Intelligent fiber optic sensor for solution concentration examination

NASA Astrophysics Data System (ADS)

Borecki, Michal; Kruszewski, Jerzy

2003-09-01

This paper presents the working principles of intelligent fiber-optic intensity sensor used for solution concentration examination. The sensor head is the ending of the large core polymer optical fiber. The head works on the reflection intensity basis. The reflected signal level depends on Fresnel reflection and reflection on suspended matter when the head is submersed in solution. The sensor head is mounted on a lift. For detection purposes the signal includes head submerging, submersion, emerging and emergence is measured. This way the viscosity turbidity and refraction coefficient has an effect on measured signal. The signal forthcoming from head is processed electrically in opto-electronic interface. Then it is feed to neural network. The novelty of presented sensor is implementation of neural network that works in generalization mode. The sensor resolution depends on opto-electronic signal conversion precision and neural network learning accuracy. Therefore, the number and quality of points used for learning process is very important. The example sensor application for examination of liquid soap concentration in water is presented in the paper.

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.

The need for calcium imaging in nonhuman primates: New motor neuroscience and brain-machine interfaces.

PubMed

O'Shea, Daniel J; Trautmann, Eric; Chandrasekaran, Chandramouli; Stavisky, Sergey; Kao, Jonathan C; Sahani, Maneesh; Ryu, Stephen; Deisseroth, Karl; Shenoy, Krishna V

2017-01-01

A central goal of neuroscience is to understand how populations of neurons coordinate and cooperate in order to give rise to perception, cognition, and action. Nonhuman primates (NHPs) are an attractive model with which to understand these mechanisms in humans, primarily due to the strong homology of their brains and the cognitively sophisticated behaviors they can be trained to perform. Using electrode recordings, the activity of one to a few hundred individual neurons may be measured electrically, which has enabled many scientific findings and the development of brain-machine interfaces. Despite these successes, electrophysiology samples sparsely from neural populations and provides little information about the genetic identity and spatial micro-organization of recorded neurons. These limitations have spurred the development of all-optical methods for neural circuit interrogation. Fluorescent calcium signals serve as a reporter of neuronal responses, and when combined with post-mortem optical clearing techniques such as CLARITY, provide dense recordings of neuronal populations, spatially organized and annotated with genetic and anatomical information. Here, we advocate that this methodology, which has been of tremendous utility in smaller animal models, can and should be developed for use with NHPs. We review here several of the key opportunities and challenges for calcium-based optical imaging in NHPs. We focus on motor neuroscience and brain-machine interface design as representative domains of opportunity within the larger field of NHP neuroscience. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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.

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

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.

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.

Development and Evaluation of Micro-Electrocorticography Arrays for Neural Interfacing Applications

NASA Astrophysics Data System (ADS)

Schendel, Amelia Ann

Neural interfaces have great promise for both electrophysiological research and therapeutic applications. Whether for the study of neural circuitry or for neural prosthetic or other therapeutic applications, micro-electrocorticography (micro-ECoG) arrays have proven extremely useful as neural interfacing devices. These devices strike a balance between invasiveness and signal resolution, an important step towards eventual human application. The objective of this research was to make design improvements to micro-ECoG devices to enhance both biocompatibility and device functionality. To best evaluate the effectiveness of these improvements, a cranial window imaging method for in vivo monitoring of the longitudinal tissue response post device implant was developed. Employment of this method provided valuable insight into the way tissue grows around micro-ECoG arrays after epidural implantation, spurring a study of the effects of substrate geometry on the meningeal tissue response. The results of the substrate footprint comparison suggest that a more open substrate geometry provides an easy path for the tissue to grow around to the top side of the device, whereas a solid device substrate encourages the tissue to thicken beneath the device, between the electrode sites and the brain. The formation of thick scar tissue between the recording electrode sites and the neural tissue is disadvantageous for long-term recorded signal quality, and thus future micro-ECoG device designs should incorporate open-architecture substrates for enhanced longitudinal in vivo function. In addition to investigating improvements for long-term device reliability, it was also desired to enhance the functionality of micro-ECoG devices for neural electrophysiology research applications. To achieve this goal, a completely transparent graphene-based device was fabricated for use with the cranial window imaging method and optogenetic techniques. The use of graphene as the conductive material provided the transparency necessary to image tissues directly below the micro-ECoG electrode sites, and to transmit light through the electrode sites to underlying neural tissue, for optical stimulation of neural cells. The flexibility and broad-spectrum transparency of graphene make it an ideal choice for thin-film, flexible electronic devices.

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.

Stimulation of the human auditory nerve with optical radiation

NASA Astrophysics Data System (ADS)

Fishman, Andrew; Winkler, Piotr; Mierzwinski, Jozef; Beuth, Wojciech; Izzo Matic, Agnella; Siedlecki, Zygmunt; Teudt, Ingo; Maier, Hannes; Richter, Claus-Peter

2009-02-01

A novel, spatially selective method to stimulate cranial nerves has been proposed: contact free stimulation with optical radiation. The radiation source is an infrared pulsed laser. The Case Report is the first report ever that shows that optical stimulation of the auditory nerve is possible in the human. The ethical approach to conduct any measurements or tests in humans requires efficacy and safety studies in animals, which have been conducted in gerbils. This report represents the first step in a translational research project to initiate a paradigm shift in neural interfaces. A patient was selected who required surgical removal of a large meningioma angiomatum WHO I by a planned transcochlear approach. Prior to cochlear ablation by drilling and subsequent tumor resection, the cochlear nerve was stimulated with a pulsed infrared laser at low radiation energies. Stimulation with optical radiation evoked compound action potentials from the human auditory nerve. Stimulation of the auditory nerve with infrared laser pulses is possible in the human inner ear. The finding is an important step for translating results from animal experiments to human and furthers the development of a novel interface that uses optical radiation to stimulate neurons. Additional measurements are required to optimize the stimulation parameters.

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.

Neural Interfaces for Intracortical Recording: Requirements, Fabrication Methods, and Characteristics

PubMed Central

Szostak, Katarzyna M.; Grand, Laszlo; Constandinou, Timothy G.

2017-01-01

Implantable neural interfaces for central nervous system research have been designed with wire, polymer, or micromachining technologies over the past 70 years. Research on biocompatible materials, ideal probe shapes, and insertion methods has resulted in building more and more capable neural interfaces. Although the trend is promising, the long-term reliability of such devices has not yet met the required criteria for chronic human application. The performance of neural interfaces in chronic settings often degrades due to foreign body response to the implant that is initiated by the surgical procedure, and related to the probe structure, and material properties used in fabricating the neural interface. In this review, we identify the key requirements for neural interfaces for intracortical recording, describe the three different types of probes—microwire, micromachined, and polymer-based probes; their materials, fabrication methods, and discuss their characteristics and related challenges. PMID:29270103

Neural Interfaces for Intracortical Recording: Requirements, Fabrication Methods, and Characteristics.

PubMed

Szostak, Katarzyna M; Grand, Laszlo; Constandinou, Timothy G

2017-01-01

Implantable neural interfaces for central nervous system research have been designed with wire, polymer, or micromachining technologies over the past 70 years. Research on biocompatible materials, ideal probe shapes, and insertion methods has resulted in building more and more capable neural interfaces. Although the trend is promising, the long-term reliability of such devices has not yet met the required criteria for chronic human application. The performance of neural interfaces in chronic settings often degrades due to foreign body response to the implant that is initiated by the surgical procedure, and related to the probe structure, and material properties used in fabricating the neural interface. In this review, we identify the key requirements for neural interfaces for intracortical recording, describe the three different types of probes-microwire, micromachined, and polymer-based probes; their materials, fabrication methods, and discuss their characteristics and related challenges.

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.

Stretchable Transparent Electrode Arrays for Simultaneous Electrical and Optical Interrogation of Neural Circuits in Vivo.

PubMed

Zhang, Jing; Liu, Xiaojun; Xu, Wenjing; Luo, Wenhan; Li, Ming; Chu, Fangbing; Xu, Lu; Cao, Anyuan; Guan, Jisong; Tang, Shiming; Duan, Xiaojie

2018-05-09

Recent developments of transparent electrode arrays provide a unique capability for simultaneous optical and electrical interrogation of neural circuits in the brain. However, none of these electrode arrays possess the stretchability highly desired for interfacing with mechanically active neural systems, such as the brain under injury, the spinal cord, and the peripheral nervous system (PNS). Here, we report a stretchable transparent electrode array from carbon nanotube (CNT) web-like thin films that retains excellent electrochemical performance and broad-band optical transparency under stretching and is highly durable under cyclic stretching deformation. We show that the CNT electrodes record well-defined neuronal response signals with negligible light-induced artifacts from cortical surfaces under optogenetic stimulation. Simultaneous two-photon calcium imaging through the transparent CNT electrodes from cortical surfaces of GCaMP-expressing mice with epilepsy shows individual activated neurons in brain regions from which the concurrent electrical recording is taken, thus providing complementary cellular information in addition to the high-temporal-resolution electrical recording. Notably, the studies on rats show that the CNT electrodes remain operational during and after brain contusion that involves the rapid deformation of both the electrode array and brain tissue. This enables real-time, continuous electrophysiological monitoring of cortical activity under traumatic brain injury. These results highlight the potential application of the stretchable transparent CNT electrode arrays in combining electrical and optical modalities to study neural circuits, especially under mechanically active conditions, which could potentially provide important new insights into the local circuit dynamics of the spinal cord and PNS as well as the mechanism underlying traumatic injuries of the nervous system.

Functional recordings from awake, behaving rodents through a microchannel based regenerative neural interface

NASA Astrophysics Data System (ADS)

Gore, Russell K.; Choi, Yoonsu; Bellamkonda, Ravi; English, Arthur

2015-02-01

Objective. Neural interface technologies could provide controlling connections between the nervous system and external technologies, such as limb prosthetics. The recording of efferent, motor potentials is a critical requirement for a peripheral neural interface, as these signals represent the user-generated neural output intended to drive external devices. Our objective was to evaluate structural and functional neural regeneration through a microchannel neural interface and to characterize potentials recorded from electrodes placed within the microchannels in awake and behaving animals. Approach. Female rats were implanted with muscle EMG electrodes and, following unilateral sciatic nerve transection, the cut nerve was repaired either across a microchannel neural interface or with end-to-end surgical repair. During a 13 week recovery period, direct muscle responses to nerve stimulation proximal to the transection were monitored weekly. In two rats repaired with the neural interface, four wire electrodes were embedded in the microchannels and recordings were obtained within microchannels during proximal stimulation experiments and treadmill locomotion. Main results. In these proof-of-principle experiments, we found that axons from cut nerves were capable of functional reinnervation of distal muscle targets, whether regenerating through a microchannel device or after direct end-to-end repair. Discrete stimulation-evoked and volitional potentials were recorded within interface microchannels in a small group of awake and behaving animals and their firing patterns correlated directly with intramuscular recordings during locomotion. Of 38 potentials extracted, 19 were identified as motor axons reinnervating tibialis anterior or soleus muscles using spike triggered averaging. Significance. These results are evidence for motor axon regeneration through microchannels and are the first report of in vivo recordings from regenerated motor axons within microchannels in a small group of awake and behaving animals. These unique findings provide preliminary evidence that efferent, volitional motor potentials can be recorded from the microchannel-based peripheral neural interface; a critical requirement for any neural interface intended to facilitate direct neural control of external technologies.

Conducting Polymers for Neural Prosthetic and Neural Interface Applications

PubMed Central

2015-01-01

Neural interfacing devices are an artificial mechanism for restoring or supplementing the function of the nervous system lost as a result of injury or disease. Conducting polymers (CPs) are gaining significant attention due to their capacity to meet the performance criteria of a number of neuronal therapies including recording and stimulating neural activity, the regeneration of neural tissue and the delivery of bioactive molecules for mediating device-tissue interactions. CPs form a flexible platform technology that enables the development of tailored materials for a range of neuronal diagnostic and treatment therapies. In this review the application of CPs for neural prostheses and other neural interfacing devices are discussed, with a specific focus on neural recording, neural stimulation, neural regeneration, and therapeutic drug delivery. PMID:26414302

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.

Measurement of wavefront aberrations in cortex and peripheral nerve using a two-photon excitation guidestar

NASA Astrophysics Data System (ADS)

Futia, Gregory L.; Fontaine, Arjun; McCullough, Connor; Ozbay, Baris N.; George, Nickolas M.; Caldwell, John; Restrepo, Diego; Weir, Richard; Gibson, Emily A.

2018-02-01

Neural-machine interfaces using optogenetics are of interest due to their minimal invasiveness and potential for parallel read in and read out of activity. One possible biological target for such an interface is the peripheral nerve, where axonlevel imaging or stimulation could greatly improve interfacing with artificial limbs or enable neuron/fascicle level neuromodulation in the vagus nerve. Two-photon imaging has been successful in imaging brain activity using genetically encoded calcium or voltage indicators, but in the peripheral nerve, this is severely limited by scattering and aberrations from myelin. We employ a Shack-Hartman wavefront sensor and two-photon excitation guidestar to quantify optical scattering and aberrations in peripheral nerves and cortex. The sciatic and vagus nerves, and cortex from a ChAT-Cre ChR-eYFP transgenic mouse were excised and imaged directly. In peripheral nerves, defocus was the strongest aberration followed by astigmatism and coma. Peripheral nerve had orders of magnitude higher aberration compared with cortex. These results point to the potential of adaptive optics for increasing the depth of two-photon access into peripheral nerves.

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.

Neuromechanism Study of Insect–Machine Interface: Flight Control by Neural Electrical Stimulation

PubMed Central

Zhao, Huixia; Zheng, Nenggan; Ribi, Willi A.; Zheng, Huoqing; Xue, Lei; Gong, Fan; Zheng, Xiaoxiang; Hu, Fuliang

2014-01-01

The insect–machine interface (IMI) is a novel approach developed for man-made air vehicles, which directly controls insect flight by either neuromuscular or neural stimulation. In our previous study of IMI, we induced flight initiation and cessation reproducibly in restrained honeybees (Apis mellifera L.) via electrical stimulation of the bilateral optic lobes. To explore the neuromechanism underlying IMI, we applied electrical stimulation to seven subregions of the honeybee brain with the aid of a new method for localizing brain regions. Results showed that the success rate for initiating honeybee flight decreased in the order: α-lobe (or β-lobe), ellipsoid body, lobula, medulla and antennal lobe. Based on a comparison with other neurobiological studies in honeybees, we propose that there is a cluster of descending neurons in the honeybee brain that transmits neural excitation from stimulated brain areas to the thoracic ganglia, leading to flight behavior. This neural circuit may involve the higher-order integration center, the primary visual processing center and the suboesophageal ganglion, which is also associated with a possible learning and memory pathway. By pharmacologically manipulating the electrically stimulated honeybee brain, we have shown that octopamine, rather than dopamine, serotonin and acetylcholine, plays a part in the circuit underlying electrically elicited honeybee flight. Our study presents a new brain stimulation protocol for the honeybee–machine interface and has solved one of the questions with regard to understanding which functional divisions of the insect brain participate in flight control. It will support further studies to uncover the involved neurons inside specific brain areas and to test the hypothesized involvement of a visual learning and memory pathway in IMI flight control. PMID:25409523

Neuromechanism study of insect-machine interface: flight control by neural electrical stimulation.

PubMed

Zhao, Huixia; Zheng, Nenggan; Ribi, Willi A; Zheng, Huoqing; Xue, Lei; Gong, Fan; Zheng, Xiaoxiang; Hu, Fuliang

2014-01-01

The insect-machine interface (IMI) is a novel approach developed for man-made air vehicles, which directly controls insect flight by either neuromuscular or neural stimulation. In our previous study of IMI, we induced flight initiation and cessation reproducibly in restrained honeybees (Apis mellifera L.) via electrical stimulation of the bilateral optic lobes. To explore the neuromechanism underlying IMI, we applied electrical stimulation to seven subregions of the honeybee brain with the aid of a new method for localizing brain regions. Results showed that the success rate for initiating honeybee flight decreased in the order: α-lobe (or β-lobe), ellipsoid body, lobula, medulla and antennal lobe. Based on a comparison with other neurobiological studies in honeybees, we propose that there is a cluster of descending neurons in the honeybee brain that transmits neural excitation from stimulated brain areas to the thoracic ganglia, leading to flight behavior. This neural circuit may involve the higher-order integration center, the primary visual processing center and the suboesophageal ganglion, which is also associated with a possible learning and memory pathway. By pharmacologically manipulating the electrically stimulated honeybee brain, we have shown that octopamine, rather than dopamine, serotonin and acetylcholine, plays a part in the circuit underlying electrically elicited honeybee flight. Our study presents a new brain stimulation protocol for the honeybee-machine interface and has solved one of the questions with regard to understanding which functional divisions of the insect brain participate in flight control. It will support further studies to uncover the involved neurons inside specific brain areas and to test the hypothesized involvement of a visual learning and memory pathway in IMI flight control.

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.

Design, fabrication, and packaging of an integrated, wirelessly-powered optrode array for optogenetics application

PubMed Central

Kwon, Ki Yong; Lee, Hyung-Min; Ghovanloo, Maysam; Weber, Arthur; Li, Wen

2015-01-01

The recent development of optogenetics has created an increased demand for advancing engineering tools for optical modulation of neural circuitry. This paper details the design, fabrication, integration, and packaging procedures of a wirelessly-powered, light emitting diode (LED) coupled optrode neural interface for optogenetic studies. The LED-coupled optrode array employs microscale LED (μLED) chips and polymer-based microwaveguides to deliver light into multi-level cortical networks, coupled with microelectrodes to record spontaneous changes in neural activity. An integrated, implantable, switched-capacitor based stimulator (SCS) system provides high instantaneous power to the μLEDs through an inductive link to emit sufficient light and evoke neural activities. The presented system is mechanically flexible, biocompatible, miniaturized, and lightweight, suitable for chronic implantation in small freely behaving animals. The design of this system is scalable and its manufacturing is cost effective through batch fabrication using microelectromechanical systems (MEMS) technology. It can be adopted by other groups and customized for specific needs of individual experiments. PMID:25999823

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.

Rodent wearable ultrasound system for wireless neural recording.

PubMed

Piech, David K; Kay, Joshua E; Boser, Bernhard E; Maharbiz, Michel M

2017-07-01

Advances in minimally-invasive, distributed biological interface nodes enable possibilities for networks of sensors and actuators to connect the brain with external devices. The recent development of the neural dust sensor mote has shown that utilizing ultrasound backscatter communication enables untethered sub-mm neural recording devices. These implanted sensor motes require a wearable external ultrasound interrogation device to enable in-vivo, freely-behaving neural interface experiments. However, minimizing the complexity and size of the implanted sensors shifts the power and processing burden to the external interrogator. In this paper, we present an ultrasound backscatter interrogator that supports real-time backscatter processing in a rodent-wearable, completely wireless device. We demonstrate a generic digital encoding scheme which is intended for transmitting neural information. The system integrates a front-end ultrasonic interface ASIC with off-the-shelf components to enable a highly compact ultrasound interrogation device intended for rodent neural interface experiments but applicable to other model systems.

