtual environment to augment interactivity. Ten healthy participants volunteered for a two day study in which they navigated a virtual environment with keyboard inputs, but were required to use the fNIR-BCI for interaction with virtual objects. Results showed that participants consistently utilized the fNIR-BCI with an overall success rate of 84% and volitionally increased their cerebral oxygenation level to trigger actions within the virtual environment.

Analogue spin-orbit torque device for artificial-neural-network-based associative memory operation

NASA Astrophysics Data System (ADS)

Borders, William A.; Akima, Hisanao; Fukami, Shunsuke; Moriya, Satoshi; Kurihara, Shouta; Horio, Yoshihiko; Sato, Shigeo; Ohno, Hideo

2017-01-01

We demonstrate associative memory operations reminiscent of the brain using nonvolatile spintronics devices. Antiferromagnet-ferromagnet bilayer-based Hall devices, which show analogue-like spin-orbit torque switching under zero magnetic fields and behave as artificial synapses, are used. An artificial neural network is used to associate memorized patterns from their noisy versions. We develop a network consisting of a field-programmable gate array and 36 spin-orbit torque devices. An effect of learning on associative memory operations is successfully confirmed for several 3 × 3-block patterns. A discussion on the present approach for realizing spintronics-based artificial intelligence is given.

Neuromorphic device architectures with global connectivity through electrolyte gating

NASA Astrophysics Data System (ADS)

Gkoupidenis, Paschalis; Koutsouras, Dimitrios A.; Malliaras, George G.

2017-05-01

Information processing in the brain takes place in a network of neurons that are connected with each other by an immense number of synapses. At the same time, neurons are immersed in a common electrochemical environment, and global parameters such as concentrations of various hormones regulate the overall network function. This computational paradigm of global regulation, also known as homeoplasticity, has important implications in the overall behaviour of large neural ensembles and is barely addressed in neuromorphic device architectures. Here, we demonstrate the global control of an array of organic devices based on poly(3,4ethylenedioxythiophene):poly(styrene sulf) that are immersed in an electrolyte, a behaviour that resembles homeoplasticity phenomena of the neural environment. We use this effect to produce behaviour that is reminiscent of the coupling between local activity and global oscillations in the biological neural networks. We further show that the electrolyte establishes complex connections between individual devices, and leverage these connections to implement coincidence detection. These results demonstrate that electrolyte gating offers significant advantages for the realization of networks of neuromorphic devices of higher complexity and with minimal hardwired connectivity.

Programmable Analog Memory Resistors For Electronic Neural Networks

NASA Technical Reports Server (NTRS)

Ramesham, Rajeshuni; Thakoor, Sarita; Daud, Taher; Thakoor, Anilkumar P.

1990-01-01

Electrical resistance of new solid-state device altered repeatedly by suitable control signals, yet remains at steady value when control signal removed. Resistance set at low value ("on" state), high value ("off" state), or at any convenient intermediate value and left there until new value desired. Circuits of this type particularly useful in nonvolatile, associative electronic memories based on models of neural networks. Such programmable analog memory resistors ideally suited as synaptic interconnects in "self-learning" neural nets. Operation of device depends on electrochromic property of WO3, which when pure is insulator. Potential uses include nonvolatile, erasable, electronically programmable read-only memories.

Voltage-induced Interface Reconstruction and Electrical Instability of the Ferromagnet-Semiconductor Device.

PubMed

Chang, Shu-Jui; Chang, Po-Chun; Lin, Wen-Chin; Lo, Shao-Hua; Chang, Liang-Chun; Lee, Shang-Fan; Tseng, Yuan-Chieh

2017-03-23

Using x-ray magnetic spectroscopy with in-situ electrical characterizations, we investigated the effects of external voltage on the spin-electronic and transport properties at the interface of a Fe/ZnO device. Layer-, element-, and spin-resolved information of the device was obtained by cross-tuning of the x-ray mode and photon energy, when voltage was applied. At the early stage of the operation, the device exhibited a low-resistance state featuring robust Fe-O bonds. However, the Fe-O bonds were broken with increasing voltage. Breaking of the Fe-O bonds caused the formation of oxygen vacancies and resulted in a high-resistance state. Such interface reconstruction was coupled to a charge-transfer effect via Fe-O hybridization, which suppressed/enhanced the magnetization/coercivity of Fe electronically. Nevertheless, the interface became stabilized with the metallic phase if the device was continuously polarized. During this stage, the spin-polarization of Fe was enhanced whereas the coercivity was lowered by voltage, but changes of both characteristics were reversible. This stage is desirable for spintronic device applications, owing to a different voltage-induced electronic transition compared to the first stage. The study enabled a straightforward detection of the spin-electronic state at the ferromagnet-semiconductor interface in relation to the transport and reversal properties during operation process of the device.

“Optical communication with brain cells by means of an implanted duplex micro-device with optogenetics and Ca2+ fluoroimaging”

PubMed Central

Kobayashi, Takuma; Haruta, Makito; Sasagawa, Kiyotaka; Matsumata, Miho; Eizumi, Kawori; Kitsumoto, Chikara; Motoyama, Mayumi; Maezawa, Yasuyo; Ohta, Yasumi; Noda, Toshihiko; Tokuda, Takashi; Ishikawa, Yasuyuki; Ohta, Jun

2016-01-01

To better understand the brain function based on neural activity, a minimally invasive analysis technology in a freely moving animal is necessary. Such technology would provide new knowledge in neuroscience and contribute to regenerative medical techniques and prosthetics care. An application that combines optogenetics for voluntarily stimulating nerves, imaging to visualize neural activity, and a wearable micro-instrument for implantation into the brain could meet the abovementioned demand. To this end, a micro-device that can be applied to the brain less invasively and a system for controlling the device has been newly developed in this study. Since the novel implantable device has dual LEDs and a CMOS image sensor, photostimulation and fluorescence imaging can be performed simultaneously. The device enables bidirectional communication with the brain by means of light. In the present study, the device was evaluated in an in vitro experiment using a new on-chip 3D neuroculture with an extracellular matrix gel and an in vivo experiment involving regenerative medical transplantation and gene delivery to the brain by using both photosensitive channel and fluorescent Ca2+ indicator. The device succeeded in activating cells locally by selective photostimulation, and the physiological Ca2+ dynamics of neural cells were visualized simultaneously by fluorescence imaging. PMID:26878910

“Optical communication with brain cells by means of an implanted duplex micro-device with optogenetics and Ca2+ fluoroimaging”

NASA Astrophysics Data System (ADS)

Kobayashi, Takuma; Haruta, Makito; Sasagawa, Kiyotaka; Matsumata, Miho; Eizumi, Kawori; Kitsumoto, Chikara; Motoyama, Mayumi; Maezawa, Yasuyo; Ohta, Yasumi; Noda, Toshihiko; Tokuda, Takashi; Ishikawa, Yasuyuki; Ohta, Jun