Optical computing and neural networks; Proceedings of the Meeting, National Chiao Tung Univ., Hsinchu, Taiwan, Dec. 16, 17, 1992

NASA Technical Reports Server (NTRS)

Hsu, Ken-Yuh (Editor); Liu, Hua-Kuang (Editor)

1992-01-01

The present conference discusses optical neural networks, photorefractive nonlinear optics, optical pattern recognition, digital and analog processors, and holography and its applications. Attention is given to bifurcating optical information processing, neural structures in digital halftoning, an exemplar-based optical neural net classifier for color pattern recognition, volume storage in photorefractive disks, and microlaser-based compact optical neuroprocessors. Also treated are the optical implementation of a feature-enhanced optical interpattern-associative neural network model and its optical implementation, an optical pattern binary dual-rail logic gate module, a theoretical analysis for holographic associative memories, joint transform correlators, image addition and subtraction via the Talbot effect, and optical wavelet-matched filters. (No individual items are abstracted in this volume)

Optical computing and neural networks; Proceedings of the Meeting, National Chiao Tung Univ., Hsinchu, Taiwan, Dec. 16, 17, 1992

NASA Astrophysics Data System (ADS)

Hsu, Ken-Yuh; Liu, Hua-Kuang

The present conference discusses optical neural networks, photorefractive nonlinear optics, optical pattern recognition, digital and analog processors, and holography and its applications. Attention is given to bifurcating optical information processing, neural structures in digital halftoning, an exemplar-based optical neural net classifier for color pattern recognition, volume storage in photorefractive disks, and microlaser-based compact optical neuroprocessors. Also treated are the optical implementation of a feature-enhanced optical interpattern-associative neural network model and its optical implementation, an optical pattern binary dual-rail logic gate module, a theoretical analysis for holographic associative memories, joint transform correlators, image addition and subtraction via the Talbot effect, and optical wavelet-matched filters. (No individual items are abstracted in this volume)

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.

An Implantable Wireless Neural Interface System for Simultaneous Recording and Stimulation of Peripheral Nerve with a Single Cuff Electrode.

PubMed

Shon, Ahnsei; Chu, Jun-Uk; Jung, Jiuk; Kim, Hyungmin; Youn, Inchan

2017-12-21

Recently, implantable devices have become widely used in neural prostheses because they eliminate endemic drawbacks of conventional percutaneous neural interface systems. However, there are still several issues to be considered: low-efficiency wireless power transmission; wireless data communication over restricted operating distance with high power consumption; and limited functionality, working either as a neural signal recorder or as a stimulator. To overcome these issues, we suggest a novel implantable wireless neural interface system for simultaneous neural signal recording and stimulation using a single cuff electrode. By using widely available commercial off-the-shelf (COTS) components, an easily reconfigurable implantable wireless neural interface system was implemented into one compact module. The implantable device includes a wireless power consortium (WPC)-compliant power transmission circuit, a medical implant communication service (MICS)-band-based radio link and a cuff-electrode path controller for simultaneous neural signal recording and stimulation. During in vivo experiments with rabbit models, the implantable device successfully recorded and stimulated the tibial and peroneal nerves while communicating with the external device. The proposed system can be modified for various implantable medical devices, especially such as closed-loop control based implantable neural prostheses requiring neural signal recording and stimulation at the same time.

An Implantable Wireless Neural Interface System for Simultaneous Recording and Stimulation of Peripheral Nerve with a Single Cuff Electrode

PubMed Central

Shon, Ahnsei; Chu, Jun-Uk; Jung, Jiuk; Youn, Inchan

2017-01-01

Recently, implantable devices have become widely used in neural prostheses because they eliminate endemic drawbacks of conventional percutaneous neural interface systems. However, there are still several issues to be considered: low-efficiency wireless power transmission; wireless data communication over restricted operating distance with high power consumption; and limited functionality, working either as a neural signal recorder or as a stimulator. To overcome these issues, we suggest a novel implantable wireless neural interface system for simultaneous neural signal recording and stimulation using a single cuff electrode. By using widely available commercial off-the-shelf (COTS) components, an easily reconfigurable implantable wireless neural interface system was implemented into one compact module. The implantable device includes a wireless power consortium (WPC)-compliant power transmission circuit, a medical implant communication service (MICS)-band-based radio link and a cuff-electrode path controller for simultaneous neural signal recording and stimulation. During in vivo experiments with rabbit models, the implantable device successfully recorded and stimulated the tibial and peroneal nerves while communicating with the external device. The proposed system can be modified for various implantable medical devices, especially such as closed-loop control based implantable neural prostheses requiring neural signal recording and stimulation at the same time. PMID:29267230

Optogenetic micro-electrocorticography for modulating and localizing cerebral cortex activity

PubMed Central

Richner, Thomas J.; Thongpang, Sanitta; Brodnick, Sarah K.; Schendel, Amelia A.; Falk, Ryan W.; Krugner-Higby, Lisa A.; Pashaie, Ramin; Williams, Justin C.

2014-01-01

Objective Spatial localization of neural activity from within the brain with electrocorticography (ECoG) and electroencephalography (EEG) remains a challenge in clinical and research settings, and while microfabricated ECoG (micro-ECoG) array technology continues to improve, complimentary methods to simultaneously modulate cortical activity while recording are needed. Approach We developed a neural interface utilizing optogenetics, cranial windowing, and micro-ECoG arrays fabricated on a transparent polymer. This approach enabled us to directly modulate neural activity at known locations around micro-ECoG arrays in mice expressing Channelrhodopsin-2 (ChR2). We applied photostimuli varying in time, space and frequency to the cortical surface, and we targeted multiple depths within the cortex using an optical fiber while recording micro-ECoG signals. Main Results Negative potentials of up to 1.5 mV were evoked by photostimuli applied to the entire cortical window, while focally applied photostimuli evoked spatially localized micro-ECoG potentials. Two simultaneously applied focal stimuli could be separated, depending on the distance between them. Photostimuli applied within the cortex with an optical fiber evoked more complex micro-ECoG potentials with multiple positive and negative peaks whose relative amplitudes depended on the depth of the fiber. Significance Optogenetic ECoG has potential applications in the study of epilepsy, cortical dynamics, and neuroprostheses. PMID:24445482

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.

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.

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.

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.

Angle of Arrival Detection Through Artificial Neural Network Analysis of Optical Fiber Intensity Patterns

DTIC Science & Technology

1990-12-01

ARTIFICIAL NEURAL NETWORK ANALYSIS OF OPTICAL FIBER INTENSITY PATTERNS THESIS Scott Thomas Captain, USAF AFIT/GE/ENG/90D-62 DTIC...ELECTE ao • JAN08 1991 Approved for public release; distribution unlimited. AFIT/GE/ENG/90D-62 ANGLE OF ARRIVAL DETECTION THROUGH ARTIFICIAL NEURAL NETWORK ANALYSIS... ARTIFICIAL NEURAL NETWORK ANALYSIS OF OPTICAL FIBER INTENSITY PATTERNS L Introduction The optical sensors of United States Air Force reconnaissance

Two-way communication with neural networks in vivo using focused light

PubMed Central

Wilson, Nathan R.; Schummers, James; Runyan, Caroline A.; Yan, Sherry; Chen, Robert F.; Deng, Yuting; Sur, Mriganka

2014-01-01

Neuronal networks process information in a distributed, spatially heterogeneous fashion that transcends the layout of electrodes. In contrast, directed and steerable light offers the potential to engage specific cells on demand. We present a unified framework for adapting microscopes to use light for simultaneous in vivo stimulation and recording of cells at fine spatiotemporal resolutions. We utilize straightforward optics to lock onto networks in vivo, steer light to activate circuit elements, and simultaneously record from other cells. We then actualize this “free” augmentation on both an “open” two-photon microscope, and a leading commercial one. Following this protocol, setup of the system takes a few days and the result is a non-invasive interface to brain dynamics based on directed light, at a network resolution that was not previously possible and which will further improve with the rapid advance in development of optical reporters and effectors. This protocol is for physiologists who are competent with computers and wish to extend hardware and software to interface more fluidly with neuronal networks. PMID:23702834

Optical-Correlator Neural Network Based On Neocognitron

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1994-01-01

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

Novel design of electrical sensing interface for prosthetic limbs using optical micro cavities

NASA Astrophysics Data System (ADS)

Ali, Amir R.; Kamel, Mohamed A.

2018-04-01

This paper uses optical whispering galley modes (WGM) cavities to construct a new electrical sensing interface between prosthetic limb and the brain. The sensing element will detect the action potential signal in the neural membrane and the prosthetic limb will be actuated accordingly. The element is a WGM dielectric polymeric cavity. WGM based optical cavities can achieve very high values of sensitivity and quality factor; thus, any minute perturbations in the morphology of the cavity can be captured and measured. The action potential signal will produce an applied external electric field on the dielectric cavity causing it to deform due to the electrostriction effect. The resulting deformation will cause WGM shifts in the transmission spectrum of the cavity. Thus, the action potential or the applied electric field can be measured using these shifts. In this paper the action potential signal will be simulated through the use of a function generator and two metal electrodes. The sensing element will be situated between these electrodes to detect the electrical signal passing through. The achieved sensitivity is 27.5 pm/V in measuring the simulated action potential signal; and 0.32 pm/V.m-1 in measuring the applied electric field due to the passage of the simulated signal.

The PennBMBI: Design of a General Purpose Wireless Brain-Machine-Brain Interface System.

PubMed

Liu, Xilin; Zhang, Milin; Subei, Basheer; Richardson, Andrew G; Lucas, Timothy H; Van der Spiegel, Jan

2015-04-01

In this paper, a general purpose wireless Brain-Machine-Brain Interface (BMBI) system is presented. The system integrates four battery-powered wireless devices for the implementation of a closed-loop sensorimotor neural interface, including a neural signal analyzer, a neural stimulator, a body-area sensor node and a graphic user interface implemented on the PC end. The neural signal analyzer features a four channel analog front-end with configurable bandpass filter, gain stage, digitization resolution, and sampling rate. The target frequency band is configurable from EEG to single unit activity. A noise floor of 4.69 μVrms is achieved over a bandwidth from 0.05 Hz to 6 kHz. Digital filtering, neural feature extraction, spike detection, sensing-stimulating modulation, and compressed sensing measurement are realized in a central processing unit integrated in the analyzer. A flash memory card is also integrated in the analyzer. A 2-channel neural stimulator with a compliance voltage up to ± 12 V is included. The stimulator is capable of delivering unipolar or bipolar, charge-balanced current pulses with programmable pulse shape, amplitude, width, pulse train frequency and latency. A multi-functional sensor node, including an accelerometer, a temperature sensor, a flexiforce sensor and a general sensor extension port has been designed. A computer interface is designed to monitor, control and configure all aforementioned devices via a wireless link, according to a custom designed communication protocol. Wireless closed-loop operation between the sensory devices, neural stimulator, and neural signal analyzer can be configured. The proposed system was designed to link two sites in the brain, bridging the brain and external hardware, as well as creating new sensory and motor pathways for clinical practice. Bench test and in vivo experiments are performed to verify the functions and performances of the system.

Neural networks within multi-core optic fibers

PubMed Central

Cohen, Eyal; Malka, Dror; Shemer, Amir; Shahmoon, Asaf; Zalevsky, Zeev; London, Michael

2016-01-01

Hardware implementation of artificial neural networks facilitates real-time parallel processing of massive data sets. Optical neural networks offer low-volume 3D connectivity together with large bandwidth and minimal heat production in contrast to electronic implementation. Here, we present a conceptual design for in-fiber optical neural networks. Neurons and synapses are realized as individual silica cores in a multi-core fiber. Optical signals are transferred transversely between cores by means of optical coupling. Pump driven amplification in erbium-doped cores mimics synaptic interactions. We simulated three-layered feed-forward neural networks and explored their capabilities. Simulations suggest that networks can differentiate between given inputs depending on specific configurations of amplification; this implies classification and learning capabilities. Finally, we tested experimentally our basic neuronal elements using fibers, couplers, and amplifiers, and demonstrated that this configuration implements a neuron-like function. Therefore, devices similar to our proposed multi-core fiber could potentially serve as building blocks for future large-scale small-volume optical artificial neural networks. PMID:27383911

Neural networks within multi-core optic fibers.

PubMed

Cohen, Eyal; Malka, Dror; Shemer, Amir; Shahmoon, Asaf; Zalevsky, Zeev; London, Michael

2016-07-07

Hardware implementation of artificial neural networks facilitates real-time parallel processing of massive data sets. Optical neural networks offer low-volume 3D connectivity together with large bandwidth and minimal heat production in contrast to electronic implementation. Here, we present a conceptual design for in-fiber optical neural networks. Neurons and synapses are realized as individual silica cores in a multi-core fiber. Optical signals are transferred transversely between cores by means of optical coupling. Pump driven amplification in erbium-doped cores mimics synaptic interactions. We simulated three-layered feed-forward neural networks and explored their capabilities. Simulations suggest that networks can differentiate between given inputs depending on specific configurations of amplification; this implies classification and learning capabilities. Finally, we tested experimentally our basic neuronal elements using fibers, couplers, and amplifiers, and demonstrated that this configuration implements a neuron-like function. Therefore, devices similar to our proposed multi-core fiber could potentially serve as building blocks for future large-scale small-volume optical artificial neural networks.

Modified-hybrid optical neural network filter for multiple object recognition within cluttered scenes

NASA Astrophysics Data System (ADS)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.

2009-08-01

Motivated by the non-linear interpolation and generalization abilities of the hybrid optical neural network filter between the reference and non-reference images of the true-class object we designed the modifiedhybrid optical neural network filter. We applied an optical mask to the hybrid optical neural network's filter input. The mask was built with the constant weight connections of a randomly chosen image included in the training set. The resulted design of the modified-hybrid optical neural network filter is optimized for performing best in cluttered scenes of the true-class object. Due to the shift invariance properties inherited by its correlator unit the filter can accommodate multiple objects of the same class to be detected within an input cluttered image. Additionally, the architecture of the neural network unit of the general hybrid optical neural network filter allows the recognition of multiple objects of different classes within the input cluttered image by modifying the output layer of the unit. We test the modified-hybrid optical neural network filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. The filter is shown to exhibit with a single pass over the input data simultaneously out-of-plane rotation, shift invariance and good clutter tolerance. It is able to successfully detect and classify correctly the true-class objects within background clutter for which there has been no previous training.

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

Optical and neural anisotropy in peripheral vision

PubMed Central

Zheleznyak, Len; Barbot, Antoine; Ghosh, Atanu; Yoon, Geunyoung

2016-01-01

Optical blur in the peripheral retina is known to be highly anisotropic due to nonrotationally symmetric wavefront aberrations such as astigmatism and coma. At the neural level, the visual system exhibits anisotropies in orientation sensitivity across the visual field. In the fovea, the visual system shows higher sensitivity for cardinal over diagonal orientations, which is referred to as the oblique effect. However, in the peripheral retina, the neural visual system becomes more sensitive to radially-oriented signals, a phenomenon known as the meridional effect. Here, we examined the relative contributions of optics and neural processing to the meridional effect in 10 participants at 0°, 10°, and 20° in the temporal retina. Optical anisotropy was quantified by measuring the eye's habitual wavefront aberrations. Alternatively, neural anisotropy was evaluated by measuring contrast sensitivity (at 2 and 4 cyc/deg) while correcting the eye's aberrations with an adaptive optics vision simulator, thus bypassing any optical factors. As eccentricity increased, optical and neural anisotropy increased in magnitude. The average ratio of horizontal to vertical optical MTF (at 2 and 4 cyc/deg) at 0°, 10°, and 20° was 0.96 ± 0.14, 1.41 ± 0.54 and 2.15 ± 1.38, respectively. Similarly, the average ratio of horizontal to vertical contrast sensitivity with full optical correction at 0°, 10°, and 20° was 0.99 ± 0.15, 1.28 ± 0.28 and 1.75 ± 0.80, respectively. These results indicate that the neural system's orientation sensitivity coincides with habitual blur orientation. These findings support the neural origin of the meridional effect and raise important questions regarding the role of peripheral anisotropic optical quality in developing the meridional effect and emmetropization. PMID:26928220

A Wireless Implantable Switched-Capacitor Based Optogenetic Stimulating System

PubMed Central

Lee, Hyung-Min; Kwon, Ki-Yong; Li, Wen

2015-01-01

This paper presents a power-efficient implantable optogenetic interface using a wireless switched-capacitor based stimulating (SCS) system. The SCS efficiently charges storage capacitors directly from an inductive link and periodically discharges them into an array of micro-LEDs, providing high instantaneous power without affecting wireless link and system supply voltage. A custom-designed computer interface in LabVIEW environment wirelessly controls stimulation parameters through the inductive link, and an optrode array enables simultaneous neural recording along with optical stimulation. The 4-channel SCS system prototype has been implemented in a 0.35-μm CMOS process and combined with the optrode array. In vivo experiments involving light-induced local field potentials verified the efficacy of the SCS system. An implantable version of the SCS system with flexible hermetic sealing is under development for chronic experiments. PMID:25570099

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

Advanced miniature processing handware for ATR applications

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin (Inventor); Daud, Taher (Inventor); Thakoor, Anikumar (Inventor)

2003-01-01

A Hybrid Optoelectronic Neural Object Recognition System (HONORS), is disclosed, comprising two major building blocks: (1) an advanced grayscale optical correlator (OC) and (2) a massively parallel three-dimensional neural-processor. The optical correlator, with its inherent advantages in parallel processing and shift invariance, is used for target of interest (TOI) detection and segmentation. The three-dimensional neural-processor, with its robust neural learning capability, is used for target classification and identification. The hybrid optoelectronic neural object recognition system, with its powerful combination of optical processing and neural networks, enables real-time, large frame, automatic target recognition (ATR).

An Implantable Wireless Neural Interface for Recording Cortical Circuit Dynamics in Moving Primates

PubMed Central

Borton, David A.; Yin, Ming; Aceros, Juan; Nurmikko, Arto

2013-01-01

Objective Neural interface technology suitable for clinical translation has the potential to significantly impact the lives of amputees, spinal cord injury victims, and those living with severe neuromotor disease. Such systems must be chronically safe, durable, and effective. Approach We have designed and implemented a neural interface microsystem, housed in a compact, subcutaneous, and hermetically sealed titanium enclosure. The implanted device interfaces the brain with a 510k-approved, 100-element silicon-based MEA via a custom hermetic feedthrough design. Full spectrum neural signals were amplified (0.1Hz to 7.8kHz, ×200 gain) and multiplexed by a custom application specific integrated circuit, digitized, and then packaged for transmission. The neural data (24 Mbps) was transmitted by a wireless data link carried on an frequency shift key modulated signal at 3.2GHz and 3.8GHz to a receiver 1 meter away by design as a point-to-point communication link for human clinical use. The system was powered by an embedded medical grade rechargeable Li-ion battery for 7-hour continuous operation between recharge via an inductive transcutaneous wireless power link at 2MHz. Main results Device verification and early validation was performed in both swine and non-human primate freely-moving animal models and showed that the wireless implant was electrically stable, effective in capturing and delivering broadband neural data, and safe for over one year of testing. In addition, we have used the multichannel data from these mobile animal models to demonstrate the ability to decode neural population dynamics associated with motor activity. Significance We have developed an implanted wireless broadband neural recording device evaluated in non-human primate and swine. The use of this new implantable neural interface technology can provide insight on how to advance human neuroprostheses beyond the present early clinical trials. Further, such tools enable mobile patient use, have the potential for wider diagnosis of neurological conditions, and will advance brain research. PMID:23428937

An implantable wireless neural interface for recording cortical circuit dynamics in moving primates

NASA Astrophysics Data System (ADS)

Borton, David A.; Yin, Ming; Aceros, Juan; Nurmikko, Arto

2013-04-01

Objective. Neural interface technology suitable for clinical translation has the potential to significantly impact the lives of amputees, spinal cord injury victims and those living with severe neuromotor disease. Such systems must be chronically safe, durable and effective. Approach. We have designed and implemented a neural interface microsystem, housed in a compact, subcutaneous and hermetically sealed titanium enclosure. The implanted device interfaces the brain with a 510k-approved, 100-element silicon-based microelectrode array via a custom hermetic feedthrough design. Full spectrum neural signals were amplified (0.1 Hz to 7.8 kHz, 200× gain) and multiplexed by a custom application specific integrated circuit, digitized and then packaged for transmission. The neural data (24 Mbps) were transmitted by a wireless data link carried on a frequency-shift-key-modulated signal at 3.2 and 3.8 GHz to a receiver 1 m away by design as a point-to-point communication link for human clinical use. The system was powered by an embedded medical grade rechargeable Li-ion battery for 7 h continuous operation between recharge via an inductive transcutaneous wireless power link at 2 MHz. Main results. Device verification and early validation were performed in both swine and non-human primate freely-moving animal models and showed that the wireless implant was electrically stable, effective in capturing and delivering broadband neural data, and safe for over one year of testing. In addition, we have used the multichannel data from these mobile animal models to demonstrate the ability to decode neural population dynamics associated with motor activity. Significance. We have developed an implanted wireless broadband neural recording device evaluated in non-human primate and swine. The use of this new implantable neural interface technology can provide insight into how to advance human neuroprostheses beyond the present early clinical trials. Further, such tools enable mobile patient use, have the potential for wider diagnosis of neurological conditions and will advance brain research.

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

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.

Monitoring the evolution of boron doped porous diamond electrode on flexible retinal implant by OCT and in vivo impedance spectroscopy.

PubMed

Hébert, Clément; Cottance, Myline; Degardin, Julie; Scorsone, Emmanuel; Rousseau, Lionel; Lissorgues, Gaelle; Bergonzo, Philippe; Picaud, Serge

2016-12-01

Nanocrystalline Boron doped Diamond proved to be a very attractive material for neural interfacing, especially with the retina, where reduce glia growth is observed with respect to other materials, thus facilitating neuro-stimulation over long terms. In the present study, we integrated diamond microelectrodes on a polyimide substrate and investigated their performances for the development of neural prosthesis. A full description of the microfabrication of the implants is provided and their functionalities are assessed using cyclic voltammetry and electrochemical impedance spectroscopy. A porous structure of the electrode surface was thus revealed and showed promising properties for neural recording or stimulation. Using the flexible implant, we showed that is possible to follow in vivo the evolution of the electric contact between the diamond electrodes and the retina over 4months by using electrochemical impedance spectroscopy. The position of the implant was also monitored by optical coherence tomography to corroborate the information given by the impedance measurements. The results suggest that diamond microelectrodes are very good candidates for retinal prosthesis. Copyright © 2016. Published by Elsevier B.V.

Optic disc, foveal, and extrafoveal damage due to surgical separation of the vitreous.

PubMed

Russell, S R; Hageman, G S

2001-11-01

To evaluate the morphologic outcomes resulting from surgical vitreoretinal separation in young adult primates. Vitrectomy and mechanical separation of the vitreous from the internal limiting lamina (ILL) of the posterior retina and surface of the optic disc were performed on 25 young adult cynomolgus monkey eyes in vivo. Lectin histochemical studies were used to evaluate the vitreoretinal interface. Morphologic outcomes were tabulated. In 11 of 25 eye regions, residual vitreous remained attached to the ILL in some of the regions. Localized ILL breaks or separation of the ILL from the neural retina was noted in 9 eyes. Retinal tissue loss, including avulsion of the ganglion cell, inner plexiform, or inner nuclear layers, was observed in 7 eyes. Avulsion of axon bundles in the optic disc was noted in 9 eyes. Significantly, partial- or full-thickness foveal tears were noted in 11 eyes. Based on the surgeons' intraoperative observations, small superficial optic disc or retinal hemorrhages were observed in 3 of 25 eyes. None of the eyes on which a vitrectomy alone was performed showed ILL damage, or retinal or optic disc tissue loss. Damage may occur to the optic disc, fovea, and extrafoveal retina as a result of surgical separation of the vitreous from the retina in young adult primates. These data support the contention that surgically induced damage at the level of the vitreoretinal interface may help explain the visual field defects noted after surgery to close full-thickness macular holes. These data also support the need for developing additional modalities to assist in vitreous separation, thereby reducing the risk of traumatic complications associated with purely mechanical procedures.

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.

Acoustic Signal Processing in Photorefractive Optical Systems.

NASA Astrophysics Data System (ADS)

Zhou, Gan

This thesis discusses applications of the photorefractive effect in the context of acoustic signal processing. The devices and systems presented here illustrate the ideas and optical principles involved in holographic processing of acoustic information. The interest in optical processing stems from the similarities between holographic optical systems and contemporary models for massively parallel computation, in particular, neural networks. An initial step in acoustic processing is the transformation of acoustic signals into relevant optical forms. A fiber-optic transducer with photorefractive readout transforms acoustic signals into optical images corresponding to their short-time spectrum. The device analyzes complex sound signals and interfaces them with conventional optical correlators. The transducer consists of 130 multimode optical fibers sampling the spectral range of 100 Hz to 5 kHz logarithmically. A physical model of the human cochlea can help us understand some characteristics of human acoustic transduction and signal representation. We construct a life-sized cochlear model using elastic membranes coupled with two fluid-filled chambers, and use a photorefractive novelty filter to investigate its response. The detection sensitivity is determined to be 0.3 angstroms per root Hz at 2 kHz. Qualitative agreement is found between the model response and physiological data. Delay lines map time-domain signals into space -domain and permit holographic processing of temporal information. A parallel optical delay line using dynamic beam coupling in a rotating photorefractive crystal is presented. We experimentally demonstrate a 64 channel device with 0.5 seconds of time-delay and 167 Hz bandwidth. Acoustic signal recognition is described in a photorefractive system implementing the time-delay neural network model. The system consists of a photorefractive optical delay-line and a holographic correlator programmed in a LiNbO_3 crystal. We demonstrate the recognition of synthesized chirps as well as spoken words. A photorefractive ring resonator containing an optical delay line can learn temporal information through self-organization. We experimentally investigate a system that learns by itself and picks out the most-frequently -presented signals from the input. We also give results demonstrating the separation of two orthogonal temporal signals into two competing ring resonators.

Neural-network-directed alignment of optical systems using the laser-beam spatial filter as an example

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Krasowski, Michael J.; Weiland, Kenneth E.

1993-01-01

This report describes an effort at NASA Lewis Research Center to use artificial neural networks to automate the alignment and control of optical measurement systems. Specifically, it addresses the use of commercially available neural network software and hardware to direct alignments of the common laser-beam-smoothing spatial filter. The report presents a general approach for designing alignment records and combining these into training sets to teach optical alignment functions to neural networks and discusses the use of these training sets to train several types of neural networks. Neural network configurations used include the adaptive resonance network, the back-propagation-trained network, and the counter-propagation network. This work shows that neural networks can be used to produce robust sequencers. These sequencers can learn by example to execute the step-by-step procedures of optical alignment and also can learn adaptively to correct for environmentally induced misalignment. The long-range objective is to use neural networks to automate the alignment and operation of optical measurement systems in remote, harsh, or dangerous aerospace environments. This work also shows that when neural networks are trained by a human operator, training sets should be recorded, training should be executed, and testing should be done in a manner that does not depend on intellectual judgments of the human operator.

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.

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.

In vivo monitoring of glial scar proliferation on chronically implanted neural electrodes by fiber optical coherence tomography

PubMed Central

Xie, Yijing; Martini, Nadja; Hassler, Christina; Kirch, Robert D.; Stieglitz, Thomas; Seifert, Andreas; Hofmann, Ulrich G.

2014-01-01

In neural prosthetics and stereotactic neurosurgery, intracortical electrodes are often utilized for delivering therapeutic electrical pulses, and recording neural electrophysiological signals. Unfortunately, neuroinflammation impairs the neuron-electrode-interface by developing a compact glial encapsulation around the implants in long term. At present, analyzing this immune reaction is only feasible with post-mortem histology; currently no means for specific in vivo monitoring exist and most applicable imaging modalities can not provide information in deep brain regions. Optical coherence tomography (OCT) is a well established imaging modality for in vivo studies, providing cellular resolution and up to 1.2 mm imaging depth in brain tissue. A fiber based spectral domain OCT was shown to be capable of minimally invasive brain imaging. In the present study, we propose to use a fiber based spectral domain OCT to monitor the progression of the tissue's immune response through scar encapsulation progress in a rat animal model. A fine fiber catheter was implanted in rat brain together with a flexible polyimide microelectrode in sight both of which acts as a foreign body and induces the brain tissue immune reaction. OCT signals were collected from animals up to 12 weeks after implantation and thus gliotic scarring in vivo monitored for that time. Preliminary data showed a significant enhancement of the OCT backscattering signal during the first 3 weeks after implantation, and increased attenuation factor of the sampled tissue due to the glial scar formation. PMID:25191264

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.

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.

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 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.

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.

EDITORIAL: Special issue on optical neural engineering: advances in optical stimulation technology Special issue on optical neural engineering: advances in optical stimulation technology

NASA Astrophysics Data System (ADS)

Shoham, Shy; Deisseroth, Karl

2010-08-01

Neural engineering, itself an 'emerging interdisciplinary research area' [1] has undergone a sea change over the past few years with the emergence of exciting new optical technologies for monitoring, stimulating, inhibiting and, more generally, modulating neural activity. To a large extent, this change is driven by the realization of the promise and complementary strengths that emerging photo-stimulation tools offer to add to the neural engineer's toolbox, which has been almost exclusively based on electrical stimulation technologies. Notably, photo-stimulation is non-contact, can in some cases be genetically targeted to specific cell populations, can achieve high spatial specificity (cellular or even sub-cellular) in two or three dimensions, and opens up the possibility of large-scale spatial-temporal patterned stimulation. It also offers a seamless solution to the problem of cross-talk generated by simultaneous electrical stimulation and recording. As in other biomedical optics phenomena [2], photo-stimulation includes multiple possible modes of interaction between light and the target neurons, including a variety of photo-physical and photo-bio-chemical effects with various intrinsic components or exogenous 'sensitizers' which can be loaded into the tissue or genetically expressed. Early isolated reports of neural excitation with light date back to the late 19th century [3] and to Arvanitaki and Chalazonitis' work five decades ago [4]; however, the mechanism by which these and other direct photo-stimulation, inhibition and modulation events [5-7] took place is yet unclear, as is their short- and long-term safety profile. Photo-chemical photolysis of covalently 'caged' neurotransmitters [8, 9] has been widely used in cellular neuroscience research for three decades, including for exciting or inhibiting neural activity, and for mapping neural circuits. Technological developments now allow neurotransmitters to be uncaged with exquisite spatial specificity (down to a single spine, with two-photon uncaging) and in rapid, flexible spatial-temporal patterns [10-14]. Nevertheless, current technology generally requires damaging doses of UV or violet illumination and the continuous re-introduction of the caged compound, which, despite interest, makes for a difficult transition beyond in vitro preparations. Thus, the tremendous progress in the in vivo application of photo-stimulation tools over the past five years has been largely facilitated by two 'exciting' new photo-stimulation technologies: photo-biological stimulation of a rapidly increasing arsenal of light-sensitive ion channels and pumps ('optogenetic' probes[15-18]) and direct photo-thermal stimulation of neural tissue with an IR laser [19-21]. The Journal of Neural Engineering has dedicated a special section in this issue to highlight advances in optical stimulation technology, which includes original peer-reviewed contributions dealing with the design of modern optical systems for spatial-temporal control of optical excitation patterns and with the biophysics of neural-thermal interaction mediated by electromagnetic waves. The paper by Nikolenko, Peterka and Yuste [22] presents a compact design of a microscope-photo-stimulator based on a transmissive phase-modulating spatial-light modulator (SLM). Computer-generated holographic photo-stimulation using SLMs [12-14, 23] allows the efficient parallel projection of intense sparse patterns of light, and the welcome development of compact, user-friendly systems will likely reduce the barrier to its widespread adoption. The paper by Losavio et al [24] presents the design and functional characteristics of their acousto-optical deflector (AOD) systems for studying spatial-temporal dendritic integration in single neurons in vitro. Both single-photon (UV) and two-photon (femtosecond pulsed IR) AOD uncaging systems are described in detail. The paper presents an excellent overview of the current state of the art and limitations of this technology, which is increasingly being applied for both photo- stimulation and imaging [25, 26]. Finally, the paper by Pikov et al [27] studies the modulatory biophysical effects exerted by low power millimeter waves on neuronal excitability and membrane properties of cortical pyramidal neurons in vitro. These extensive neuro-modulatory effects seem to include a thermal component (related to the photo-thermal effects observed under laser illumination [28]) as well as a more specific effect exerted by these lower frequency (sub-THz) electromagnetic waves. These new contributions augment five previous manuscripts published by the journal on optical stimulation technology, which reported the development of a fiber-based system for in vivo optogenetic cortical stimulation [29], patterned stimulation systems based on computer-generated holography [23] and on arrays of micro-LEDs [30] designed for an optical retina neuroprosthetic [31], and an integrated system for optical stimulation with microelectrode array recording [32]. Without doubt, many more will quickly follow as neural engineers and neuroscientists increasingly tackle the many challenges that this exciting area poses. We can all expect to hear much more in the near future about the biophysics and implementation of photo-physical neural-interaction mechanisms, the design of new optogenetic probes and patterned-stimulation systems (including stand-alone and implantable systems), further integration of electrodes and optical components into electro-optical neurostimulation systems, and rapid progress towards multiple medical applications for alleviating neurological disabilities and improving human health. References [1] Durand D M 2006 What is neural engineering? J. Neural Eng. 4 (4) [2] Niemz M H 2007 Laser-Tissue Interactions: Fundamentals and Applications 3rd edn (Berlin: Springer) [3] Arsonval A D 1891 La fibre musculaire est directement excitable par la lumiere C. R. Soc. Biol. 43 318-20 [4] Arvanitaki A and Chalazonitis N 1961 Excitatiory and inhibitory processes initiated by light and infra-red radiations in single identifiable nerve cells Nervous Inhibition ed. E Florey (New York: Pergamon) pP 194-231 [5] Fork R L 1971 Laser stimulation of nerve cells in Aplysia Science 171 907-8 [6] Allegre G, Avrillier S and Albe-Fessard D 1994 Stimulation in the rat of a nerve fiber bundle by a short UV pulse from an excimer laser Neurosci. Lett. 180 261-4 [7] Hirase H, Nikolenko V, Goldberg J H and Yuste R 2002 Multiphoton stimulation of neurons J. Neurobiol. 51 237-47 [8] Callaway E M and Yuste R 2002 Stimulating neurons with light Curr. Opin. Neurobiol. 12 587-92 [9] Ellis-Davies G C 2007 Caged compounds: photorelease technology for control of cellular chemistry and physiology Nat. Methods 4 619-28 [10] Shoham S, O'Connor D H, Sarkisov D V and Wang S S 2005 Rapid neurotransmitter uncaging in spatially defined patterns Nat. Methods 2 837-43 [11] Nikolenko V, Poskanzer K E and Yuste R 2007 Two-photon photostimulation and imaging of neural circuits Nat. Methods 4 943-50 [12] Lutz C, Otis T S, DeSars V, Charpak S, DiGregorio D A and Emiliani V 2008 Holographic photolysis of caged neurotransmitters Nat. Methods 5 821-7 [13] Nikolenko V, Watson B O, Araya R, Woodruff A, Peterka D S and Yuste R 2008 SLM microscopy: scanless two-photon imaging and photostimulation with spatial light modulators Front. Neural Circuits 2 5 [14] Zahid M, Velez-Fort M, Papagiakoumou E, Ventalon C, Angulo M C and Emiliani V Holographic photolysis for multiple cell stimulation in mouse hippocampal slices PLoS One 5 e9431 [15] Boyden E S, Zhang F, Bamberg E, Nagel G and Deisseroth K 2005 Millisecond-timescale, genetically targeted optical control of neural activity Nat. Neurosci. 8 1263-8 [16] Zhang F, Aravanis A M, Adamantidis A, de Lecea L and Deisseroth K 2007 Circuit-breakers: optical technologies for probing neural signals and systems Nat. Rev. Neurosci. 8 577-81 [17] Gradinaru V, Zhang F, Ramakrishnan C, Mattis J, Prakash R, Diester I, Goshen I, Thompson K R, Deisseroth K 2010 Molecular and cellular approaches for diversifying and extending optogenetics Cell 141 154-65 [18] Zhang F, Gradinaru V, Adamantidis A R, Durand R, Airan R D, de Lecea L and Deisseroth K 2010 Optogenetic interrogation of neural circuits: technology for probing mammalian brain structures Nat. Protoc. 5 439-56 [19] Wells J, Kao C, Mariappan K, Albea J, Duco Jansen E, Konrad P and Mahadevan-Jansen A 2005 Optical stimulation of neural tissue in vivo Opt. Lett. 30 504-6 [20] Izzo A D, Richter C P, Jansen E D and Walsh J T Jr 2006 Laser stimulation of the auditory nerve Lasers Surg. Med. 38 745-53 [21] Richter C P, Izzo A D, Wells J, Jansen E D and Walsh J T Jr 2010 Neural stimulation with optical radiation Laser Photonics Rev. available at doi:10.1002/lpor.200900044 [22] Nikolenko V, Peterka D S and Yuste R 2010 A portable laser photostimulation and imaging microscope J. Neural Eng. 7 045001 [23] Golan L, Reutsky I, Farah N and Shoham S 2009 Design and characteristics of holographic neural photo-stimulation systems J. Neural Eng. 6 066004 [24] Losavio B E, Iyer V, Patel S and Saggau P 2010 Acousto-optical laser scanning for multi-site photo-stimulation of single neurons in vitro J. Neural Eng. 7 045002 [25] Duemani Reddy G, Kelleher K, Fink R and Saggau P 2008 Three-dimensional random access multiphoton microscopy for functional imaging of neuronal activity Nat. Neurosci. 11 713-20 [26] Grewe B F, Langer D, Kasper H, Kampa B M and Helmchen F 2010 High-speed in vivo calcium imaging reveals neuronal network activity with near-millisecond precision Nat. Methods 7 399-405 [27] Pikov V, Arakaki X, Harrington M, Fraser S E and Siegel P H 2010 Modulation of neuronal activity and plasma membrane propertiess with low-power millimeter waves in organotypic cortical slices J. Neural Eng. 7 045003 [28] Liang S et al 2009 Temperature-dependent activation of neurons by continuous near-infrared laser Cell Biochem. Biophys. 53 33-42 [29] Aravanis A M, Wang L-P, ZhangF, Meltzer L A, Mogri M Z, Schneider M B and Deisseroth K 2007 An optical neural interface: in vivo control of rodent motor cortex with integrated fiberoptic and optogenetic technology J. Neural Eng. 4 S143-56 [30] Grossman N et al 2010 Multi-site optical excitation using ChR2 and micro-LED array J. Neural Eng. 7 016004 [31] Degenaar P, Grossman N, Memon M A, Burrone J, Dawson M, Drakakis E, Neil M and Nikolic K 2009 Optobionic vision—a new genetically enhanced light on retinal prosthesis J. Neural Eng. 6 035007 [32] Zhang J et al 2009 Integrated device for optical stimulation and spatiotemporal electrical recording of neural activity in light-sensitized brain tissue J. Neural Eng. 6 055007

Neurophysiology and neural engineering: a review.