2016-02-01

To better understand the brain function based on neural activity, a minimally invasive analysis technology in a freely moving animal is necessary. Such technology would provide new knowledge in neuroscience and contribute to regenerative medical techniques and prosthetics care. An application that combines optogenetics for voluntarily stimulating nerves, imaging to visualize neural activity, and a wearable micro-instrument for implantation into the brain could meet the abovementioned demand. To this end, a micro-device that can be applied to the brain less invasively and a system for controlling the device has been newly developed in this study. Since the novel implantable device has dual LEDs and a CMOS image sensor, photostimulation and fluorescence imaging can be performed simultaneously. The device enables bidirectional communication with the brain by means of light. In the present study, the device was evaluated in an in vitro experiment using a new on-chip 3D neuroculture with an extracellular matrix gel and an in vivo experiment involving regenerative medical transplantation and gene delivery to the brain by using both photosensitive channel and fluorescent Ca2+ indicator. The device succeeded in activating cells locally by selective photostimulation, and the physiological Ca2+ dynamics of neural cells were visualized simultaneously by fluorescence imaging.

T-LECS: The Control Software System for MOIRCS

NASA Astrophysics Data System (ADS)

Yoshikawa, T.; Omata, K.; Konishi, M.; Ichikawa, T.; Suzuki, R.; Tokoku, C.; Katsuno, Y.; Nishimura, T.

2006-07-01

MOIRCS (Multi-Object Infrared Camera and Spectrograph) is a new instrument for the Subaru Telescope. We present the system design of the control software system for MOIRCS, named T-LECS (Tohoku University - Layered Electronic Control System). T-LECS is a PC-Linux based network distributed system. Two PCs equipped with the focal plane array system operate two HAWAII2 detectors, respectively, and another PC is used for user interfaces and a database server. Moreover, these PCs control various devices for observations distributed on a TCP/IP network. T-LECS has three interfaces; interfaces to the devices and two user interfaces. One of the user interfaces is to the integrated observation control system (Subaru Observation Software System) for observers, and another one provides the system developers the direct access to the devices of MOIRCS. In order to help the communication between these interfaces, we employ an SQL database system.

Construction of a Piezoresistive Neural Sensor Array

NASA Technical Reports Server (NTRS)

Carlson, W. B.; Schulze, W. A.; Pilgrim, P. M.

1996-01-01

The construction of a piezoresistive - piezoelectric sensor (or actuator) array is proposed using 'neural' connectivity for signal recognition and possible actuation functions. A closer integration of the sensor and decision functions is necessary in order to achieve intrinsic identification within the sensor. A neural sensor is the next logical step in development of truly 'intelligent' arrays. This proposal will integrate 1-3 polymer piezoresistors and MLC electroceramic devices for applications involving acoustic identification. The 'intelligent' piezoresistor -piezoelectric system incorporates printed resistors, composite resistors, and a feedback for the resetting of resistances. A model of a design is proposed in order to simulate electromechanical resistor interactions. The goal of optimizing a sensor geometry for improving device reliability, training, & signal identification capabilities is the goal of this work. At present, studies predict performance of a 'smart' device with a significant control of 'effective' compliance over a narrow pressure range due to a piezoresistor percolation threshold. An interesting possibility may be to use an array of control elements to shift the threshold function in order to change the level of resistance in a neural sensor array for identification, or, actuation applications. The proposed design employs elements of: (1) conductor loaded polymers for a 'fast' RC time constant response; and (2) multilayer ceramics for actuation or sensing and shifting of resistance in the polymer. Other material possibilities also exist using magnetoresistive layered systems for shifting the resistance. It is proposed to use a neural net configuration to test and to help study the possible changes required in the materials design of these devices. Numerical design models utilize electromechanical elements, in conjunction with structural elements in order to simulate piezoresistively controlled actuators and changes in resistance of sensors. The construction of these devices may show significant improvement in ability to interrogate signals and in the control of effective compliance. This work focuses on the development a variety of series/parallel interconnected piezoresistive control elements for the neural sensing function.

Apparatus for fixing latency

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hall, David R; Bartholomew, David B; Moon, Justin

2009-09-08

An apparatus for fixing computational latency within a deterministic region on a network comprises a network interface modem, a high priority module and at least one deterministic peripheral device. The network interface modem is in communication with the network. The high priority module is in communication with the network interface modem. The at least one deterministic peripheral device is connected to the high priority module. The high priority module comprises a packet assembler/disassembler, and hardware for performing at least one operation. Also disclosed is an apparatus for executing at least one instruction on a downhole device within a deterministic region,more » the apparatus comprising a control device, a downhole network, and a downhole device. The control device is near the surface of a downhole tool string. The downhole network is integrated into the tool string. The downhole device is in communication with the downhole network.« less

Probe-pin device for optical neurotransmitter sensing in the brain

NASA Astrophysics Data System (ADS)

Kim, Min Hyuck; Song, Kyo D.; Yoon, Hargsoon; Park, Yeonjoon; Choi, Sang H.; Lee, Dae-Sung; Shin, Kyu-Sik; Hwang, Hak-In; Lee, Uhn

2015-04-01

Development of an optical neurotransmitter sensing device using nano-plasmonic probes and a micro-spectrometer for real time monitoring of neural signals in the brain is underway. Clinical application of this device technology is to provide autonomous closed-loop feedback control to a deep brain stimulation (DBS) system and enhance the accuracy and efficacy of DBS treatment. By far, we have developed an implantable probe-pin device based on localized field enhancement of surface plasmonic resonance on a nanostructured sensing domain which can amplify neurochemical signals from evoked neural activity in the brain. In this paper, we will introduce the details of design and sensing performance of a proto-typed microspectrometer and nanostructured probing devices for real time measurement of neurotransmitter concentrations.

On the theory of Carriers's Electrostatic Interaction near an Interface

NASA Astrophysics Data System (ADS)

Waters, Michael; Hashemi, Hossein; Kieffer, John

2015-03-01

Heterojunction interfaces are common in non-traditional photovoltaic device designs, such as those based small molecules, polymers, and perovskites. We have examined a number of the effects of the heterojunction interface region on carrier/exciton energetics using a mixture of both semi-classical and quantum electrostatic methods, ab initio methods, and statistical mechanics. Our theoretical analysis has yielded several useful relationships and numerical recipes that should be considered in device design regardless of the particular materials system. As a demonstration, we highlight these formalisms as applied to carriers and polaron pairs near a C60/subphthalocyanine interface. On the regularly ordered areas of the heterojunction, the effect of the interface is a significant set of corrections to the carrier energies, which in turn directly affects device performance.

Controlling band alignments by artificial interface dipoles at perovskite heterointerfaces

DOE PAGES

Yajima, Takeaki; Hikita, Yasuyuki; Minohara, Makoto; ...