PubMed

Prochazka, Arthur

2017-08-01

Neurophysiology is the branch of physiology concerned with understanding the function of neural systems. Neural engineering (also known as neuroengineering) is a discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, enhance, or otherwise exploit the properties and functions of neural systems. In most cases neural engineering involves the development of an interface between electronic devices and living neural tissue. This review describes the origins of neural engineering, the explosive development of methods and devices commencing in the late 1950s, and the present-day devices that have resulted. The barriers to interfacing electronic devices with living neural tissues are many and varied, and consequently there have been numerous stops and starts along the way. Representative examples are discussed. None of this could have happened without a basic understanding of the relevant neurophysiology. I also consider examples of how neural engineering is repaying the debt to basic neurophysiology with new knowledge and insight. Copyright © 2017 the American Physiological Society.

Research in Optical Symbolic Tasks

DTIC Science & Technology

1989-11-29

November 1989. Specifically, we have concentrated on the following topics: complexity studies for optical neural and digital systems, architecture and...1989. Specifically, we hav, concentrated on the following topics: complexity studies for optical neural and digital systems, architecture and models for...Digital Systems 1.1 Digital Optical Parallel System Complexity Our study of digital optical system complexity has included a comparison of optical and

The structural, electronic and optical properties of Au-ZnO interface structure from the first-principles calculation

NASA Astrophysics Data System (ADS)

Huo, Jin-Rong; Li, Lu; Cheng, Hai-Xia; Wang, Xiao-Xu; Zhang, Guo-Hua; Qian, Ping

2018-03-01

The interface structure, electronic and optical properties of Au-ZnO are studied using the first-principles calculation based on density functional theory (DFT). Given the interfacial distance, bonding configurations and terminated surface, we built the optimal interface structure and calculated the electronic and optical properties of the interface. The total density of states, partial electronic density of states, electric charge density and atomic populations (Mulliken) are also displayed. The results show that the electrons converge at O atoms at the interface, leading to a stronger binding of interfaces and thereby affecting the optical properties of interface structures. In addition, we present the binding energies of different interface structures. When the interface structure of Au-ZnO gets changed, furthermore, varying optical properties are exhibited.

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.

Feasibility study for future implantable neural-silicon interface devices.

PubMed

Al-Armaghany, Allann; Yu, Bo; Mak, Terrence; Tong, Kin-Fai; Sun, Yihe

2011-01-01

The emerging neural-silicon interface devices bridge nerve systems with artificial systems and play a key role in neuro-prostheses and neuro-rehabilitation applications. Integrating neural signal collection, processing and transmission on a single device will make clinical applications more practical and feasible. This paper focuses on the wireless antenna part and real-time neural signal analysis part of implantable brain-machine interface (BMI) devices. We propose to use millimeter-wave for wireless connections between different areas of a brain. Various antenna, including microstrip patch, monopole antenna and substrate integrated waveguide antenna are considered for the intra-cortical proximity communication. A Hebbian eigenfilter based method is proposed for multi-channel neuronal spike sorting. Folding and parallel design techniques are employed to explore various structures and make a trade-off between area and power consumption. Field programmable logic arrays (FPGAs) are used to evaluate various structures.

Neural nets for aligning optical components in harsh environments: Beam smoothing spatial filter as an example

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Krasowski, Michael J.

1991-01-01

The goal is to develop an approach to automating the alignment and adjustment of optical measurement, visualization, inspection, and control systems. Classical controls, expert systems, and neural networks are three approaches to automating the alignment of an optical system. Neural networks were chosen for this project and the judgements that led to this decision are presented. Neural networks were used to automate the alignment of the ubiquitous laser-beam-smoothing spatial filter. The results and future plans of the project are presented.

Optical interconnections and networks; Proceedings of the Meeting, The Hague, Netherlands, Mar. 14, 15, 1990

NASA Technical Reports Server (NTRS)

Bartelt, Hartmut (Editor)

1990-01-01

The conference presents papers on interconnections, clock distribution, neural networks, and components and materials. Particular attention is given to a comparison of optical and electrical data interconnections at the board and backplane levels, a wafer-level optical interconnection network layout, an analysis and simulation of photonic switch networks, and the integration of picosecond GaAs photoconductive devices with silicon circuits for optical clocking and interconnects. Consideration is also given to the optical implementation of neural networks, invariance in an optoelectronic implementation of neural networks, and the recording of reversible patterns in polymer lightguides.

Electro-Optic Computing Architectures. Volume I

DTIC Science & Technology

1998-02-01

The objective of the Electro - Optic Computing Architecture (EOCA) program was to develop multi-function electro - optic interfaces and optical...interconnect units to enhance the performance of parallel processor systems and form the building blocks for future electro - optic computing architectures...Specifically, three multi-function interface modules were targeted for development - an Electro - Optic Interface (EOI), an Optical Interconnection Unit (OW

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.

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.

SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Optical neural networks based on holographic correlators

NASA Astrophysics Data System (ADS)

Sokolov, V. K.; Shubnikov, E. I.

1995-10-01

The three most important models of neural networks — a bidirectional associative memory, Hopfield networks, and adaptive resonance networks — are used as examples to show that a holographic correlator has its place in the neural computing paradigm.

Remote sensing of nutrient deficiency in Lactuca sativa using neural networks for terrestrial and advanced life support applications

NASA Astrophysics Data System (ADS)

Sears, Edie Seldon

2000-12-01

A remote sensing study using reflectance and fluorescence spectra of hydroponically grown Lactuca sativa (lettuce) canopies was conducted. An optical receiver was designed and constructed to interface with a commercial fiber optic spectrometer for data acquisition. Optical parameters were varied to determine effects of field of view and distance to target on vegetation stress assessment over the test plant growth cycle. Feedforward backpropagation neural networks (NN) were implemented to predict the presence of canopy stress. Effects of spatial and spectral resolutions on stress predictions of the neural network were also examined. Visual inspection and fresh mass values failed to differentiate among controls, plants cultivated with 25% of the recommended concentration of phosphorous (P), and those cultivated with 25% nitrogen (N) based on fresh mass and visual inspection. The NN's were trained on input vectors created using reflectance and test day, fluorescence and test day, and reflectance, fluorescence, and test day. Four networks were created representing four levels of spectral resolution: 100-nm NN, 10-nm NN, 1-nm NN, and 0.1-nm NN. The 10-nm resolution was found to be sufficient for classifying extreme nitrogen deficiency in freestanding hydroponic lettuce. As a result of leaf angle and canopy structure broadband scattering intensity in the 700-nm to 1000-nm range was found to be the most useful portion of the spectrum in this study. More subtle effects of "greenness" and fluorescence emission were believed to be obscured by canopy structure and leaf orientation. As field of view was not as found to be as significant as originally believed, systems implementing higher repetitions over more uniformly oriented, i.e. smaller, flatter, target areas would provide for more discernible neural network input vectors. It is believed that this technique holds considerable promise for early detection of extreme nitrogen deficiency. Further research is recommended using stereoscopic digital cameras to quantify leaf area index, leaf shape, and leaf orientation as well as reflectance. Given this additional information fluorescence emission may also prove a more useful biological assay of freestanding vegetation.

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

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.

Electro-Optic Computing Architectures: Volume II. Components and System Design and Analysis

DTIC Science & Technology

1998-02-01

The objective of the Electro - Optic Computing Architecture (EOCA) program was to develop multi-function electro - optic interfaces and optical...interconnect units to enhance the performance of parallel processor systems and form the building blocks for future electro - optic computing architectures...Specifically, three multi-function interface modules were targeted for development - an Electro - Optic Interface (EOI), an Optical Interconnection Unit

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.

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.

Implantable neurotechnologies: bidirectional neural interfaces--applications and VLSI circuit implementations.

PubMed

Greenwald, Elliot; Masters, Matthew R; Thakor, Nitish V

2016-01-01

A bidirectional neural interface is a device that transfers information into and out of the nervous system. This class of devices has potential to improve treatment and therapy in several patient populations. Progress in very large-scale integration has advanced the design of complex integrated circuits. System-on-chip devices are capable of recording neural electrical activity and altering natural activity with electrical stimulation. Often, these devices include wireless powering and telemetry functions. This review presents the state of the art of bidirectional circuits as applied to neuroprosthetic, neurorepair, and neurotherapeutic systems.

Bidirectional Neural Interfaces

PubMed Central

Masters, Matthew R.; Thakor, Nitish V.

2016-01-01

A bidirectional neural interface is a device that transfers information into and out of the nervous system. This class of devices has potential to improve treatment and therapy in several patient populations. Progress in very-large-scale integration (VLSI) has advanced the design of complex integrated circuits. System-on-chip (SoC) devices are capable of recording neural electrical activity and altering natural activity with electrical stimulation. Often, these devices include wireless powering and telemetry functions. This review presents the state of the art of bidirectional circuits as applied to neuroprosthetic, neurorepair, and neurotherapeutic systems. PMID:26753776

Reconfigurable visible nanophotonic switch for optogenetic applications (Conference Presentation)

NASA Astrophysics Data System (ADS)

Mohanty, Aseema; Li, Qian; Tadayon, Mohammad Amin; Bhatt, Gaurang R.; Cardenas, Jaime; Miller, Steven A.; Kepecs, Adam; Lipson, Michal

2017-02-01

High spatiotemporal resolution deep-brain optical excitation for optogenetics would enable activation of specific neural populations and in-depth study of neural circuits. Conventionally, a single fiber is used to flood light into a large area of the brain with limited resolution. The scalability of silicon photonics could enable neural excitation over large areas with single-cell resolution similar to electrical probes. However, active control of these optical circuits has yet to be demonstrated for optogenetics. Here we demonstrate the first active integrated optical switch for neural excitation at 473 nm, enabling control of multiple beams for deep-brain neural stimulation. Using a silicon nitride waveguide platform, we develop a cascaded Mach-Zehnder interferometer (MZI) network located outside the brain to direct light to 8 different grating emitters located at the tip of the neural probe. We use integrated platinum microheaters to induce a local thermo-optic phase shift in the MZI to control the switch output. We measure an ON/OFF extinction ratio of >8dB for a single switch and a switching speed of 20 microseconds. We characterize the optical output of the switch by imaging its excitation of fluorescent dye. Finally, we demonstrate in vivo single-neuron optical activation from different grating emitters using a fully packaged device inserted into a mouse brain. Directly activated neurons showed robust spike firing activities with low first-spike latency and small jitter. Active switching on a nanophotonic platform is necessary for eventually controlling highly-multiplexed reconfigurable optical circuits, enabling high-resolution optical stimulation in deep-brain regions.

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.

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

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.

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.

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.

Optical imaging of neural and hemodynamic brain activity

NASA Astrophysics Data System (ADS)

Schei, Jennifer Lynn

Optical imaging technologies can be used to record neural and hemodynamic activity. Neural activity elicits physiological changes that alter the optical tissue properties. Specifically, changes in polarized light are concomitant with neural depolarization. We measured polarization changes from an isolated lobster nerve during action potential propagation using both reflected and transmitted light. In transmission mode, polarization changes were largest throughout the center of the nerve, suggesting that most of the optical signal arose from the inner nerve bundle. In reflection mode, polarization changes were largest near the edges, suggesting that most of the optical signal arose from the outer sheath. To overcome irregular cell orientation found in the brain, we measured polarization changes from a nerve tied in a knot. Our results show that neural activation produces polarization changes that can be imaged even without regular cell orientations. Neural activation expends energy resources and elicits metabolic delivery through blood vessel dilation, increasing blood flow and volume. We used spectroscopic imaging techniques combined with electrophysiological measurements to record evoked neural and hemodynamic responses from the auditory cortex of the rat. By using implantable optics, we measured responses across natural wake and sleep states, as well as responses following different amounts of sleep deprivation. During quiet sleep, evoked metabolic responses were larger compared to wake, perhaps because blood vessels were more compliant. When animals were sleep deprived, evoked hemodynamic responses were smaller following longer periods of deprivation. These results suggest that prolonged neural activity through sleep deprivation may diminish vascular compliance as indicated by the blunted vascular response. Subsequent sleep may allow vessels to relax, restoring their ability to deliver blood. These results also suggest that severe sleep deprivation or chronic sleep disturbances could push the vasculature to critical limits, leading to metabolic deficit and the potential for tissue trauma.

In vivo optical modulation of neural signals using monolithically integrated two-dimensional neural probe arrays

PubMed Central

Son, Yoojin; Jenny Lee, Hyunjoo; Kim, Jeongyeon; Shin, Hyogeun; Choi, Nakwon; Justin Lee, C.; Yoon, Eui-Sung; Yoon, Euisik; Wise, Kensall D.; Geun Kim, Tae; Cho, Il-Joo

2015-01-01

Integration of stimulation modalities (e.g. electrical, optical, and chemical) on a large array of neural probes can enable an investigation of important underlying mechanisms of brain disorders that is not possible through neural recordings alone. Furthermore, it is important to achieve this integration of multiple functionalities in a compact structure to utilize a large number of the mouse models. Here we present a successful optical modulation of in vivo neural signals of a transgenic mouse through our compact 2D MEMS neural array (optrodes). Using a novel fabrication method that embeds a lower cladding layer in a silicon substrate, we achieved a thin silicon 2D optrode array that is capable of delivering light to multiple sites using SU-8 as a waveguide core. Without additional modification to the microelectrodes, the measured impedance of the multiple microelectrodes was below 1 MΩ at 1 kHz. In addition, with a low background noise level (±25 μV), neural spikes from different individual neurons were recorded on each microelectrode. Lastly, we successfully used our optrodes to modulate the neural activity of a transgenic mouse through optical stimulation. These results demonstrate the functionality of the 2D optrode array and its potential as a next-generation tool for optogenetic applications. PMID:26494437

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

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

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

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.

Neural Organization of the Optic Lobe Changes Steadily from Late Embryonic Stage to Adulthood in Cuttlefish Sepia pharaonis

PubMed Central

Liu, Yung-Chieh; Liu, Tsung-Han; Su, Chia-Hao; Chiao, Chuan-Chin

2017-01-01

The optic lobe is the largest structure in the cuttlefish brain. While the general morphology of the optic lobe in adult cuttlefish has been well described, the 3D structure and ontogenetic development of its neural organization have not been characterized. To correlate observed behavioral changes within the brain structure along the development of this animal, optic lobes from the late embryonic stage to adulthood were examined systematically in the present study. The MRI scan revealed that the so called “cell islands” in the medulla of the cephalopod's optic lobe (Young, 1962, 1974) are in fact a contiguous tree-like structure. Quantification of the neural organizational development of optic lobes showed that structural features of the cortex and radial column zone were established earlier than those of the tangential zone during embryonic and post-hatching stages. Within the cell islands, the density of nuclei was decreased while the size of nuclei was increased during the development. Furthermore, the visual processing area in the optic lobe showed a significant variation in lateralization during embryonic and juvenile stages. Our observation of a continuous increase in neural fibers and nucleus size in the tangential zone of the optic lobe from late embryonic stage to adulthood indicates that the neural organization of the optic lobe is modified along the development of cuttlefish. These findings thus support that the ontogenetic change of the optic lobe is responsible for their continuously increased complexity in body patterning and visuomotor behaviors. PMID:28798695

Optical implementation of a feature-based neural network with application to automatic target recognition

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1993-01-01

An optical neural network based on the neocognitron paradigm is introduced. A novel aspect of the architecture design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by feeding back the ouput of the feature correlator interatively to the input spatial light modulator and by updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved. A detailed system description is provided. Experimental demonstrations of a two-layer neural network for space-object discrimination is also presented.

Automatic target recognition using a feature-based optical neural network

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1992-01-01

An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.

Technologies for imaging neural activity in large volumes

PubMed Central

Ji, Na; Freeman, Jeremy; Smith, Spencer L.

2017-01-01

Neural circuitry has evolved to form distributed networks that act dynamically across large volumes. Collecting data from individual planes, conventional microscopy cannot sample circuitry across large volumes at the temporal resolution relevant to neural circuit function and behaviors. Here, we review emerging technologies for rapid volume imaging of neural circuitry. We focus on two critical challenges: the inertia of optical systems, which limits image speed, and aberrations, which restrict the image volume. Optical sampling time must be long enough to ensure high-fidelity measurements, but optimized sampling strategies and point spread function engineering can facilitate rapid volume imaging of neural activity within this constraint. We also discuss new computational strategies for the processing and analysis of volume imaging data of increasing size and complexity. Together, optical and computational advances are providing a broader view of neural circuit dynamics, and help elucidate how brain regions work in concert to support behavior. PMID:27571194

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

Diagnostic apparatus and method for use in the alignment of one or more laser means onto a fiber optics interface

DOEpatents

Johnson, Steve A.; Shannon, Robert R.

1987-01-01

Diagnostic apparatus for use in determining the proper alignment of a plurality of laser beams onto a fiber optics interface is disclosed. The apparatus includes a lens assembly which serves two functions, first to focus a plurality of laser beams onto the fiber optics interface, and secondly to reflect and image the interface using scattered light to a monitor means. The monitor means permits indirect observation of the alignment or focusing of the laser beams onto the fiber optics interface.

Diagnostic apparatus and method for use in the alignment of one or more laser means onto a fiber optics interface

DOEpatents

Johnson, S.A.; Shannon, R.R.

1985-01-18

Diagnostic apparatus for use in determining the proper alignment of a plurality of laser beams onto a fiber optics interface is disclosed. The apparatus includes a lens assembly which serves two functions, first to focus a plurality of laser beams onto the fiber optics interface, and secondly to reflect and image the interface using scattered light to a monitor means. The monitor means permits indirect observation of the alignment or focusing of the laser beams onto the fiber optics interface.

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.

Spatio-Temporal Neural Networks for Vision, Reasoning and Rapid Decision Making

DTIC Science & Technology

1994-08-31

something that is obviously not pattern for long-term knowledge base (LTKB) facts. As a matter possiblc in common neural networks (as units in a...Conferences on Neural Davis, P. (19W0) Application of op~tical chaos to temporal pattern search in a Networks . Piscataway, NJ. [SC] nonlinear optical...Science Institute PROJECT TITLE: Spatio-temporal Neural Networks for Vision, Reasoning and Rapid Decision Making (N00014-93-1-1149) Number of ONR

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.

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.

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.

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.

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.

An Implantable Neural Sensing Microsystem with Fiber-Optic Data Transmission and Power Delivery

PubMed Central

Park, Sunmee; Borton, David A.; Kang, Mingyu; Nurmikko, Arto V.; Song, Yoon-Kyu

2013-01-01

We have developed a prototype cortical neural sensing microsystem for brain implantable neuroengineering applications. Its key feature is that both the transmission of broadband, multichannel neural data and power required for the embedded microelectronics are provided by optical fiber access. The fiber-optic system is aimed at enabling neural recording from rodents and primates by converting cortical signals to a digital stream of infrared light pulses. In the full microsystem whose performance is summarized in this paper, an analog-to-digital converter and a low power digital controller IC have been integrated with a low threshold, semiconductor laser to extract the digitized neural signals optically from the implantable unit. The microsystem also acquires electrical power and synchronization clocks via optical fibers from an external laser by using a highly efficient photovoltaic cell on board. The implantable unit employs a flexible polymer substrate to integrate analog and digital microelectronics and on-chip optoelectronic components, while adapting to the anatomical and physiological constraints of the environment. A low power analog CMOS chip, which includes preamplifier and multiplexing circuitry, is directly flip-chip bonded to the microelectrode array to form the cortical neurosensor device. PMID:23666130

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.

Vacuum-actuated percutaneous insertion/implantation tool for flexible neural probes and interfaces

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

Sheth, Heeral; Bennett, William J.; Pannu, Satinderpall S.

A flexible device insertion tool including an elongated stiffener with one or more suction ports, and a vacuum connector for interfacing the stiffener to a vacuum source, for attaching the flexible device such as a flexible neural probe to the stiffener during insertion by a suction force exerted through the suction ports to, and to release the flexible device by removing the suction force.

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.

Multimodal Navigation in Endoscopic Transsphenoidal Resection of Pituitary Tumors Using Image-Based Vascular and Cranial Nerve Segmentation: A Prospective Validation Study.

PubMed

Dolati, Parviz; Eichberg, Daniel; Golby, Alexandra; Zamani, Amir; Laws, Edward

2016-11-01

Transsphenoidal surgery (TSS) is the most common approach for the treatment of pituitary tumors. However, misdirection, vascular damage, intraoperative cerebrospinal fluid leakage, and optic nerve injuries are all well-known complications, and the risk of adverse events is more likely in less-experienced hands. This prospective study was conducted to validate the accuracy of image-based segmentation coupled with neuronavigation in localizing neurovascular structures during TSS. Twenty-five patients with a pituitary tumor underwent preoperative 3-T magnetic resonance imaging (MRI), and MRI images loaded into the navigation platform were used for segmentation and preoperative planning. After patient registration and subsequent surgical exposure, each segmented neural or vascular element was validated by manual placement of the navigation probe or Doppler probe on or as close as possible to the target. Preoperative segmentation of the internal carotid artery and cavernous sinus matched with the intraoperative endoscopic and micro-Doppler findings in all cases. Excellent correspondence between image-based segmentation and the endoscopic view was also evident at the surface of the tumor and at the tumor-normal gland interfaces. Image guidance assisted the surgeons in localizing the optic nerve and chiasm in 64% of cases. The mean accuracy of the measurements was 1.20 ± 0.21 mm. Image-based preoperative vascular and neural element segmentation, especially with 3-dimensional reconstruction, is highly informative preoperatively and potentially could assist less-experienced neurosurgeons in preventing vascular and neural injury during TSS. In addition, the accuracy found in this study is comparable to previously reported neuronavigation measurements. This preliminary study is encouraging for future prospective intraoperative validation with larger numbers of patients. Copyright © 2016 Elsevier Inc. All rights reserved.

Concurrent electrophysiology and TPM/OCT imaging of long-term implanted electrodes (Conference Presentation)

NASA Astrophysics Data System (ADS)

Hammer, Daniel X.; Gao, Yu-Rong; Ye, Meijun; Welle, Cristin G.

2017-02-01

Microelectrodes implanted in the brain cause mechanical damage to the tissue that mediate neuroinflammation and eventual encapsulation by microglia and astrocytes. Electrophysiological signals recorded from implants used in brain-computer interfaces (BCI) degrade over time, limiting their usefulness, but the precise causes and progression are not fully understood. We are investigating the dynamics of brain morphological changes and neuroinflammation with a multimodal approach to better understand the potential causes of implant failure. We performed weekly optical coherence tomography (OCT)-guided two-photon microscopy (TPM) in the region around microelectrodes inserted under a cranial window concurrent with electrophysiological recordings. Transgenic mouse cohorts studied include Thy1-YFP, Cx3cr1, and GFAP-GFP to image neurons, microglia, and astrocytes, respectively. Single-shank, 16-channel, Michigan-style microelectrodes were inserted under the window at a 15-20° angle with an insertion depth up to cortical layer 5. Single-unit and local field potential (LFP) recordings were collected for 15 minutes while the animals moved freely in their home cages. Cellular and vascular morphology were monitored using TPM and OCT at timepoints matched to the recordings. In preliminary data, we observed a decay of neural firing rates in most of the channels after implantation. The relationship between electrophysiological measures (e.g., neural firing rate, LFP power) and neural/vascular morphological measurements (e.g., cell density, glial migration, blood flow changes) will be quantified. The multimodal approach combining electrophysiology and optical imaging provides a broader picture of the multifactorial nature of the response to implanted electrodes. Understanding and accounting for the response may lead to better BCI designs and approaches.

Optical waveguides with memory effect using photochromic material for neural network

NASA Astrophysics Data System (ADS)

Tanimoto, Keisuke; Amemiya, Yoshiteru; Yokoyama, Shin

2018-04-01

An optical neural network using a waveguide with a memory effect, a photodiode, CMOS circuits and LEDs was proposed. To realize the neural network, optical waveguides with a memory effect were fabricated using a cladding layer containing the photochromic material “diarylethene”. The transmittance of green light was decreased by UV light irradiation and recovered by the passage of green light through the waveguide. It was confirmed that the transmittance versus total energy of the green light that passed through the waveguide well fit the universal exponential curve.

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 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.

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.

Optical resonators and neural networks

NASA Astrophysics Data System (ADS)

Anderson, Dana Z.

1986-08-01

It may be possible to implement neural network models using continuous field optical architectures. These devices offer the inherent parallelism of propagating waves and an information density in principle dictated by the wavelength of light and the quality of the bulk optical elements. Few components are needed to construct a relatively large equivalent network. Various associative memories based on optical resonators have been demonstrated in the literature, a ring resonator design is discussed in detail here. Information is stored in a holographic medium and recalled through a competitive processes in the gain medium supplying energy to the ring rsonator. The resonator memory is the first realized example of a neural network function implemented with this kind of architecture.

An Investigation of the Application of Artificial Neural Networks to Adaptive Optics Imaging Systems

DTIC Science & Technology

1991-12-01

neural network and the feedforward neural network studied is the single layer perceptron artificial neural network . The recurrent artificial neural network input...features are the wavefront sensor slope outputs and neighboring actuator feedback commands. The feedforward artificial neural network input

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

Flexible Organic Electronics for Use in Neural Sensing

PubMed Central

Bink, Hank; Lai, Yuming; Saudari, Sangameshwar R.; Helfer, Brian; Viventi, Jonathan; Van der Spiegel, Jan; Litt, Brian; Kagan, Cherie

2016-01-01

Recent research in brain-machine interfaces and devices to treat neurological disease indicate that important network activity exists at temporal and spatial scales beyond the resolution of existing implantable devices. High density, active electrode arrays hold great promise in enabling high-resolution interface with the brain to access and influence this network activity. Integrating flexible electronic devices directly at the neural interface can enable thousands of multiplexed electrodes to be connected using many fewer wires. Active electrode arrays have been demonstrated using flexible, inorganic silicon transistors. However, these approaches may be limited in their ability to be cost-effectively scaled to large array sizes (8×8 cm). Here we show amplifiers built using flexible organic transistors with sufficient performance for neural signal recording. We also demonstrate a pathway for a fully integrated, amplified and multiplexed electrode array built from these devices. PMID:22255558

Logarithmic r-θ mapping for hybrid optical neural network filter for multiple objects recognition within cluttered scenes

NASA Astrophysics Data System (ADS)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.; Birch, Phil M.

2009-04-01

θThe window unit in the design of the complex logarithmic r-θ mapping for hybrid optical neural network filter can allow multiple objects of the same class to be detected within the input image. Additionally, the architecture of the neural network unit of the complex logarithmic r-θ mapping for hybrid optical neural network filter becomes attractive for accommodating the recognition of multiple objects of different classes within the input image by modifying the output layer of the unit. We test the overall filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. Logarithmic r-θ mapping for hybrid optical neural network filter is shown to exhibit with a single pass over the input data simultaneously in-plane rotation, out-of-plane rotation, scale, log r-θ map translation and shift invariance, and good clutter tolerance by recognizing correctly the different objects within the cluttered scenes. We record in our results additional extracted information from the cluttered scenes about the objects' relative position, scale and in-plane rotation.

A four-port vertical-coupling optical interface based on two-dimensional grating coupler

NASA Astrophysics Data System (ADS)

Zhang, Zan; Zhang, Zanyun; Huang, Beiju; Cheng, Chuantong; Gao, Tianxi; Hu, Xiaochuan; Zhang, Lin; Chen, Hongda

2016-10-01

In this work, a fiber-to-chip optical interface with four output ports is proposed. External lights irradiate vertically from single mode fiber to the center of optical interface can be coupled into silicon photonic chips and split into four siliconon- insulator (SOI) waveguides. If the light is circular polarized, the power of light will be equally split into four ports. Meanwhile, all lights travel in the four channel will be converted into TE polarization. The optical interface is based on a two-dimensional grating coupler with carefully designed duty cycle and period. Simulation results show that the coupling efficiency of each port can reach 11.6% so that the total coupling efficiency of the interface is 46.4%. And Lights coupled into four waveguides are all converted into TE polarization. Further, the optical interface has a simple grating structure allowing for easy fabrication.

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

Architecture for fiber-optic sensors and actuators in aircraft propulsion systems

NASA Technical Reports Server (NTRS)

Glomb, W. L., Jr.

1990-01-01

This paper describes a design for fiber-optic sensing and control in advanced aircraft Electronic Engine Control (EEC). The recommended architecture is an on-engine EEC which contains electro-optic interface circuits for fiber-optic sensors. Size and weight are reduced by multiplexing arrays of functionally similar sensors on a pairs of optical fibers to common electro-optical interfaces. The architecture contains interfaces to seven sensor groups. Nine distinct fiber-optic sensor types were found to provide the sensing functions. Analysis revealed no strong discriminator (except reliability of laser diodes and remote electronics) on which to base a selection of preferred common interface type. A hardware test program is recommended to assess the relative maturity of the technologies and to determine real performance in the engine environment.

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

Ternary mixed crystal effects on interface optical phonon and electron-phonon coupling in zinc-blende GaN/AlxGa1-xN spherical quantum dots

NASA Astrophysics Data System (ADS)

Huang, Wen Deng; Chen, Guang De; Yuan, Zhao Lin; Yang, Chuang Hua; Ye, Hong Gang; Wu, Ye Long

2016-02-01

The theoretical investigations of the interface optical phonons, electron-phonon couplings and its ternary mixed effects in zinc-blende spherical quantum dots are obtained by using the dielectric continuum model and modified random-element isodisplacement model. The features of dispersion curves, electron-phonon coupling strengths, and its ternary mixed effects for interface optical phonons in a single zinc-blende GaN/AlxGa1-xN spherical quantum dot are calculated and discussed in detail. The numerical results show that there are three branches of interface optical phonons. One branch exists in low frequency region; another two branches exist in high frequency region. The interface optical phonons with small quantum number l have more important contributions to the electron-phonon interactions. It is also found that ternary mixed effects have important influences on the interface optical phonon properties in a single zinc-blende GaN/AlxGa1-xN quantum dot. With the increase of Al component, the interface optical phonon frequencies appear linear changes, and the electron-phonon coupling strengths appear non-linear changes in high frequency region. But in low frequency region, the frequencies appear non-linear changes, and the electron-phonon coupling strengths appear linear changes.

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

Optical information-processing systems and architectures II; Proceedings of the Meeting, San Diego, CA, July 9-13, 1990

NASA Astrophysics Data System (ADS)

Javidi, Bahram

The present conference discusses topics in the fields of neural networks, acoustooptic signal processing, pattern recognition, phase-only processing, nonlinear signal processing, image processing, optical computing, and optical information processing. Attention is given to the optical implementation of an inner-product neural associative memory, optoelectronic associative recall via motionless-head/parallel-readout optical disk, a compact real-time acoustooptic image correlator, a multidimensional synthetic estimation filter, and a light-efficient joint transform optical correlator. Also discussed are a high-resolution spatial light modulator, compact real-time interferometric Fourier-transform processors, a fast decorrelation algorithm for permutation arrays, the optical interconnection of optical modules, and carry-free optical binary adders.

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.

Optical neural net for classifying imaging spectrometer data

NASA Technical Reports Server (NTRS)

Barnard, Etienne; Casasent, David P.

1989-01-01

The problem of determining the composition of an unknown input mixture from its measured spectrum, given the spectra of a number of elements, is studied. The Hopfield minimization procedure was used to express the determination of the compositions as a problem suitable for solution by neural nets. A mathematical description of the problem was developed and used as a basis for a neural network solution and an optical implementation.

Limitations of opto-electronic neural networks

NASA Technical Reports Server (NTRS)

Yu, Jeffrey; Johnston, Alan; Psaltis, Demetri; Brady, David

1989-01-01

Consideration is given to the limitations of implementing neurons, weights, and connections in neural networks for electronics and optics. It is shown that the advantages of each technology are utilized when electronically fabricated neurons are included and a combination of optics and electronics are employed for the weights and connections. The relationship between the types of neural networks being constructed and the choice of technologies to implement the weights and connections is examined.

Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network.

PubMed

Yu, Zhibin; Wang, Yubo; Zheng, Bing; Zheng, Haiyong; Wang, Nan; Gu, Zhaorui

2017-01-01

Underwater inherent optical properties (IOPs) are the fundamental clues to many research fields such as marine optics, marine biology, and underwater vision. Currently, beam transmissometers and optical sensors are considered as the ideal IOPs measuring methods. But these methods are inflexible and expensive to be deployed. To overcome this problem, we aim to develop a novel measuring method using only a single underwater image with the help of deep artificial neural network. The power of artificial neural network has been proved in image processing and computer vision fields with deep learning technology. However, image-based IOPs estimation is a quite different and challenging task. Unlike the traditional applications such as image classification or localization, IOP estimation looks at the transparency of the water between the camera and the target objects to estimate multiple optical properties simultaneously. In this paper, we propose a novel Depth Aided (DA) deep neural network structure for IOPs estimation based on a single RGB image that is even noisy. The imaging depth information is considered as an aided input to help our model make better decision.

Holographic imaging and photostimulation of neural activity.

PubMed

Yang, Weijian; Yuste, Rafael

2018-06-01

Optical imaging methods are powerful tools in neuroscience as they can systematically monitor the activity of neuronal populations with high spatiotemporal resolution using calcium or voltage indicators. Moreover, caged compounds and optogenetic actuators enable to optically manipulate neural activity. Among optical methods, computer-generated holography offers an enormous flexibility to sculpt the excitation light in three-dimensions (3D), particularly when combined with two-photon light sources. By projecting holographic light patterns on the sample, the activity of multiple neurons across a 3D brain volume can be simultaneously imaged or optically manipulated with single-cell precision. This flexibility makes two-photon holographic microscopy an ideal all-optical platform to simultaneously read and write activity in neuronal populations in vivo in 3D, a critical ability to dissect the function of neural circuits. Copyright © 2018 Elsevier Ltd. All rights reserved.

A 1024-channel 6 mW/mm2 optical stimulator for in-vitro neuroscience experiments.

PubMed

Cai, Lei; Wang, Baitong; Huang, Xiuxiang; Yang, Zhi

2014-01-01

Recent optical stimulation technologies allow improved selectivity and have been widely used in neuroscience research. This paper presents an optical stimulator based on high power LEDs. It has 1024 channels and can produce flexible stimulation patterns in each frame, refreshed at above 20 Hz. To increase the light intensity, each LED has an optical package that directs the light into a small angle. To ensure the light of each LED can reach the lens, the LEDs have been specially placed and oriented to the lens. With these efforts, the achieved power efficiency (defined as the mount of LED light power passing through the lens divided by the LED total power consumption) is 5 × 10(-5). In our current prototype, an individual LED unit can source 60 mW electrical power, where the induced irradiance on neural tissues is 6 mW/mm(2) integrating from 460 nm to 480 nm. The light spot is tunable in size from 18 μm to 40 μm with an extra 5-10 μm separation for isolating two adjacent spots. Through both bench-top measurement and finite element simulation, we found the cross channel interference is below 10%. A customized software interface has been developed to control and program the stimulator operation.