2015-04-07

The concept ‘the interface is the device' is embodied in a wide variety of interfacial electronic phenomena and associated applications in oxide materials, ranging from catalysts and clean energy systems to emerging multifunctional devices. Many device properties are defined by the band alignment, which is often influenced by interface dipoles. On the other hand, the ability to purposefully create and control interface dipoles is a relatively unexplored degree of freedom for perovskite oxides, which should be particularly effective for such ionic materials. Here we demonstrate tuning the band alignment in perovskite metal-semiconductor heterojunctions over a broad range of 1.7 eV.more » This is achieved by the insertion of positive or negative charges at the interface, and the resultant dipole formed by the induced screening charge. This approach can be broadly used in applications where decoupling the band alignment from the constituent work functions and electron affinities can enhance device functionality.« less

Enabling Low-Power, Multi-Modal Neural Interfaces Through a Common, Low-Bandwidth Feature Space.

PubMed

Irwin, Zachary T; Thompson, David E; Schroeder, Karen E; Tat, Derek M; Hassani, Ali; Bullard, Autumn J; Woo, Shoshana L; Urbanchek, Melanie G; Sachs, Adam J; Cederna, Paul S; Stacey, William C; Patil, Parag G; Chestek, Cynthia A

2016-05-01

Brain-Machine Interfaces (BMIs) have shown great potential for generating prosthetic control signals. Translating BMIs into the clinic requires fully implantable, wireless systems; however, current solutions have high power requirements which limit their usability. Lowering this power consumption typically limits the system to a single neural modality, or signal type, and thus to a relatively small clinical market. Here, we address both of these issues by investigating the use of signal power in a single narrow frequency band as a decoding feature for extracting information from electrocorticographic (ECoG), electromyographic (EMG), and intracortical neural data. We have designed and tested the Multi-modal Implantable Neural Interface (MINI), a wireless recording system which extracts and transmits signal power in a single, configurable frequency band. In prerecorded datasets, we used the MINI to explore low frequency signal features and any resulting tradeoff between power savings and decoding performance losses. When processing intracortical data, the MINI achieved a power consumption 89.7% less than a more typical system designed to extract action potential waveforms. When processing ECoG and EMG data, the MINI achieved similar power reductions of 62.7% and 78.8%. At the same time, using the single signal feature extracted by the MINI, we were able to decode all three modalities with less than a 9% drop in accuracy relative to using high-bandwidth, modality-specific signal features. We believe this system architecture can be used to produce a viable, cost-effective, clinical BMI.

Efficient Cancer Detection Using Multiple Neural Networks.

PubMed

Shell, John; Gregory, William D

2017-01-01

The inspection of live excised tissue specimens to ascertain malignancy is a challenging task in dermatopathology and generally in histopathology. We introduce a portable desktop prototype device that provides highly accurate neural network classification of malignant and benign tissue. The handheld device collects 47 impedance data samples from 1 Hz to 32 MHz via tetrapolar blackened platinum electrodes. The data analysis was implemented with six different backpropagation neural networks (BNN). A data set consisting of 180 malignant and 180 benign breast tissue data files in an approved IRB study at the Aurora Medical Center, Milwaukee, WI, USA, were utilized as a neural network input. The BNN structure consisted of a multi-tiered consensus approach autonomously selecting four of six neural networks to determine a malignant or benign classification. The BNN analysis was then compared with the histology results with consistent sensitivity of 100% and a specificity of 100%. This implementation successfully relied solely on statistical variation between the benign and malignant impedance data and intricate neural network configuration. This device and BNN implementation provides a novel approach that could be a valuable tool to augment current medical practice assessment of the health of breast, squamous, and basal cell carcinoma and other excised tissue without requisite tissue specimen expertise. It has the potential to provide clinical management personnel with a fast non-invasive accurate assessment of biopsied or sectioned excised tissue in various clinical settings.

Efficient Cancer Detection Using Multiple Neural Networks

PubMed Central

Gregory, William D.

2017-01-01

The inspection of live excised tissue specimens to ascertain malignancy is a challenging task in dermatopathology and generally in histopathology. We introduce a portable desktop prototype device that provides highly accurate neural network classification of malignant and benign tissue. The handheld device collects 47 impedance data samples from 1 Hz to 32 MHz via tetrapolar blackened platinum electrodes. The data analysis was implemented with six different backpropagation neural networks (BNN). A data set consisting of 180 malignant and 180 benign breast tissue data files in an approved IRB study at the Aurora Medical Center, Milwaukee, WI, USA, were utilized as a neural network input. The BNN structure consisted of a multi-tiered consensus approach autonomously selecting four of six neural networks to determine a malignant or benign classification. The BNN analysis was then compared with the histology results with consistent sensitivity of 100% and a specificity of 100%. This implementation successfully relied solely on statistical variation between the benign and malignant impedance data and intricate neural network configuration. This device and BNN implementation provides a novel approach that could be a valuable tool to augment current medical practice assessment of the health of breast, squamous, and basal cell carcinoma and other excised tissue without requisite tissue specimen expertise. It has the potential to provide clinical management personnel with a fast non-invasive accurate assessment of biopsied or sectioned excised tissue in various clinical settings. PMID:29282435

Design of a Computer-Controlled, Random-Access Slide Projector Interface. Final Report (April 1974 - November 1974).

ERIC Educational Resources Information Center

Kirby, Paul J.; And Others

The design, development, test, and evaluation of an electronic hardware device interfacing a commercially available slide projector with a plasma panel computer terminal is reported. The interface device allows an instructional computer program to select slides for viewing based upon the lesson student situation parameters of the instructional…

A Communication Device for Interfacing Slide/Audio Tape Programs with the Microcomputer for Computer-Assisted Self-Instruction.

ERIC Educational Resources Information Center

Hostetler, Jerry C.; Englert, Duwayne C.

1987-01-01

Presents description of an interface device which ties in microcomputers and slide/tape presentations for computer assisted instruction. Highlights include the use of this technology in an introductory undergraduate zoology course; a discussion of authoring languages with emphasis on SuperPILOT; and hardware and software design for the interface.…

System Architectural Concepts: Army Battlefield Command and Control Information Utility (CCIU).

DTIC Science & Technology

1982-07-25

produce (device-type), the computers they may interface with (required- host), and the identification number of the devices (device- number). Line- printers ...interface in a network PE ( ZINK Sol. A-5 GLOSSARY Kernel A layer of the PEOS; implements the basic system primitives. LUS Local Name Space Locking A

Interface trap of p-type gate integrated AlGaN/GaN heterostructure field effect transistors

NASA Astrophysics Data System (ADS)

Kim, Kyu Sang

2017-09-01

In this work, the impact of trap states at the p-(Al)GaN/AlGaN interface has been investigated for the normally-off mode p-(Al)GaN/AlGaN/GaN heterostructure field-effect transistors (HFETs) by means of frequency dependent conductance. From the current-voltage (I-V) measurement, it was found that the p-AlGaN gate integrated device has higher drain current and lower gate leakage current compared to the p-GaN gate integrated device. We obtained the interface trap density and the characteristic time constant for the p-type gate integrated HFETs under the forward gate voltage of up to 6 V. As a result, the interface trap density (characteristic time constant) of the p-GaN gate device was lower (longer) than that of the p-AlGaN. Furthermore, it was analyzed that the trap state energy level of the p-GaN gate device was located at the shallow level relative to the p-AlGaN gate device, which accounts for different gate leakage current of each devices.

Evaluating and improving the performance of thin film force sensors within body and device interfaces.

PubMed

Likitlersuang, Jirapat; Leineweber, Matthew J; Andrysek, Jan

2017-10-01

Thin film force sensors are commonly used within biomechanical systems, and at the interface of the human body and medical and non-medical devices. However, limited information is available about their performance in such applications. The aims of this study were to evaluate and determine ways to improve the performance of thin film (FlexiForce) sensors at the body/device interface. Using a custom apparatus designed to load the sensors under simulated body/device conditions, two aspects were explored relating to sensor calibration and application. The findings revealed accuracy errors of 23.3±17.6% for force measurements at the body/device interface with conventional techniques of sensor calibration and application. Applying a thin rigid disc between the sensor and human body and calibrating the sensor using compliant surfaces was found to substantially reduce measurement errors to 2.9±2.0%. The use of alternative calibration and application procedures is recommended to gain acceptable measurement performance from thin film force sensors in body/device applications. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Online handwritten mathematical expression recognition

NASA Astrophysics Data System (ADS)

Büyükbayrak, Hakan; Yanikoglu, Berrin; Erçil, Aytül

2007-01-01

We describe a system for recognizing online, handwritten mathematical expressions. The system is designed with a user-interface for writing scientific articles, supporting the recognition of basic mathematical expressions as well as integrals, summations, matrices etc. A feed-forward neural network recognizes symbols which are assumed to be single-stroke and a recursive algorithm parses the expression by combining neural network output and the structure of the expression. Preliminary results show that writer-dependent recognition rates are very high (99.8%) while writer-independent symbol recognition rates are lower (75%). The interface associated with the proposed system integrates the built-in recognition capabilities of the Microsoft's Tablet PC API for recognizing textual input and supports conversion of hand-drawn figures into PNG format. This enables the user to enter text, mathematics and draw figures in a single interface. After recognition, all output is combined into one LATEX code and compiled into a PDF file.

The Evolution of Neuroprosthetic Interfaces

PubMed Central

Adewole, Dayo O.; Serruya, Mijail D.; Harris, James P.; Burrell, Justin C.; Petrov, Dmitriy; Chen, H. Isaac; Wolf, John A.; Cullen, D. Kacy

2017-01-01

The ideal neuroprosthetic interface permits high-quality neural recording and stimulation of the nervous system while reliably providing clinical benefits over chronic periods. Although current technologies have made notable strides in this direction, significant improvements must be made to better achieve these design goals and satisfy clinical needs. This article provides an overview of the state of neuroprosthetic interfaces, starting with the design and placement of these interfaces before exploring the stimulation and recording platforms yielded from contemporary research. Finally, we outline emerging research trends in an effort to explore the potential next generation of neuroprosthetic interfaces. PMID:27652455

Examining sensory ability, feature matching and assessment-based adaptation for a brain-computer interface using the steady-state visually evoked potential.

PubMed

Brumberg, Jonathan S; Nguyen, Anh; Pitt, Kevin M; Lorenz, Sean D

2018-01-31

We investigated how overt visual attention and oculomotor control influence successful use of a visual feedback brain-computer interface (BCI) for accessing augmentative and alternative communication (AAC) devices in a heterogeneous population of individuals with profound neuromotor impairments. BCIs are often tested within a single patient population limiting generalization of results. This study focuses on examining individual sensory abilities with an eye toward possible interface adaptations to improve device performance. Five individuals with a range of neuromotor disorders participated in four-choice BCI control task involving the steady state visually evoked potential. The BCI graphical interface was designed to simulate a commercial AAC device to examine whether an integrated device could be used successfully by individuals with neuromotor impairment. All participants were able to interact with the BCI and highest performance was found for participants able to employ an overt visual attention strategy. For participants with visual deficits to due to impaired oculomotor control, effective performance increased after accounting for mismatches between the graphical layout and participant visual capabilities. As BCIs are translated from research environments to clinical applications, the assessment of BCI-related skills will help facilitate proper device selection and provide individuals who use BCI the greatest likelihood of immediate and long term communicative success. Overall, our results indicate that adaptations can be an effective strategy to reduce barriers and increase access to BCI technology. These efforts should be directed by comprehensive assessments for matching individuals to the most appropriate device to support their complex communication needs. Implications for Rehabilitation Brain computer interfaces using the steady state visually evoked potential can be integrated with an augmentative and alternative communication device to provide access to language and literacy for individuals with neuromotor impairment. Comprehensive assessments are needed to fully understand the sensory, motor, and cognitive abilities of individuals who may use brain-computer interfaces for proper feature matching as selection of the most appropriate device including optimization device layouts and control paradigms. Oculomotor impairments negatively impact brain-computer interfaces that use the steady state visually evoked potential, but modifications to place interface stimuli and communication items in the intact visual field can improve successful outcomes.

Enhanced Lifetime of Polymer Solar Cells by Surface Passivation of Metal Oxide Buffer Layers.

PubMed

Venkatesan, Swaminathan; Ngo, Evan; Khatiwada, Devendra; Zhang, Cheng; Qiao, Qiquan

2015-07-29

The role of electron selective interfaces on the performance and lifetime of polymer solar cells were compared and analyzed. Bilayer interfaces consisting of metal oxide films with cationic polymer modification namely poly ethylenimine ethoxylated (PEIE) were found to enhance device lifetime compared to bare metal oxide films when used as an electron selective cathode interface. Devices utilizing surface-modified metal oxide layers showed enhanced lifetimes, retaining up to 85% of their original efficiency when stored in ambient atmosphere for 180 days without any encapsulation. The work function and surface potential of zinc oxide (ZnO) and ZnO/PEIE interlayers were evaluated using Kelvin probe and Kelvin probe force microscopy (KPFM) respectively. Kelvin probe measurements showed a smaller reduction in work function of ZnO/PEIE films compared to bare ZnO films when aged in atmospheric conditions. KPFM measurements showed that the surface potential of the ZnO surface drastically reduces when stored in ambient air for 7 days because of surface oxidation. Surface oxidation of the interface led to a substantial decrease in the performance in aged devices. The enhancement in the lifetime of devices with a bilayer interface was correlated to the suppressed surface oxidation of the metal oxide layers. The PEIE passivated surface retained a lower Fermi level when aged, which led to lower trap-assisted recombination at the polymer-cathode interface. Further photocharge extraction by linearly increasing voltage (Photo-CELIV) measurements were performed on fresh and aged samples to evaluate the field required to extract maximum charges. Fresh devices with a bare ZnO cathode interlayer required a lower field than devices with ZnO/PEIE cathode interface. However, aged devices with ZnO required a much higher field to extract charges while aged devices with ZnO/PEIE showed a minor increase compared to the fresh devices. Results indicate that surface modification can act as a suitable passivation layer to suppress oxidation in metal oxide thin films for enhanced lifetime in inverted organic solar cells.