High-speed all-optical DNA local sequence alignment based on a three-dimensional artificial neural network.

PubMed

Maleki, Ehsan; Babashah, Hossein; Koohi, Somayyeh; Kavehvash, Zahra

2017-07-01

This paper presents an optical processing approach for exploring a large number of genome sequences. Specifically, we propose an optical correlator for global alignment and an extended moiré matching technique for local analysis of spatially coded DNA, whose output is fed to a novel three-dimensional artificial neural network for local DNA alignment. All-optical implementation of the proposed 3D artificial neural network is developed and its accuracy is verified in Zemax. Thanks to its parallel processing capability, the proposed structure performs local alignment of 4 million sequences of 150 base pairs in a few seconds, which is much faster than its electrical counterparts, such as the basic local alignment search tool.

High-performance parallel interface to synchronous optical network gateway

DOEpatents

St. John, Wallace B.; DuBois, David H.

1996-01-01

A system of sending and receiving gateways interconnects high speed data interfaces, e.g., HIPPI interfaces, through fiber optic links, e.g., a SONET network. An electronic stripe distributor distributes bytes of data from a first interface at the sending gateway onto parallel fiber optics of the fiber optic link to form transmitted data. An electronic stripe collector receives the transmitted data on the parallel fiber optics and reforms the data into a format effective for input to a second interface at the receiving gateway. Preferably, an error correcting syndrome is constructed at the sending gateway and sent with a data frame so that transmission errors can be detected and corrected in a real-time basis. Since the high speed data interface operates faster than any of the fiber optic links the transmission rate must be adapted to match the available number of fiber optic links so the sending and receiving gateways monitor the availability of fiber links and adjust the data throughput accordingly. In another aspect, the receiving gateway must have sufficient available buffer capacity to accept an incoming data frame. A credit-based flow control system provides for continuously updating the sending gateway on the available buffer capacity at the receiving gateway.

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.

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.

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

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.

Automated target recognition and tracking using an optical pattern recognition neural network

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1991-01-01

The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.

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

Classification of Acousto-Optic Correlation Signatures of Spread Spectrum Signals Using Artificial Neural Networks

DTIC Science & Technology

1989-12-01

Ohio ’aPw iorlipuab muo i 0I2, AFIT/GE/ENG/89D-10 CLASSIFICATION OF ACOUSTO - OPTIC CORRELATION SIGNATURES OF SPREAD SPECTRUM SIGNALS USING ARTIFICIAL...ENG/89D- 10 CLASSIFICATION OF ACOUSTO - OPTIC CORRELATION SIGNATURES OF SPREAD SPECTRUM SIGNALS USING ARTIFICIAL NEURAL NETWORKS THESIS John W. DeBerry...Captain, USAF AFIT/GE/ENG/89D- 10 Approved for public release; distribution unlimited. AFIT/GE/ENG/89D-10 CLASSIFICATION OF ACOUSTO - OPTIC CORRELATION

Neural network post-processing of grayscale optical correlator

NASA Technical Reports Server (NTRS)

Lu, Thomas T; Hughlett, Casey L.; Zhoua, Hanying; Chao, Tien-Hsin; Hanan, Jay C.

2005-01-01

In this paper we present the use of a radial basis function neural network (RBFNN) as a post-processor to assist the optical correlator to identify the objects and to reject false alarms. Image plane features near the correlation peaks are extracted and fed to the neural network for analysis. The approach is capable of handling large number of object variations and filter sets. Preliminary experimental results are presented and the performance is analyzed.

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.

Optical encryption interface

NASA Technical Reports Server (NTRS)

Jackson, Deborah J. (Inventor)

1998-01-01

An analog optical encryption system based on phase scrambling of two-dimensional optical images and holographic transformation for achieving large encryption keys and high encryption speed. An enciphering interface uses a spatial light modulator for converting a digital data stream into a two dimensional optical image. The optical image is further transformed into a hologram with a random phase distribution. The hologram is converted into digital form for transmission over a shared information channel. A respective deciphering interface at a receiver reverses the encrypting process by using a phase conjugate reconstruction of the phase scrambled hologram.

Optical nano-biosensing interface via nucleic acid amplification strategy: construction and application.

PubMed

Zhou, Hong; Liu, Jing; Xu, Jing-Juan; Zhang, Shu-Sheng; Chen, Hong-Yuan

2018-03-21

Modern optical detection technology plays a critical role in current clinical detection due to its high sensitivity and accuracy. However, higher requirements such as extremely high detection sensitivity have been put forward due to the clinical needs for the early finding and diagnosing of malignant tumors which are significant for tumor therapy. The technology of isothermal amplification with nucleic acids opens up avenues for meeting this requirement. Recent reports have shown that a nucleic acid amplification-assisted modern optical sensing interface has achieved satisfactory sensitivity and accuracy, high speed and specificity. Compared with isothermal amplification technology designed to work completely in a solution system, solid biosensing interfaces demonstrated better performances in stability and sensitivity due to their ease of separation from the reaction mixture and the better signal transduction on these optical nano-biosensing interfaces. Also the flexibility and designability during the construction of these nano-biosensing interfaces provided a promising research topic for the ultrasensitive detection of cancer diseases. In this review, we describe the construction of the burgeoning number of optical nano-biosensing interfaces assisted by a nucleic acid amplification strategy, and provide insightful views on: (1) approaches to the smart fabrication of an optical nano-biosensing interface, (2) biosensing mechanisms via the nucleic acid amplification method, (3) the newest strategies and future perspectives.

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.

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.

Optical mass memory system (AMM-13). AMM/DBMS interface control document

NASA Technical Reports Server (NTRS)

Bailey, G. A.

1980-01-01

The baseline for external interfaces of a 10 to the 13th power bit, optical archival mass memory system (AMM-13) is established. The types of interfaces addressed include data transfer; AMM-13, Data Base Management System, NASA End-to-End Data System computer interconnect; data/control input and output interfaces; test input data source; file management; and facilities interface.

Optical determination of material abundances by using neural networks for the derivation of spectral filters

NASA Astrophysics Data System (ADS)

Krippner, Wolfgang; Wagner, Felix; Bauer, Sebastian; Puente León, Fernando

2017-06-01

Using appropriately designed spectral filters allows to optically determine material abundances. While an infinite number of possibilities exist for determining spectral filters, we take advantage of using neural networks to derive spectral filters leading to precise estimations. To overcome some drawbacks that regularly influence the determination of material abundances using hyperspectral data, we incorporate the spectral variability of the raw materials into the training of the considered neural networks. As a main result, we successfully classify quantized material abundances optically. Thus, the main part of the high computational load, which belongs to the use of neural networks, is avoided. In addition, the derived material abundances become invariant against spatially varying illumination intensity as a remarkable benefit in comparison with spectral filters based on the Moore-Penrose pseudoinverse, for instance.

HoloHands: games console interface for controlling holographic optical manipulation

NASA Astrophysics Data System (ADS)

McDonald, C.; McPherson, M.; McDougall, C.; McGloin, D.

2012-10-01

The increased application of holographic optical manipulation techniques within the life sciences has sparked the development of accessible interfaces for control of holographic optical tweezers. Of particular interest are those that employ familiar, commercially available technologies. Here we present the use of a low cost games console interface, the Microsoft Kinect for the control of holographic optical tweezers and a study into the effect of using such a system upon the quality of trap generated.

High-performance parallel interface to synchronous optical network gateway

DOEpatents

St. John, W.B.; DuBois, D.H.

1996-12-03

Disclosed is a system of sending and receiving gateways interconnects high speed data interfaces, e.g., HIPPI interfaces, through fiber optic links, e.g., a SONET network. An electronic stripe distributor distributes bytes of data from a first interface at the sending gateway onto parallel fiber optics of the fiber optic link to form transmitted data. An electronic stripe collector receives the transmitted data on the parallel fiber optics and reforms the data into a format effective for input to a second interface at the receiving gateway. Preferably, an error correcting syndrome is constructed at the sending gateway and sent with a data frame so that transmission errors can be detected and corrected in a real-time basis. Since the high speed data interface operates faster than any of the fiber optic links the transmission rate must be adapted to match the available number of fiber optic links so the sending and receiving gateways monitor the availability of fiber links and adjust the data throughput accordingly. In another aspect, the receiving gateway must have sufficient available buffer capacity to accept an incoming data frame. A credit-based flow control system provides for continuously updating the sending gateway on the available buffer capacity at the receiving gateway. 7 figs.

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.

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.

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.

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.

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

Switchable Polymer Based Thin Film Coils as a Power Module for Wireless Neural Interfaces.

PubMed

Kim, S; Zoschke, K; Klein, M; Black, D; Buschick, K; Toepper, M; Tathireddy, P; Harrison, R; Solzbacher, F

2007-05-01

Reliable chronic operation of implantable medical devices such as the Utah Electrode Array (UEA) for neural interface requires elimination of transcutaneous wire connections for signal processing, powering and communication of the device. A wireless power source that allows integration with the UEA is therefore necessary. While (rechargeable) micro batteries as well as biological micro fuel cells are yet far from meeting the power density and lifetime requirements of an implantable neural interface device, inductive coupling between two coils is a promising approach to power such a device with highly restricted dimensions. The power receiving coils presented in this paper were designed to maximize the inductance and quality factor of the coils and microfabricated using polymer based thin film technologies. A flexible configuration of stacked thin film coils allows parallel and serial switching, thereby allowing to tune the coil's resonance frequency. The electrical properties of the fabricated coils were characterized and their power transmission performance was investigated in laboratory condition.

ZrO2 film interfaces with Si and SiO2

NASA Astrophysics Data System (ADS)

Lopez, C. M.; Suvorova, N. A.; Irene, E. A.; Suvorova, A. A.; Saunders, M.

2005-08-01

The interface formed by the thermal oxidation of sputter-deposited Zr metal onto Si(100)- and SiO2-coated Si(100) wafers was studied in situ and in real time using spectroscopic ellipsometry (SE) in the 1.5-4.5 photon energy range and mass spectrometry of recoiled ions (MSRI). SE yielded optical properties for the film and interface and MSRI yielded film and interface composition. An optical model was developed and verified using transmission electron microscopy. Interfacial reaction of the ZrO2 was observed for both substrates, with more interaction for Si substrates. Equivalent oxide thicknesses and interface trap levels were determined on capacitors with lower trap levels found on samples with a thicker SiO2 underlayer. In addition to the optical properties for the intermixed interface layer, the optical properties for Zr metal and unreacted ZrO2 are also reported.

Dynamically tunable interface states in 1D graphene-embedded photonic crystal heterostructure

NASA Astrophysics Data System (ADS)

Huang, Zhao; Li, Shuaifeng; Liu, Xin; Zhao, Degang; Ye, Lei; Zhu, Xuefeng; Zang, Jianfeng

2018-03-01

Optical interface states exhibit promising applications in nonlinear photonics, low-threshold lasing, and surface-wave assisted sensing. However, the further application of interface states in configurable optics is hindered by their limited tunability. Here, we demonstrate a new approach to generate dynamically tunable and angle-resolved interface states using graphene-embedded photonic crystal (GPC) heterostructure device. By combining the GPC structure design with in situ electric doping of graphene, a continuously tunable interface state can be obtained and its tuning range is as wide as the full bandgap. Moreover, the exhibited tunable interface states offer a possibility to study the correspondence between space and time characteristics of light, which is beyond normal incident conditions. Our strategy provides a new way to design configurable devices with tunable optical states for various advanced optical applications such as beam splitter and dynamically tunable laser.

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.

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.

Optical measurement of interface movements of liquid metal excited by a pneumatic shaker

NASA Astrophysics Data System (ADS)

Men, Shouqiang; Zhou, Jun; Xu, Jingwen

2015-02-01

A model experiment was designed, and Faraday instabilities were generated in a plexiglass cylinder excited by a pneumatic shaker. A contacting distance meter and a single-point fiber-optic vibrometer were applied to measure the displacement/velocity of the shaker, both of the results are in good agreement with each other. Besides, the fibre-optic laser vibrometer was exploited to measure the velocity of the interface between potassium hydroxide aqueous solution and Galinstan. It shows that the fibre-optic vibrometer can be applied to measure the interface movements without Faraday instabilities, whereas there are strong scatter and the interface displacement can only be obtained qualitatively. In this case, a scanning vibrometer or a high-speed CCD camera should be used to record the interface movements.

Fluorescent fluid interface position sensor

DOEpatents

Weiss, Jonathan D.

2004-02-17

A new fluid interface position sensor has been developed, which is capable of optically determining the location of an interface between an upper fluid and a lower fluid, the upper fluid having a larger refractive index than a lower fluid. The sensor functions by measurement, of fluorescence excited by an optical pump beam which is confined within a fluorescent waveguide where that waveguide is in optical contact with the lower fluid, but escapes from the fluorescent waveguide where that waveguide is in optical contact with the upper fluid.

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.

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.

Examples of Current and Future Uses of Neural-Net Image Processing for Aerospace Applications

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2004-01-01

Feed forward artificial neural networks are very convenient for performing correlated interpolation of pairs of complex noisy data sets as well as detecting small changes in image data. Image-to-image, image-to-variable and image-to-index applications have been tested at Glenn. Early demonstration applications are summarized including image-directed alignment of optics, tomography, flow-visualization control of wind-tunnel operations and structural-model-trained neural networks. A practical application is reviewed that employs neural-net detection of structural damage from interference fringe patterns. Both sensor-based and optics-only calibration procedures are available for this technique. These accomplishments have generated the knowledge necessary to suggest some other applications for NASA and Government programs. A tomography application is discussed to support Glenn's Icing Research tomography effort. The self-regularizing capability of a neural net is shown to predict the expected performance of the tomography geometry and to augment fast data processing. Other potential applications involve the quantum technologies. It may be possible to use a neural net as an image-to-image controller of an optical tweezers being used for diagnostics of isolated nano structures. The image-to-image transformation properties also offer the potential for simulating quantum computing. Computer resources are detailed for implementing the black box calibration features of the neural nets.

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.

Resonator memories and optical novelty filters

NASA Astrophysics Data System (ADS)

Anderson, Dana Z.; Erle, Marie C.

Optical resonators having holographic elements are potential candidates for storing information that can be accessed through content addressable or associative recall. Closely related to the resonator memory is the optical novelty filter, which can detect the differences between a test object and a set of reference objects. We discuss implementations of these devices using continuous optical media such as photorefractive materials. The discussion is framed in the context of neural network models. There are both formal and qualitative similarities between the resonator memory and optical novelty filter and network models. Mode competition arises in the theory of the resonator memory, much as it does in some network models. We show that the role of the phenomena of "daydreaming" in the real-time programmable optical resonator is very much akin to the role of "unlearning" in neural network memories. The theory of programming the real-time memory for a single mode is given in detail. This leads to a discussion of the optical novelty filter. Experimental results for the resonator memory, the real-time programmable memory, and the optical tracking novelty filter are reviewed. We also point to several issues that need to be addressed in order to implement more formal models of neural networks.

Resonator Memories And Optical Novelty Filters

NASA Astrophysics Data System (ADS)

Anderson, Dana Z.; Erie, Marie C.

1987-05-01

Optical resonators having holographic elements are potential candidates for storing information that can be accessed through content-addressable or associative recall. Closely related to the resonator memory is the optical novelty filter, which can detect the differences between a test object and a set of reference objects. We discuss implementations of these devices using continuous optical media such as photorefractive ma-terials. The discussion is framed in the context of neural network models. There are both formal and qualitative similarities between the resonator memory and optical novelty filter and network models. Mode competition arises in the theory of the resonator memory, much as it does in some network models. We show that the role of the phenomena of "daydream-ing" in the real-time programmable optical resonator is very much akin to the role of "unlearning" in neural network memories. The theory of programming the real-time memory for a single mode is given in detail. This leads to a discussion of the optical novelty filter. Experimental results for the resonator memory, the real-time programmable memory, and the optical tracking novelty filter are reviewed. We also point to several issues that need to be addressed in order to implement more formal models of neural networks.

Holography and optical information processing; Proceedings of the Soviet-Chinese Joint Seminar, Bishkek, Kyrgyzstan, Sept. 21-26, 1991

NASA Astrophysics Data System (ADS)

Mikaelian, Andrei L.

Attention is given to data storage, devices, architectures, and implementations of optical memory and neural networks; holographic optical elements and computer-generated holograms; holographic display and materials; systems, pattern recognition, interferometry, and applications in optical information processing; and special measurements and devices. Topics discussed include optical immersion as a new way to increase information recording density, systems for data reading from optical disks on the basis of diffractive lenses, a new real-time optical associative memory system, an optical pattern recognition system based on a WTA model of neural networks, phase diffraction grating for the integral transforms of coherent light fields, holographic recording with operated sensitivity and stability in chalcogenide glass layers, a compact optical logic processor, a hybrid optical system for computing invariant moments of images, optical fiber holographic inteferometry, and image transmission through random media in single pass via optical phase conjugation.

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.

Closed-loop optical neural stimulation based on a 32-channel low-noise recording system with online spike sorting

NASA Astrophysics Data System (ADS)

Nguyen, T. K. T.; Navratilova, Z.; Cabral, H.; Wang, L.; Gielen, G.; Battaglia, F. P.; Bartic, C.

2014-08-01

Objective. Closed-loop operation of neuro-electronic systems is desirable for both scientific and clinical (neuroprosthesis) applications. Integrating optical stimulation with recording capability further enhances the selectivity of neural stimulation. We have developed a system enabling the local delivery of optical stimuli and the simultaneous electrical measuring of the neural activities in a closed-loop approach. Approach. The signal analysis is performed online through the implementation of a template matching algorithm. The system performance is demonstrated with the recorded data and in awake rats. Main results. Specifically, the neural activities are simultaneously recorded, detected, classified online (through spike sorting) from 32 channels, and used to trigger a light emitting diode light source using generated TTL signals. Significance. A total processing time of 8 ms is achieved, suitable for optogenetic studies of brain mechanisms online.

An optical/digital processor - Hardware and applications

NASA Technical Reports Server (NTRS)

Casasent, D.; Sterling, W. M.

1975-01-01

A real-time two-dimensional hybrid processor consisting of a coherent optical system, an optical/digital interface, and a PDP-11/15 control minicomputer is described. The input electrical-to-optical transducer is an electron-beam addressed potassium dideuterium phosphate (KD2PO4) light valve. The requirements and hardware for the output optical-to-digital interface, which is constructed from modular computer building blocks, are presented. Initial experimental results demonstrating the operation of this hybrid processor in phased-array radar data processing, synthetic-aperture image correlation, and text correlation are included. The applications chosen emphasize the role of the interface in the analysis of data from an optical processor and possible extensions to the digital feedback control of an optical processor.