Brain-computer interface devices for patients with paralysis and amputation: a meeting report

NASA Astrophysics Data System (ADS)

Bowsher, K.; Civillico, E. F.; Coburn, J.; Collinger, J.; Contreras-Vidal, J. L.; Denison, T.; Donoghue, J.; French, J.; Getzoff, N.; Hochberg, L. R.; Hoffmann, M.; Judy, J.; Kleitman, N.; Knaack, G.; Krauthamer, V.; Ludwig, K.; Moynahan, M.; Pancrazio, J. J.; Peckham, P. H.; Pena, C.; Pinto, V.; Ryan, T.; Saha, D.; Scharen, H.; Shermer, S.; Skodacek, K.; Takmakov, P.; Tyler, D.; Vasudevan, S.; Wachrathit, K.; Weber, D.; Welle, C. G.; Ye, M.

2016-04-01

Objective. The Food and Drug Administration’s (FDA) Center for Devices and Radiological Health (CDRH) believes it is important to help stakeholders (e.g., manufacturers, health-care professionals, patients, patient advocates, academia, and other government agencies) navigate the regulatory landscape for medical devices. For innovative devices involving brain-computer interfaces, this is particularly important. Approach. Towards this goal, on 21 November, 2014, CDRH held an open public workshop on its White Oak, MD campus with the aim of fostering an open discussion on the scientific and clinical considerations associated with the development of brain-computer interface (BCI) devices, defined for the purposes of this workshop as neuroprostheses that interface with the central or peripheral nervous system to restore lost motor or sensory capabilities. Main results. This paper summarizes the presentations and discussions from that workshop. Significance. CDRH plans to use this information to develop regulatory considerations that will promote innovation while maintaining appropriate patient protections. FDA plans to build on advances in regulatory science and input provided in this workshop to develop guidance that provides recommendations for premarket submissions for BCI devices. These proceedings will be a resource for the BCI community during the development of medical devices for consumers.

Brain-computer interface devices for patients with paralysis and amputation: a meeting report.

PubMed

Bowsher, K; Civillico, E F; Coburn, J; Collinger, J; Contreras-Vidal, J L; Denison, T; Donoghue, J; French, J; Getzoff, N; Hochberg, L R; Hoffmann, M; Judy, J; Kleitman, N; Knaack, G; Krauthamer, V; Ludwig, K; Moynahan, M; Pancrazio, J J; Peckham, P H; Pena, C; Pinto, V; Ryan, T; Saha, D; Scharen, H; Shermer, S; Skodacek, K; Takmakov, P; Tyler, D; Vasudevan, S; Wachrathit, K; Weber, D; Welle, C G; Ye, M

2016-04-01

The Food and Drug Administration's (FDA) Center for Devices and Radiological Health (CDRH) believes it is important to help stakeholders (e.g., manufacturers, health-care professionals, patients, patient advocates, academia, and other government agencies) navigate the regulatory landscape for medical devices. For innovative devices involving brain-computer interfaces, this is particularly important. Towards this goal, on 21 November, 2014, CDRH held an open public workshop on its White Oak, MD campus with the aim of fostering an open discussion on the scientific and clinical considerations associated with the development of brain-computer interface (BCI) devices, defined for the purposes of this workshop as neuroprostheses that interface with the central or peripheral nervous system to restore lost motor or sensory capabilities. This paper summarizes the presentations and discussions from that workshop. CDRH plans to use this information to develop regulatory considerations that will promote innovation while maintaining appropriate patient protections. FDA plans to build on advances in regulatory science and input provided in this workshop to develop guidance that provides recommendations for premarket submissions for BCI devices. These proceedings will be a resource for the BCI community during the development of medical devices for consumers.

Chronic impedance spectroscopy of an endovascular stent-electrode array

NASA Astrophysics Data System (ADS)

Opie, Nicholas L.; John, Sam E.; Rind, Gil S.; Ronayne, Stephen M.; Grayden, David B.; Burkitt, Anthony N.; May, Clive N.; O'Brien, Terence J.; Oxley, Thomas J.

2016-08-01

Objective. Recently, we reported a minimally invasive stent-electrode array capable of recording neural signals from within a blood vessel. We now investigate the use of electrochemical impedance spectroscopy (EIS) measurements to infer changes occurring to the electrode-tissue interface from devices implanted in a cohort of sheep for up to 190 days. Approach. In a cohort of 15 sheep, endovascular stent-electrode arrays were implanted in the superior sagittal sinus overlying the motor cortex for up to 190 days. EIS was performed routinely to quantify viable electrodes for up to 91 days. An equivalent circuit model (ECM) was developed from the in vivo measurements to characterize the electrode-tissue interface changes occurring to the electrodes chronically implanted within a blood vessel. Post-mortem histological assessment of stent and electrode incorporation into the wall of the cortical vessels was compared to the electrical impedance measurements. Main results. EIS could be used to infer electrode viability and was consistent with x-ray analysis performed in vivo, and post-mortem evaluation. Viable electrodes exhibited consistent 1 kHz impedances across the 91 day measurement period, with the peak resistance frequency for the acquired data also stable over time. There was a significant change in 100 Hz phase angles, increasing from -67.8° ± 8.8° at day 0 to -43.8° ± 0.8° at day 91, which was observed to stabilize after eight days. ECM’s modeled to the data suggested this change was due to an increase in the capacitance of the electrode-tissue interface. This was supported by histological assessment with >85% of the implanted stent struts covered with neointima and incorporated into the blood vessel within two weeks. Conclusion. This work demonstrated that EIS could be used to determine the viability of electrode implanted chronically within a blood vessel. Impedance measurements alone were not observed to be a useful predictor of alterations occurring at the electrode tissue interface. However, measurement of 100 Hz phase angles was in good agreement with the capacitive changes predicted by the ECM and consistent with suggestions that this represents protein absorption on the electrode surface. 100 Hz phase angles stabilized after 8 days, consistent with histologically assessed samples. Significance. These findings demonstrate the potential application of this technology for use as a chronic neural recording system and indicate the importance of conducting EIS as a measure to identify viable electrodes and changes occurring at the electrode-tissue interface.

Flexible inorganic light emitting diodes and transparent PEDOT:PSS/Parylene C for simultaneous optogenetics and electrocorticography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lee, Keundong; Ganji, Mehran; Hossain, Lorraine; Ro, Yun Goo; Lee, Sang Heon; Park, Jong-woo; Yoo, Dongha; Yoon, Jiyoung; Yi, Gyu-Chul; Dayeh, Shadi A.

2017-02-01

Electrocorticography (ECoG) is a powerful tool for direct mapping of local field potentials from the brain surface. Progress in development of high-fidelity materials such as poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) on thin conformal substrates such as parylene C enabled intimate contact with cortical surfaces and higher quality recordings from small volumes of neurons. Meanwhile, stimulation of neuronal activity is conventionally accomplished with electrical microstimulation and transcranial magnetic stimulation that can be combined with ECoG to form the basis of bidirectional neural interface. However, these stimulation mechanisms are less controlled and primitively understood on the local and cellular levels. With the advent of optogenetics, the localization and specificity of neuronal stimulation and inhibition is possible. Therefore, the development of integrated devices that can merge the sensitivity of ECoG or depth recording with optogenetic tools can lead to newer frontiers in understanding the neuronal activity. Herein, we introduce a hybrid device comprising flexible inorganic LED arrays integrated PEDOT:PSS/parylene C microelectrode arrays for high resolution bidirectional neuronal interfaces. The flexible inorganic LEDs have been developed by the metal-organic vapor phase epitaxy of position-controlled GaN microLEDs on ZnO nanostructured templates pre-grown at precise locations on a graphene layer. By transferring it onto the microelectrode arrays, it can provides the individual electrical addressability by light stimulation patterns. We will present experimental and simulation results on the optoelectronic characteristics and light activation capability of flexible microLEDs and their evaluation in vivo.

Circling motion and screen edges as an alternative input method for on-screen target manipulation.

PubMed

Ka, Hyun W; Simpson, Richard C

2017-04-01

To investigate a new alternative interaction method, called circling interface, for manipulating on-screen objects. To specify a target, the user makes a circling motion around the target. To specify a desired pointing command with the circling interface, each edge of the screen is used. The user selects a command before circling the target. To evaluate the circling interface, we conducted an experiment with 16 participants, comparing the performance on pointing tasks with different combinations of selection method (circling interface, physical mouse and dwelling interface) and input device (normal computer mouse, head pointer and joystick mouse emulator). A circling interface is compatible with many types of pointing devices, not requiring physical activation of mouse buttons, and is more efficient than dwell-clicking. Across all common pointing operations, the circling interface had a tendency to produce faster performance with a head-mounted mouse emulator than with a joystick mouse. The performance accuracy of the circling interface outperformed the dwelling interface. It was demonstrated that the circling interface has the potential as another alternative pointing method for selecting and manipulating objects in a graphical user interface. Implications for Rehabilitation A circling interface will improve clinical practice by providing an alternative pointing method that does not require physically activating mouse buttons and is more efficient than dwell-clicking. The Circling interface can also work with AAC devices.

Pattern learning with deep neural networks in EMG-based speech recognition.

PubMed

Wand, Michael; Schultz, Tanja

2014-01-01

We report on classification of phones and phonetic features from facial electromyographic (EMG) data, within the context of our EMG-based Silent Speech interface. In this paper we show that a Deep Neural Network can be used to perform this classification task, yielding a significant improvement over conventional Gaussian Mixture models. Our central contribution is the visualization of patterns which are learned by the neural network. With increasing network depth, these patterns represent more and more intricate electromyographic activity.

Neural Network Prototyping Package Within IRAF

NASA Technical Reports Server (NTRS)

Bazell, David

1997-01-01

The purpose of this contract was to develop a neural network package within the IRAF environment to allow users to easily understand and use different neural network algorithms the analysis of astronomical data. The package was developed for use within IRAF to allow portability to different computing environments and to provide a familiar and easy to use interface with the routines. In addition to developing the software and supporting documentation, we planned to use the system for the analysis of several sample problems to prove its viability and usefulness.

Neural-Network-Development Program

NASA Technical Reports Server (NTRS)

Phillips, Todd A.

1993-01-01

NETS, software tool for development and evaluation of neural networks, provides simulation of neural-network algorithms plus computing environment for development of such algorithms. Uses back-propagation learning method for all of networks it creates. Enables user to customize patterns of connections between layers of network. Also provides features for saving, during learning process, values of weights, providing more-precise control over learning process. Written in ANSI standard C language. Machine-independent version (MSC-21588) includes only code for command-line-interface version of NETS 3.0.

AAAIC '88 - Aerospace Applications of Artificial Intelligence; Proceedings of the Fourth Annual Conference, Dayton, OH, Oct. 25-27, 1988. Volumes 1 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, J.R.; Netrologic, Inc., San Diego, CA)

1988-01-01

Topics presented include integrating neural networks and expert systems, neural networks and signal processing, machine learning, cognition and avionics applications, artificial intelligence and man-machine interface issues, real time expert systems, artificial intelligence, and engineering applications. Also considered are advanced problem solving techniques, combinational optimization for scheduling and resource control, data fusion/sensor fusion, back propagation with momentum, shared weights and recurrency, automatic target recognition, cybernetics, optical neural networks.

A Wirelessly Powered and Controlled Device for Optical Neural Control of Freely-Behaving Animals

PubMed Central

Wentz, Christian T.; Bernstein, Jacob G.; Monahan, Patrick; Guerra, Alexander; Rodriguez, Alex; Boyden, Edward S.

2011-01-01

Optogenetics, the ability to use light to activate and silence specific neuron types within neural networks in vivo and in vitro, is revolutionizing neuroscientists’ capacity to understand how defined neural circuit elements contribute to normal and pathological brain functions. Typically awake behaving experiments are conducted by inserting an optical fiber into the brain, tethered to a remote laser, or by utilizing an implanted LED, tethered to a remote power source. A fully wireless system would enable chronic or longitudinal experiments where long duration tethering is impractical, and would also support high-throughput experimentation. However, the high power requirements of light sources (LEDs, lasers), especially in the context of the high-frequency pulse trains often desired in experiments, precludes battery-powered approaches from being widely applicable. We have developed a headborne device weighing 2 grams capable of wirelessly receiving power using a resonant RF power link and storing the energy in an adaptive supercapacitor circuit, which can algorithmically control one or more headborne LEDs via a microcontroller. The device can deliver approximately 2W of power to the LEDs in steady state, and 4.3W in bursts. We also present an optional radio transceiver module (1 gram) which, when added to the base headborne device, enables real-time updating of light delivery protocols; dozens of devices can be simultaneously controlled from one computer. We demonstrate use of the technology to wirelessly drive cortical control of movement in mice. These devices may serve as prototypes for clinical ultra-precise neural prosthetics that use light as the modality of biological control. PMID:21701058

A device-dependent interface for interactive image display

NASA Technical Reports Server (NTRS)

Perkins, D. C.; Szczur, M. R.; Owings, J.; Jamros, R. K.

1984-01-01

The structure of the device independent Display Management Subsystem (DMS) and the interface routines that are available to the applications programmer for use in developing a set of portable image display utility programs are described.