Feasibility of 3D Reconstruction of Neural Morphology Using Expansion Microscopy and Barcode-Guided Agglomeration

PubMed Central

Yoon, Young-Gyu; Dai, Peilun; Wohlwend, Jeremy; Chang, Jae-Byum; Marblestone, Adam H.; Boyden, Edward S.

2017-01-01

We here introduce and study the properties, via computer simulation, of a candidate automated approach to algorithmic reconstruction of dense neural morphology, based on simulated data of the kind that would be obtained via two emerging molecular technologies—expansion microscopy (ExM) and in-situ molecular barcoding. We utilize a convolutional neural network to detect neuronal boundaries from protein-tagged plasma membrane images obtained via ExM, as well as a subsequent supervoxel-merging pipeline guided by optical readout of information-rich, cell-specific nucleic acid barcodes. We attempt to use conservative imaging and labeling parameters, with the goal of establishing a baseline case that points to the potential feasibility of optical circuit reconstruction, leaving open the possibility of higher-performance labeling technologies and algorithms. We find that, even with these conservative assumptions, an all-optical approach to dense neural morphology reconstruction may be possible via the proposed algorithmic framework. Future work should explore both the design-space of chemical labels and barcodes, as well as algorithms, to ultimately enable routine, high-performance optical circuit reconstruction. PMID:29114215

Feasibility of 3D Reconstruction of Neural Morphology Using Expansion Microscopy and Barcode-Guided Agglomeration.

PubMed

Yoon, Young-Gyu; Dai, Peilun; Wohlwend, Jeremy; Chang, Jae-Byum; Marblestone, Adam H; Boyden, Edward S

2017-01-01

We here introduce and study the properties, via computer simulation, of a candidate automated approach to algorithmic reconstruction of dense neural morphology, based on simulated data of the kind that would be obtained via two emerging molecular technologies-expansion microscopy (ExM) and in-situ molecular barcoding. We utilize a convolutional neural network to detect neuronal boundaries from protein-tagged plasma membrane images obtained via ExM, as well as a subsequent supervoxel-merging pipeline guided by optical readout of information-rich, cell-specific nucleic acid barcodes. We attempt to use conservative imaging and labeling parameters, with the goal of establishing a baseline case that points to the potential feasibility of optical circuit reconstruction, leaving open the possibility of higher-performance labeling technologies and algorithms. We find that, even with these conservative assumptions, an all-optical approach to dense neural morphology reconstruction may be possible via the proposed algorithmic framework. Future work should explore both the design-space of chemical labels and barcodes, as well as algorithms, to ultimately enable routine, high-performance optical circuit reconstruction.

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.

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.

Integration of Optical Manipulation and Electrophysiological Tools to Modulate and Record Activity in Neural Networks

NASA Astrophysics Data System (ADS)

Difato, F.; Schibalsky, L.; Benfenati, F.; Blau, A.

2011-07-01

We present an optical system that combines IR (1064 nm) holographic optical tweezers with a sub-nanosecond-pulsed UV (355 nm) laser microdissector for the optical manipulation of single neurons and entire networks both on transparent and non-transparent substrates in vitro. The phase-modulated laser beam can illuminate the sample concurrently or independently from above or below assuring compatibility with different types of microelectrode array and patch-clamp electrophysiology. By combining electrophysiological and optical tools, neural activity in response to localized stimuli or injury can be studied and quantified at sub-cellular, cellular, and network level.

General MACOS Interface for Modeling and Analysis for Controlled Optical Systems

NASA Technical Reports Server (NTRS)

Sigrist, Norbert; Basinger, Scott A.; Redding, David C.

2012-01-01

The General MACOS Interface (GMI) for Modeling and Analysis for Controlled Optical Systems (MACOS) enables the use of MATLAB as a front-end for JPL s critical optical modeling package, MACOS. MACOS is JPL s in-house optical modeling software, which has proven to be a superb tool for advanced systems engineering of optical systems. GMI, coupled with MACOS, allows for seamless interfacing with modeling tools from other disciplines to make possible integration of dynamics, structures, and thermal models with the addition of control systems for deformable optics and other actuated optics. This software package is designed as a tool for analysts to quickly and easily use MACOS without needing to be an expert at programming MACOS. The strength of MACOS is its ability to interface with various modeling/development platforms, allowing evaluation of system performance with thermal, mechanical, and optical modeling parameter variations. GMI provides an improved means for accessing selected key MACOS functionalities. The main objective of GMI is to marry the vast mathematical and graphical capabilities of MATLAB with the powerful optical analysis engine of MACOS, thereby providing a useful tool to anyone who can program in MATLAB. GMI also improves modeling efficiency by eliminating the need to write an interface function for each task/project, reducing error sources, speeding up user/modeling tasks, and making MACOS well suited for fast prototyping.

Virtual optical interfaces for the transportation industry

NASA Astrophysics Data System (ADS)

Hejmadi, Vic; Kress, Bernard

2010-04-01

We present a novel implementation of virtual optical interfaces for the transportation industry (automotive and avionics). This new implementation includes two functionalities in a single device; projection of a virtual interface and sensing of the position of the fingers on top of the virtual interface. Both functionalities are produced by diffraction of laser light. The device we are developing include both functionalities in a compact package which has no optical elements to align since all of them are pre-aligned on a single glass wafer through optical lithography. The package contains a CMOS sensor which diffractive objective lens is optimized for the projected interface color as well as for the IR finger position sensor based on structured illumination. Two versions are proposed: a version which senses the 2d position of the hand and a version which senses the hand position in 3d.

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.

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.

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.

Single neural code for blur in subjects with different interocular optical blur orientation

PubMed Central

Radhakrishnan, Aiswaryah; Sawides, Lucie; Dorronsoro, Carlos; Peli, Eli; Marcos, Susana

2015-01-01

The ability of the visual system to compensate for differences in blur orientation between eyes is not well understood. We measured the orientation of the internal blur code in both eyes of the same subject monocularly by presenting pairs of images blurred with real ocular point spread functions (PSFs) of similar blur magnitude but varying in orientations. Subjects assigned a level of confidence to their selection of the best perceived image in each pair. Using a classification-images–inspired paradigm and applying a reverse correlation technique, a classification map was obtained from the weighted averages of the PSFs, representing the internal blur code. Positive and negative neural PSFs were obtained from the classification map, representing the neural blur for best and worse perceived blur, respectively. The neural PSF was found to be highly correlated in both eyes, even for eyes with different ocular PSF orientations (rPos = 0.95; rNeg = 0.99; p < 0.001). We found that in subjects with similar and with different ocular PSF orientations between eyes, the orientation of the positive neural PSF was closer to the orientation of the ocular PSF of the eye with the better optical quality (average difference was ∼10°), while the orientation of the positive and negative neural PSFs tended to be orthogonal. These results suggest a single internal code for blur with orientation driven by the orientation of the optical blur of the eye with better optical quality. PMID:26114678

An insect-inspired model for visual binding I: learning objects and their characteristics.

PubMed

Northcutt, Brandon D; Dyhr, Jonathan P; Higgins, Charles M

2017-04-01

Visual binding is the process of associating the responses of visual interneurons in different visual submodalities all of which are responding to the same object in the visual field. Recently identified neuropils in the insect brain termed optic glomeruli reside just downstream of the optic lobes and have an internal organization that could support visual binding. Working from anatomical similarities between optic and olfactory glomeruli, we have developed a model of visual binding based on common temporal fluctuations among signals of independent visual submodalities. Here we describe and demonstrate a neural network model capable both of refining selectivity of visual information in a given visual submodality, and of associating visual signals produced by different objects in the visual field by developing inhibitory neural synaptic weights representing the visual scene. We also show that this model is consistent with initial physiological data from optic glomeruli. Further, we discuss how this neural network model may be implemented in optic glomeruli at a neuronal level.

Optical-nanofiber-based interface for single molecules

NASA Astrophysics Data System (ADS)

Skoff, Sarah M.; Papencordt, David; Schauffert, Hardy; Bayer, Bernhard C.; Rauschenbeutel, Arno

2018-04-01

Optical interfaces for quantum emitters are a prerequisite for implementing quantum networks. Here, we couple single molecules to the guided modes of an optical nanofiber. The molecules are embedded within a crystal that provides photostability and, due to the inhomogeneous broadening, a means to spectrally address single molecules. Single molecules are excited and detected solely via the nanofiber interface without the requirement of additional optical access. In this way, we realize a fully fiber-integrated system that is scalable and may become a versatile constituent for quantum hybrid systems.

Optoelectronic analogs of self-programming neural nets - Architecture and methodologies for implementing fast stochastic learning by simulated annealing

NASA Technical Reports Server (NTRS)

Farhat, Nabil H.

1987-01-01

Self-organization and learning is a distinctive feature of neural nets and processors that sets them apart from conventional approaches to signal processing. It leads to self-programmability which alleviates the problem of programming complexity in artificial neural nets. In this paper architectures for partitioning an optoelectronic analog of a neural net into distinct layers with prescribed interconnectivity pattern to enable stochastic learning by simulated annealing in the context of a Boltzmann machine are presented. Stochastic learning is of interest because of its relevance to the role of noise in biological neural nets. Practical considerations and methodologies for appreciably accelerating stochastic learning in such a multilayered net are described. These include the use of parallel optical computing of the global energy of the net, the use of fast nonvolatile programmable spatial light modulators to realize fast plasticity, optical generation of random number arrays, and an adaptive noisy thresholding scheme that also makes stochastic learning more biologically plausible. The findings reported predict optoelectronic chips that can be used in the realization of optical learning machines.

Fiber optics interface for a dye laser oscillator and method

DOEpatents

Johnson, Steve A.; Seppala, Lynn G.

1986-01-01

A dye laser oscillator in which one light beam is used to pump a continuous tream of dye within a cooperating dye chamber for producing a second, different beam is generally disclosed herein along with a specific arrangement including an optical fiber and a fiber optics interface for directing the pumping beam into the dye chamber. The specific fiber optics interface illustrated includes three cooperating lenses which together image one particular dimension of the pumping beam into the dye chamber from the output end of the optical fiber in order to insure that the dye chamber is properly illuminated by the pumping beam.

Fiber optics interface for a dye laser oscillator and method

DOEpatents

Johnson, S.A.; Seppala, L.G.

1984-06-13

A dye laser oscillator in which one light beam is used to pump a continuous stream of dye within a cooperating dye chamber for producing a second, different beam is generally disclosed herein along with a specific arrangement including an optical fiber and a fiber optics interface for directing the pumping beam into the dye chamber. The specific fiber optics interface illustrated includes three cooperating lenses which together image one particular dimension of the pumping beam into the dye chamber from the output end of the optical fiber in order to insure that the dye chamber is properly illuminated by the pumping beam.

Evaluation of insertion characteristics of less invasive Si optoneural probe with embedded optical fiber

NASA Astrophysics Data System (ADS)

Morikawa, Takumi; Harashima, Takuya; Kino, Hisashi; Fukushima, Takafumi; Tanaka, Tetsu

2017-04-01

A less invasive Si optoneural probe with an embedded optical fiber was proposed and successfully fabricated. The diameter of the optical fiber was completely controlled by hydrogen fluoride etching, and the thinned optical fiber can propagate light without any leakage. This optical fiber was embedded in a trench formed inside a probe shank, which causes less damage to tissues. In addition, it was confirmed that the optical fiber embedded in the probe shank successfully irradiated light to optically stimulate gene transfected neurons. The electrochemical impedance of the probe did not change despite the light irradiation. Furthermore, probe insertion characteristics were evaluated in detail and less invasive insertion was clearly indicated for the Si optoneural probe with the embedded optical fiber compared with conventional optical neural probes. This neural probe with the embedded optical fiber can be used as a simple and easy tool for optogenetics and brain science.

The liquid crystal light valve, an optical-to-optical interface device

NASA Technical Reports Server (NTRS)

Jacobson, A. D.; Beard, T. D.; Bleha, W. P.; Margerum, J. D.; Wong, S. Y.

1972-01-01

A photoactivated liquid crystal light valve is described as an optical-to-optical interface device (OTTO) which is designed to transfer an optical image from a noncoherent light beam to a spatially coherent beam of light, in real time. Schematics of OTTO in use, the liquid cyrstal cell, and the liquid crystal structure are presented. Sensitivity characteristics and the principles of operation are discussed.

Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems.

PubMed

González-Gutiérrez, Carlos; Santos, Jesús Daniel; Martínez-Zarzuela, Mario; Basden, Alistair G; Osborn, James; Díaz-Pernas, Francisco Javier; De Cos Juez, Francisco Javier

2017-06-02

Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named "CARMEN" are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances.

The first neural probe integrated with light source (blue laser diode) for optical stimulation and electrical recording.

PubMed

Park, HyungDal; Shin, Hyun-Joon; Cho, Il-Joo; Yoon, Eui-sung; Suh, Jun-Kyo Francis; Im, Maesoon; Yoon, Euisik; Kim, Yong-Jun; Kim, Jinseok

2011-01-01

In this paper, we report a neural probe which can selectively stimulate target neurons optically through Si wet etched mirror surface and record extracellular neural signals in iridium oxide tetrodes. Consequently, the proposed approach provides to improve directional problem and achieve at least 150/m gap distance between stimulation and recording sites by wet etched mirror surface in V-groove. Also, we developed light source, blue laser diode (OSRAM Blue Laser Diode_PL 450), integration through simple jig for one-touch butt-coupling. Furthermore, optical power and impedance of iridium oxide tetrodes were measured as 200 μW on 5 mW from LD and 206.5 k Ω at 1 kHz and we demonstrated insertion test of probe in 0.5% agarose-gel successfully. We have successfully transmitted a light of 450 nm to optical fiber through the integrated LD using by butt-coupling method.

Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems

PubMed Central

González-Gutiérrez, Carlos; Santos, Jesús Daniel; Martínez-Zarzuela, Mario; Basden, Alistair G.; Osborn, James; Díaz-Pernas, Francisco Javier; De Cos Juez, Francisco Javier

2017-01-01

Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named “CARMEN” are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances. PMID:28574426

Limitations of the commonly used simplified laterally uniform optical fiber probe-tissue interface in Monte Carlo simulations of diffuse reflectance

PubMed Central

Naglič, Peter; Pernuš, Franjo; Likar, Boštjan; Bürmen, Miran

2015-01-01

Light propagation models often simplify the interface between the optical fiber probe tip and tissue to a laterally uniform boundary with mismatched refractive indices. Such simplification neglects the precise optical properties of the commonly used probe tip materials, e.g. stainless steel or black epoxy. In this paper, we investigate the limitations of the laterally uniform probe-tissue interface in Monte Carlo simulations of diffuse reflectance. In comparison to a realistic probe-tissue interface that accounts for the layout and properties of the probe tip materials, the simplified laterally uniform interface is shown to introduce significant errors into the simulated diffuse reflectance. PMID:26504647

High-gain AlGaAs/GaAs double heterojunction Darlington phototransistors for optical neural networks

NASA Technical Reports Server (NTRS)

Kim, Jae H. (Inventor); Lin, Steven H. (Inventor)

1991-01-01

High-gain MOCVD-grown (metal-organic chemical vapor deposition) AlGaAs/GaAs/AlGaAs n-p-n double heterojunction bipolar transistors (DHBTs) and Darlington phototransistor pairs are provided for use in optical neural networks and other optoelectronic integrated circuit applications. The reduced base doping level used results in effective blockage of Zn out-diffusion, enabling a current gain of 500, higher than most previously reported values for Zn-diffused-base DHBTs. Darlington phototransitor pairs of this material can achieve a current gain of over 6000, which satisfies the gain requirement for optical neural network designs, which advantageously may employ neurons comprising the Darlington phototransistor pairs in series with a light source.

A method for optical imaging and monitoring of the excretion of fluorescent nanocomposites from the body using artificial neural networks.

PubMed

Sarmanova, Olga E; Burikov, Sergey A; Dolenko, Sergey A; Isaev, Igor V; Laptinskiy, Kirill A; Prabhakar, Neeraj; Karaman, Didem Şen; Rosenholm, Jessica M; Shenderova, Olga A; Dolenko, Tatiana A

2018-04-12

In this study, a new approach to the implementation of optical imaging of fluorescent nanoparticles in a biological medium using artificial neural networks is proposed. The studies were carried out using new synthesized nanocomposites - nanometer graphene oxides, covered by the poly(ethylene imine)-poly(ethylene glycol) copolymer and by the folic acid. We present an example of a successful solution of the problem of monitoring the removal of nanocomposites based on nGO and their components with urine using fluorescent spectroscopy and artificial neural networks. However, the proposed method is applicable for optical imaging of any fluorescent nanoparticles used as theranostic agents in biological tissue. Copyright © 2018. Published by Elsevier Inc.

Modulated error diffusion CGHs for neural nets

NASA Astrophysics Data System (ADS)

Vermeulen, Pieter J. E.; Casasent, David P.

1990-05-01

New modulated error diffusion CGHs (computer generated holograms) for optical computing are considered. Specific attention is given to their use in optical matrix-vector, associative processor, neural net and optical interconnection architectures. We consider lensless CGH systems (many CGHs use an external Fourier transform (FT) lens), the Fresnel sampling requirements, the effects of finite CGH apertures (sample and hold inputs), dot size correction (for laser recorders), and new applications for this novel encoding method (that devotes attention to quantization noise effects).

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.

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

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 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

Electro-optic architecture (EOA) for sensors and actuators in aircraft propulsion systems

NASA Technical Reports Server (NTRS)

Glomb, W. L., Jr.

1989-01-01

Results of a study to design an optimal architecture for electro-optical sensing and control in advanced aircraft and space systems are described. The propulsion full authority digital Electronic Engine Control (EEC) was the focus for the study. The recommended architecture is an on-engine EEC which contains electro-optic interface circuits for fiber-optic sensors on the engine. Size and weight are reduced by multiplexing arrays of functionally similar sensors on a pair of optical fibers to common electro-optical interfaces. The architecture contains common, multiplex interfaces to seven sensor groups: (1) self luminous sensors; (2) high temperatures; (3) low temperatures; (4) speeds and flows; (5) vibration; (6) pressures; and (7) mechanical positions. Nine distinct fiber-optic sensor types were found to provide these sensing functions: (1) continuous wave (CW) intensity modulators; (2) time division multiplexing (TDM) digital optic codeplates; (3) time division multiplexing (TDM) analog self-referenced sensors; (4) wavelength division multiplexing (WDM) digital optic code plates; (5) wavelength division multiplexing (WDM) analog self-referenced intensity modulators; (6) analog optical spectral shifters; (7) self-luminous bodies; (8) coherent optical interferometers; and (9) remote electrical sensors. The report includes the results of a trade study including engine sensor requirements, environment, the basic sensor types, and relevant evaluation criteria. These figures of merit for the candidate interface types were calculated from the data supplied by leading manufacturers of fiber-optic sensors.