Synthesis and characterization of sputtered titanium nitride as a nucleation layer for novel neural electrode coatings

NASA Astrophysics Data System (ADS)

Sait, R. A.; Cross, R. B. M.

2017-12-01

A growing demand for chronically implantable electrodes has led to a search for the most suitable neural electrode interface material. Nobel metals such as platinum (Pt) are inadequate for electrode/neuron interfaces at small scales due to their poor electrochemical properties, low charge injection and high charge density per unit area. Titanium nitride (TiN) has been implemented in neural electrodes application due to its outstanding properties. In this work, TiNx films were deposited by non-reactive radio frequency (RF) magnetron sputtering towards the development of a novel TiN nanowires (NWs) neural interface. Although, there is substantial work on this material, its growth using non-reactive RF magnetron sputtering has not been reported previously and optimised towards the growth of TiN NWs and their use in neural interface applications. The sputtering parameters of RF power and argon (Ar) flow rate were varied in order to investigate their effects on the structural, electrical and electrochemical properties of the TiN films. A dense film morphology was observed in the scanning electron microscopy (SEM) images of TiN thin films showing a columnar structure. The film preferential orientation was changed between (200) and (111) with Ar flow rate due to the variation of the kinetic energy (KE) of the sputtered atoms. The crystallites size obtained were in the range of 13-95 nm. Surface roughness was found to increase from 0.69 to 1.95 nm as Ar flow rate increased. TiNx films showed a good electrical resistivity of 228 μΩ cm. Stoichiometry was found to vary with sputtering conditions in which the nitrogen content was found to deplete from the film at low Ar flow rate. The electrochemical behaviour of TiN films were characterised and the highest capacitance value obtained was 0.416 mF/cm2. From the results, it can be suggested that TiN thin film can be easily optimised to act as a nucleation layer for the growth of nanowires.

Conductive nanogel-interfaced neural microelectrode arrays with electrically controlled in-situ delivery of manganese ions enabling high-resolution MEMRI for synchronous neural tracing with deep brain stimulation.

PubMed

Huang, Wei-Chen; Lo, Yu-Chih; Chu, Chao-Yi; Lai, Hsin-Yi; Chen, You-Yin; Chen, San-Yuan

2017-04-01

Chronic brain stimulation has become a promising physical therapy with increased efficacy and efficiency in the treatment of neurodegenerative diseases. The application of deep brain electrical stimulation (DBS) combined with manganese-enhanced magnetic resonance imaging (MEMRI) provides an unbiased representation of the functional anatomy, which shows the communication between areas of the brain responding to the therapy. However, it is challenging for the current system to provide a real-time high-resolution image because the incorporated MnCl 2 solution through microinjection usually results in image blurring or toxicity due to the uncontrollable diffusion of Mn 2+ . In this study, we developed a new type of conductive nanogel-based neural interface composed of amphiphilic chitosan-modified poly(3,4 -ethylenedioxythiophene) (PMSDT) that can exhibit biomimic structural/mechanical properties and ionic/electrical conductivity comparable to that of Au. More importantly, the PMSDT enables metal-ligand bonding with Mn 2+ ions, so that the system can release Mn 2+ ions rather than MnCl 2 solution directly and precisely controlled by electrical stimulation (ES) to achieve real-time high-resolution MEMRI. With the integration of PMSDT nanogel-based coating in polyimide-based microelectrode arrays, the post-implantation DBS enables frequency-dependent MR imaging in vivo, as well as small focal imaging in response to channel site-specific stimulation on the implant. The MR imaging of the implanted brain treated with 5-min electrical stimulation showed a thalamocortical neuronal pathway after 36 h, confirming the effective activation of a downstream neuronal circuit following DBS. By eliminating the susceptibility to artifact and toxicity, this system, in combination with a MR-compatible implant and a bio-compliant neural interface, provides a harmless and synchronic functional anatomy for DBS. The study demonstrates a model of MEMRI-functionalized DBS based on functional neural interface engineering and controllable delivery technology, which can be utilized in more detailed exploration of the functional anatomy in the treatment of neurodegenerative diseases. Copyright © 2017 Elsevier Ltd. All rights reserved.

An optical neural interface: in vivo control of rodent motor cortex with integrated fiberoptic and optogenetic technology

NASA Astrophysics Data System (ADS)

Aravanis, Alexander M.; Wang, Li-Ping; Zhang, Feng; Meltzer, Leslie A.; Mogri, Murtaza Z.; Schneider, M. Bret; Deisseroth, Karl

2007-09-01

Neural interface technology has made enormous strides in recent years but stimulating electrodes remain incapable of reliably targeting specific cell types (e.g. excitatory or inhibitory neurons) within neural tissue. This obstacle has major scientific and clinical implications. For example, there is intense debate among physicians, neuroengineers and neuroscientists regarding the relevant cell types recruited during deep brain stimulation (DBS); moreover, many debilitating side effects of DBS likely result from lack of cell-type specificity. We describe here a novel optical neural interface technology that will allow neuroengineers to optically address specific cell types in vivo with millisecond temporal precision. Channelrhodopsin-2 (ChR2), an algal light-activated ion channel we developed for use in mammals, can give rise to safe, light-driven stimulation of CNS neurons on a timescale of milliseconds. Because ChR2 is genetically targetable, specific populations of neurons even sparsely embedded within intact circuitry can be stimulated with high temporal precision. Here we report the first in vivo behavioral demonstration of a functional optical neural interface (ONI) in intact animals, involving integrated fiberoptic and optogenetic technology. We developed a solid-state laser diode system that can be pulsed with millisecond precision, outputs 20 mW of power at 473 nm, and is coupled to a lightweight, flexible multimode optical fiber, ~200 µm in diameter. To capitalize on the unique advantages of this system, we specifically targeted ChR2 to excitatory cells in vivo with the CaMKIIα promoter. Under these conditions, the intensity of light exiting the fiber (~380 mW mm-2) was sufficient to drive excitatory neurons in vivo and control motor cortex function with behavioral output in intact rodents. No exogenous chemical cofactor was needed at any point, a crucial finding for in vivo work in large mammals. Achieving modulation of behavior with optical control of neuronal subtypes may give rise to fundamental network-level insights complementary to what electrode methodologies have taught us, and the emerging optogenetic toolkit may find application across a broad range of neuroscience, neuroengineering and clinical questions.

Design and implementation of a seamless and comprehensive integrated medical device interface system for outpatient electronic medical records in a general hospital.

PubMed

Choi, Jong Soo; Lee, Jean Hyoung; Park, Jong Hwan; Nam, Han Seung; Kwon, Hyuknam; Kim, Dongsoo; Park, Seung Woo

2011-04-01

Implementing an efficient Electronic Medical Record (EMR) system is regarded as one of the key strategies for improving the quality of healthcare services. However, the system's interoperability between medical devices and the EMR is a big barrier to deploying the EMR system in an outpatient clinical setting. The purpose of this study is to design a framework for a seamless and comprehensively integrated medical device interface system, and to develop and implement a system for accelerating the deployment of the EMR system. We designed and developed a framework that could transform data from medical devices into the relevant standards and then store them in the EMR. The framework is composed of 5 interfacing methods according to the types of medical devices utilized at an outpatient clinical setting, registered in Samsung Medical Center (SMC) database. The medical devices used for this study were devices that have microchips embedded or that came packaged with personal computers. The devices are completely integrated with the EMR based on SMC's long term IT strategies. First deployment of integrating 352 medical devices into the EMR took place in April, 2006, and it took about 48 months. By March, 2010, every medical device was interfaced with the EMR. About 66,000 medical examinations per month were performed taking up an average of 50GB of storage space. We surveyed users, mainly the technicians. Out of 73 that responded, 76% of the respondents replied that they were strongly satisfied or satisfied, 20% replied as being neutral and only 4% complained about the speed of the system, which was attributed to the slow speed of the old-fashioned medical devices and computers. The current implementation of the medical device interface system based on the SMC framework significantly streamlines the clinical workflow in a satisfactory manner. 2010 Elsevier Ireland Ltd. All rights reserved.

Toward a Proprioceptive Neural Interface That Mimics Natural Cortical Activity

PubMed Central

Tomlinson, Tucker

2017-01-01

The dramatic advances in efferent neural interfaces over the past decade are remarkable, with cortical signals used to allow paralyzed patients to control the movement of a prosthetic limb or even their own hand. However, this success has thrown into relief, the relative lack of progress in our ability to restore somatosensation to these same patients. Somatosensation, including proprioception, the sense of limb position and movement, plays a crucial role in even basic motor tasks like reaching and walking. Its loss results in crippling deficits. Historical work dating back decades and even centuries has demonstrated that modality-specific sensations can be elicited by activating the central nervous system electrically. Recent work has focused on the challenge of refining these sensations by stimulating the somatosensory cortex (S1) directly. Animals are able to detect particular patterns of stimulation and even associate those patterns with particular sensory cues. Most of this work has involved areas of the somatosensory cortex that mediate the sense of touch. Very little corresponding work has been done for proprioception. Here we describe the effort to develop afferent neural interfaces through spatiotemporally precise intracortical microstimulation (ICMS). We review what is known of the cortical representation of proprioception, and describe recent work in our lab that demonstrates for the first time, that sensations like those of natural proprioception may be evoked by ICMS in S1. These preliminary findings are an important first step to the development of an afferent cortical interface to restore proprioception. PMID:28035576

Toward a Proprioceptive Neural Interface that Mimics Natural Cortical Activity.

PubMed

Tomlinson, Tucker; Miller, Lee E

2016-01-01

The dramatic advances in efferent neural interfaces over the past decade are remarkable, with cortical signals used to allow paralyzed patients to control the movement of a prosthetic limb or even their own hand. However, this success has thrown into relief, the relative lack of progress in our ability to restore somatosensation to these same patients. Somatosensation, including proprioception, the sense of limb position and movement, plays a crucial role in even basic motor tasks like reaching and walking. Its loss results in crippling deficits. Historical work dating back decades and even centuries has demonstrated that modality-specific sensations can be elicited by activating the central nervous system electrically. Recent work has focused on the challenge of refining these sensations by stimulating the somatosensory cortex (S1) directly. Animals are able to detect particular patterns of stimulation and even associate those patterns with particular sensory cues. Most of this work has involved areas of the somatosensory cortex that mediate the sense of touch. Very little corresponding work has been done for proprioception. Here we describe the effort to develop afferent neural interfaces through spatiotemporally precise intracortical microstimulation (ICMS). We review what is known of the cortical representation of proprioception, and describe recent work in our lab that demonstrates for the first time, that sensations like those of natural proprioception may be evoked by ICMS in S1. These preliminary findings are an important first step to the development of an afferent cortical interface to restore proprioception.

Minimally-Invasive Neural Interface for Distributed Wireless Electrocorticogram Recording Systems

PubMed Central

Chang, Sun-Il

2018-01-01

This paper presents a minimally-invasive neural interface for distributed wireless electrocorticogram (ECoG) recording systems. The proposed interface equips all necessary components for ECoG recording, such as the high performance front-end integrated circuits, a fabricated flexible microelectrode array, and wireless communication inside a miniaturized custom-made platform. The multiple units of the interface systems can be deployed to cover a broad range of the target brain region and transmit signals via a built-in intra-skin communication (ISCOM) module. The core integrated circuit (IC) consists of 16-channel, low-power push-pull double-gated preamplifiers, in-channel successive approximation register analog-to-digital converters (SAR ADC) with a single-clocked bootstrapping switch and a time-delayed control unit, an ISCOM module for wireless data transfer through the skin instead of a power-hungry RF wireless transmitter, and a monolithic voltage/current reference generator to support the aforementioned analog and mixed-signal circuit blocks. The IC was fabricated using 250 nm CMOS processes in an area of 3.2 × 0.9 mm2 and achieved the low-power operation of 2.5 µW per channel. Input-referred noise was measured as 5.62 µVrms for 10 Hz to 10 kHz and ENOB of 7.21 at 31.25 kS/s. The implemented system successfully recorded multi-channel neural activities in vivo from a primate and demonstrated modular expandability using the ISCOM with power consumption of 160 µW. PMID:29342103

Minimally-Invasive Neural Interface for Distributed Wireless Electrocorticogram Recording Systems.

PubMed

Chang, Sun-Il; Park, Sung-Yun; Yoon, Euisik

2018-01-17

This paper presents a minimally-invasive neural interface for distributed wireless electrocorticogram (ECoG) recording systems. The proposed interface equips all necessary components for ECoG recording, such as the high performance front-end integrated circuits, a fabricated flexible microelectrode array, and wireless communication inside a miniaturized custom-made platform. The multiple units of the interface systems can be deployed to cover a broad range of the target brain region and transmit signals via a built-in intra-skin communication (ISCOM) module. The core integrated circuit (IC) consists of 16-channel, low-power push-pull double-gated preamplifiers, in-channel successive approximation register analog-to-digital converters (SAR ADC) with a single-clocked bootstrapping switch and a time-delayed control unit, an ISCOM module for wireless data transfer through the skin instead of a power-hungry RF wireless transmitter, and a monolithic voltage/current reference generator to support the aforementioned analog and mixed-signal circuit blocks. The IC was fabricated using 250 nm CMOS processes in an area of 3.2 × 0.9 mm² and achieved the low-power operation of 2.5 µW per channel. Input-referred noise was measured as 5.62 µV rms for 10 Hz to 10 kHz and ENOB of 7.21 at 31.25 kS/s. The implemented system successfully recorded multi-channel neural activities in vivo from a primate and demonstrated modular expandability using the ISCOM with power consumption of 160 µW.