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.

Al+Si Interface Optical Properties Obtained in the Si Solar Cell Configuration

DOE PAGES

Subedi, Indra; Silverman, Timothy J.; Deceglie, Michael G.; ...

2017-10-18

Al is a commonly used material for rear side metallization in commercial silicon (Si) wafer solar cells. In this study, through-the-silicon spectroscopic ellipsometry is used in a test sample to measure Al+Si interface optical properties like those in Si wafer solar cells. Two different spectroscopic ellipsometers are used for measurement of Al+Si interface optical properties over the 1128-2500 nm wavelength range. For validation, the measured interface optical properties are used in a ray tracing simulation over the 300-2500 nm wavelength range for an encapsulated Si solar cell having random pyramidal texture. The ray tracing model matches well with the measuredmore » total reflectance at normal incidence of a commercially available Si module. The Al+Si optical properties presented here enable quantitative assessment of major irradiance/current flux losses arising from reflection and parasitic absorption in encapsulated Si solar cells.« less

Al+Si Interface Optical Properties Obtained in the Si Solar Cell Configuration

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

Subedi, Indra; Silverman, Timothy J.; Deceglie, Michael G.

Al is a commonly used material for rear side metallization in commercial silicon (Si) wafer solar cells. In this study, through-the-silicon spectroscopic ellipsometry is used in a test sample to measure Al+Si interface optical properties like those in Si wafer solar cells. Two different spectroscopic ellipsometers are used for measurement of Al+Si interface optical properties over the 1128-2500 nm wavelength range. For validation, the measured interface optical properties are used in a ray tracing simulation over the 300-2500 nm wavelength range for an encapsulated Si solar cell having random pyramidal texture. The ray tracing model matches well with the measuredmore » total reflectance at normal incidence of a commercially available Si module. The Al+Si optical properties presented here enable quantitative assessment of major irradiance/current flux losses arising from reflection and parasitic absorption in encapsulated Si solar cells.« less

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.

Characterization of a 3D optrode array for infrared neural stimulation

PubMed Central

Abaya, T.V.F.; Diwekar, M.; Blair, S.; Tathireddy, P.; Rieth, L.; Clark, G.A.; Solzbacher, F.

2012-01-01

This paper characterizes the Utah Slant Optrode Array (USOA) as a means to deliver infrared light deep into tissue. An undoped crystalline silicon (100) substrate was used to fabricate 10 × 10 arrays of optrodes with rows of varying lengths from 0.5 mm to 1.5 mm on a 400-μm pitch. Light delivery from optical fibers and loss mechanisms through these Si optrodes were characterized, with the primary loss mechanisms being Fresnel reflection, coupling, radiation losses from the tapered shank and total internal reflection in the tips. Transmission at the optrode tips with different optical fiber core diameters and light in-coupling interfaces was investigated. At λ = 1.55μm, the highest optrode transmittance of 34.7%, relative to the optical fiber output power, was obtained with a 50-μm multi-mode fiber butt-coupled to the optrode through an intervening medium of index n = 1.66. Maximum power is directed into the optrodes when using fibers with core diameters of 200 μm or less. In addition, the output power varied with the optrode length/taper such that longer and less tapered optrodes exhibited higher light transmission efficiency. Output beam profiles and potential impacts on physiological tests were also examined. Future work is expected to improve USOA efficiency to greater than 64%. PMID:23024914

Characterization of a 3D optrode array for infrared neural stimulation.

PubMed

Abaya, T V F; Diwekar, M; Blair, S; Tathireddy, P; Rieth, L; Clark, G A; Solzbacher, F

2012-09-01

This paper characterizes the Utah Slant Optrode Array (USOA) as a means to deliver infrared light deep into tissue. An undoped crystalline silicon (100) substrate was used to fabricate 10 × 10 arrays of optrodes with rows of varying lengths from 0.5 mm to 1.5 mm on a 400-μm pitch. Light delivery from optical fibers and loss mechanisms through these Si optrodes were characterized, with the primary loss mechanisms being Fresnel reflection, coupling, radiation losses from the tapered shank and total internal reflection in the tips. Transmission at the optrode tips with different optical fiber core diameters and light in-coupling interfaces was investigated. At λ = 1.55μm, the highest optrode transmittance of 34.7%, relative to the optical fiber output power, was obtained with a 50-μm multi-mode fiber butt-coupled to the optrode through an intervening medium of index n = 1.66. Maximum power is directed into the optrodes when using fibers with core diameters of 200 μm or less. In addition, the output power varied with the optrode length/taper such that longer and less tapered optrodes exhibited higher light transmission efficiency. Output beam profiles and potential impacts on physiological tests were also examined. Future work is expected to improve USOA efficiency to greater than 64%.

Switch configuration for migration to optical fiber network

NASA Technical Reports Server (NTRS)

Zobrist, George W.

1993-01-01

The purpose is to investigate the migration of an Ethernet LAN segment to fiber optics. At the present time it is proposed to support a Fiber Distributed Data Interface (FDDI) backbone and to upgrade the VAX cluster to fiber optic interface. Possibly some workstations will have an FDDI interface. The remaining stations on the Ethernet LAN will be segmented. The rationale for migrating from the present Ethernet configuration to a fiber optic backbone is due to the increase in the number of workstations and the movement of applications to a windowing environment, extensive document transfers, and compute intensive applications.

Si-based optical I/O for optical memory interface

NASA Astrophysics Data System (ADS)

Ha, Kyoungho; Shin, Dongjae; Byun, Hyunil; Cho, Kwansik; Na, Kyoungwon; Ji, Hochul; Pyo, Junghyung; Hong, Seokyong; Lee, Kwanghyun; Lee, Beomseok; Shin, Yong-hwack; Kim, Junghye; Kim, Seong-gu; Joe, Insung; Suh, Sungdong; Choi, Sanghoon; Han, Sangdeok; Park, Yoondong; Choi, Hanmei; Kuh, Bongjin; Kim, Kichul; Choi, Jinwoo; Park, Sujin; Kim, Hyeunsu; Kim, Kiho; Choi, Jinyong; Lee, Hyunjoo; Yang, Sujin; Park, Sungho; Lee, Minwoo; Cho, Minchang; Kim, Saebyeol; Jeong, Taejin; Hyun, Seokhun; Cho, Cheongryong; Kim, Jeong-kyoum; Yoon, Hong-gu; Nam, Jeongsik; Kwon, Hyukjoon; Lee, Hocheol; Choi, Junghwan; Jang, Sungjin; Choi, Joosun; Chung, Chilhee

2012-01-01

Optical interconnects may provide solutions to the capacity-bandwidth trade-off of recent memory interface systems. For cost-effective optical memory interfaces, Samsung Electronics has been developing silicon photonics platforms on memory-compatible bulk-Si 300-mm wafers. The waveguide of 0.6 dB/mm propagation loss, vertical grating coupler of 2.7 dB coupling loss, modulator of 10 Gbps speed, and Ge/Si photodiode of 12.5 Gbps bandwidth have been achieved on the bulk-Si platform. 2x6.4 Gbps electrical driver circuits have been also fabricated using a CMOS process.

Neural Network for Image-to-Image Control of Optical Tweezers

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Anderson, Robert C.; Weiland, Kenneth E.; Wrbanek, Susan Y.

2004-01-01

A method is discussed for using neural networks to control optical tweezers. Neural-net outputs are combined with scaling and tiling to generate 480 by 480-pixel control patterns for a spatial light modulator (SLM). The SLM can be combined in various ways with a microscope to create movable tweezers traps with controllable profiles. The neural nets are intended to respond to scattered light from carbon and silicon carbide nanotube sensors. The nanotube sensors are to be held by the traps for manipulation and calibration. Scaling and tiling allow the 100 by 100-pixel maximum resolution of the neural-net software to be applied in stages to exploit the full 480 by 480-pixel resolution of the SLM. One of these stages is intended to create sensitive null detectors for detecting variations in the scattered light from the nanotube sensors.

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 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.

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.

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

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.

High bandwidth electro-optic technology for intersatellite optical communications

NASA Technical Reports Server (NTRS)

Krainak, Michael A.

1992-01-01

The research and development of electronic and electro-optic components for geosynchronous and low earth orbiting satellite optical high bandwidth communications at the NASA-Goddard Space Flight Center is reviewed. Intersatellite optical communications retains a strong reliance on microwave circuit technology in several areas - the microwave to optical interface, the laser transmitter modulation driver and the optical receiver. A microwave to optical interface is described requiring high bandwidth electronic downconverters and demodulators. Electrical bandwidth and current drive requirements for the laser modulation driver for three laser alternatives are discussed. Bandwidth and noise requirements are presented for optical receiver architectures.

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.

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.

Statistical characterization of the optical interaction at a supercavitating interface

NASA Astrophysics Data System (ADS)

Walters, Gage; Kane, Tim; Jefferies, Rhett; Antonelli, Lynn

2016-05-01

The optical characteristics of an air/water interface have been widely studied for natural interface formations. However, the creation and management of artificial cavities creates a complicated interaction of gas and liquid that makes optical sensing and communication through the interface challenging. A ventilated cavity can reduce friction in underwater vehicles, but the resulting bubble drastically impedes optical and acoustic communication propagation. The complicated interaction at the air/water boundary yields surface waves and turbulence that make modeling and compensating of the optical properties difficult. Our experimental approach uses a narrow laser beam to probe the surface of the interface and measure the beam deflection and lensing effects. Using a vehicle model with a cavitator in a water tunnel, a laser beam is propagated outward from the model through the boundary and projected onto a target grid. The beam projection is captured using a high-speed camera, allowing us to measure and analyze beam shape and deflection. This approach has enabled us to quantify the temporal and spatial periodic variations in the beam propagation through the cavity boundary and fluid.

Optical second harmonic generation phase measurement at interfaces of some organic layers with indium tin oxide

NASA Astrophysics Data System (ADS)

Ngah Demon, Siti Zulaikha; Miyauchi, Yoshihiro; Mizutani, Goro; Matsushima, Toshinori; Murata, Hideyuki

2014-08-01

We observed phase shift in optical second harmonic generation (SHG) from interfaces of indium tin oxide (ITO)/copper phthalocyanine (CuPc) and ITO/pentacene. Phase correction due to Fresnel factors of the sample was taken into account. The phase of SHG electric field at the ITO/pentacene interface, ϕinterface with respect to the phase of SHG of bare substrate ITO was 160°, while the interface of ITO/CuPc had a phase of 140°.

Optical implementation of neural learning algorithms based on cross-gain modulation in a semiconductor optical amplifier

NASA Astrophysics Data System (ADS)

Li, Qiang; Wang, Zhi; Le, Yansi; Sun, Chonghui; Song, Xiaojia; Wu, Chongqing

2016-10-01

Neuromorphic engineering has a wide range of applications in the fields of machine learning, pattern recognition, adaptive control, etc. Photonics, characterized by its high speed, wide bandwidth, low power consumption and massive parallelism, is an ideal way to realize ultrafast spiking neural networks (SNNs). Synaptic plasticity is believed to be critical for learning, memory and development in neural circuits. Experimental results have shown that changes of synapse are highly dependent on the relative timing of pre- and postsynaptic spikes. Synaptic plasticity in which presynaptic spikes preceding postsynaptic spikes results in strengthening, while the opposite timing results in weakening is called antisymmetric spike-timing-dependent plasticity (STDP) learning rule. And synaptic plasticity has the opposite effect under the same conditions is called antisymmetric anti-STDP learning rule. We proposed and experimentally demonstrated an optical implementation of neural learning algorithms, which can achieve both of antisymmetric STDP and anti-STDP learning rule, based on the cross-gain modulation (XGM) within a single semiconductor optical amplifier (SOA). The weight and height of the potentitation and depression window can be controlled by adjusting the injection current of the SOA, to mimic the biological antisymmetric STDP and anti-STDP learning rule more realistically. As the injection current increases, the width of depression and potentitation window decreases and height increases, due to the decreasing of recovery time and increasing of gain under a stronger injection current. Based on the demonstrated optical STDP circuit, ultrafast learning in optical SNNs can be realized.

Preface: phys. stat. sol. (b) 242/13

NASA Astrophysics Data System (ADS)

Esser, Norbert; Zahn, Dietrich R. T.

2005-11-01

Wolfgang Richter celebrated his 65th birthday on 2 January 2005. On such an occasion, usually marking retirement, achievements and breakthroughs in research are reviewed. But Wolfgang Richter is not retiring: he has accepted an offer of a professorship at the University Rome II Tor Vergata. As he explained to us with his famous smile, he plans to concentrate his future efforts even more on his true love in science - the optical diagnostics of interfaces.Wolfgang Richter has been working in the field of optical spectroscopy of solids since his PhD studies at the University of Cologne. Having finished his PhD in 1969 in the field of infrared spectroscopy he decided to reduce the probed volume by increasing the energy of probing photons: Raman spectroscopy! During his postdoctoral and Habilitation periods (1970-1979) at Pennsylvania State University, Max-Planck-Institut für Festkörperforschung, and RWTH Aachen, he pursued his interest in resonance Raman spectroscopy on semiconductors.In 1979 he received his first appointment as full professor at the University of Ulm. He returned to RWTH Aachen in 1981 and discovered his true destiny: semiconductor interfaces. At that time in the Department of Semiconductor Technology, metal-organic vapour phase epitaxy (MOVPE) was under development as a new technique for growing semiconductor layers. The underlying processes in MOVPE were known to be complex and very difficult to analyse with available experimental techniques, due to the unfriendly, reactive gas phase environment. Optical diagnostics turned out to be the key to a better understanding of MOVPE processes. Wolfgang Richter moved from RWTH Aachen to TU Berlin at the end of 1988 and began building a strong research group concentrating on interface analysis from two complementary sides: on the one hand, tracking MOVPE growth processes online by in situ optics and, on the other hand, advancing the fundamental understanding of optical spectra of interfaces by relating the optical response to atomic structures. Combining both aspects has finally led to considerable progress in surface and interface optics, as well as in vapour phase epitaxy and, moreover, the in situ optical tools developed are nowadays available as standard options in commercial MOVPE machines.The advances largely concerned the development of reflectance anisotropy spectroscopy and spectroscopic ellipsometry as in situ optical tools. However, considerable progress in Raman spectroscopy was also made: analysis of surfaces, ultrathin layers down to a single monolayer or even sub-monolayer coverages, and sub-wavelength spatial resolution were demonstrated in recent years. Current challenges concern, in particular, organic materials, molecule-solid interfaces and bio-interfaces, which will help in the development of many new applications and devices. Interfaces will play a crucial role in many of these developments and optical spectroscopy offers promising capabilities for analysing such interfaces. Wolfgang Richter and his group at University of Rome II Tor Vergata are sure to be active in this emerging field for a long time to come.Based on a symposium on Optical Spectroscopy of Interfaces at the Spring Meeting of the German Physical Society in Berlin 2005, we have asked former and present colleagues of Wolfgang Richter to contribute to this special issue of physica status solidi (b) on Advanced Optical Diagnostics of Surfaces, Nanostructures and Ultrathin Films. We think that the collection of 26 papers gives an excellent overview on recent achievements and future developments in the field of linear optics. In addition to a number of Original Papers on experimental work and some Review Articles, the issue includes examples of the current approaches of computational theory to solid state optics and interface optics. We hope that this issue will stimulate the expansion of the growing field of optical analysis of interfaces, nanostructures and ultrathin layers into new areas of basic and applied science. After the success in characterising inorganic materials, it is surely time that the potential of optical spectroscopy techniques for probing thin films and interfaces of composite (organic-inorganic) materials was considered.5 October 2005

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

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.

A mixture neural net for multispectral imaging spectrometer processing

NASA Technical Reports Server (NTRS)

Casasent, David; Slagle, Timothy

1990-01-01

Each spatial region viewed by an imaging spectrometer contains various elements in a mixture. The elements present and the amount of each are to be determined. A neural net solution is considered. Initial optical neural net hardware is described. The first simulations on the component requirements of a neural net are considered. The pseudoinverse solution is shown to not suffice, i.e. a neural net solution is required.

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

Classification of remotely sensed data using OCR-inspired neural network techniques. [Optical Character Recognition

NASA Technical Reports Server (NTRS)

Kiang, Richard K.

1992-01-01

Neural networks have been applied to classifications of remotely sensed data with some success. To improve the performance of this approach, an examination was made of how neural networks are applied to the optical character recognition (OCR) of handwritten digits and letters. A three-layer, feedforward network, along with techniques adopted from OCR, was used to classify Landsat-4 Thematic Mapper data. Good results were obtained. To overcome the difficulties that are characteristic of remote sensing applications and to attain significant improvements in classification accuracy, a special network architecture may be required.

Optical track width measurements below 100 nm using artificial neural networks

NASA Astrophysics Data System (ADS)

Smith, R. J.; See, C. W.; Somekh, M. G.; Yacoot, A.; Choi, E.

2005-12-01

This paper discusses the feasibility of using artificial neural networks (ANNs), together with a high precision scanning optical profiler, to measure very fine track widths that are considerably below the conventional diffraction limit of a conventional optical microscope. The ANN is trained using optical profiles obtained from tracks of known widths, the network is then assessed by applying it to test profiles. The optical profiler is an ultra-stable common path scanning interferometer, which provides extremely precise surface measurements. Preliminary results, obtained with a 0.3 NA objective lens and a laser wavelength of 633 nm, show that the system is capable of measuring a 50 nm track width, with a standard deviation less than 4 nm.

Low-power, transparent optical network interface for high bandwidth off-chip interconnects.

PubMed

Liboiron-Ladouceur, Odile; Wang, Howard; Garg, Ajay S; Bergman, Keren

2009-04-13

The recent emergence of multicore architectures and chip multiprocessors (CMPs) has accelerated the bandwidth requirements in high-performance processors for both on-chip and off-chip interconnects. For next generation computing clusters, the delivery of scalable power efficient off-chip communications to each compute node has emerged as a key bottleneck to realizing the full computational performance of these systems. The power dissipation is dominated by the off-chip interface and the necessity to drive high-speed signals over long distances. We present a scalable photonic network interface approach that fully exploits the bandwidth capacity offered by optical interconnects while offering significant power savings over traditional E/O and O/E approaches. The power-efficient interface optically aggregates electronic serial data streams into a multiple WDM channel packet structure at time-of-flight latencies. We demonstrate a scalable optical network interface with 70% improvement in power efficiency for a complete end-to-end PCI Express data transfer.

Involvement of the Extrageniculate System in the Perception of Optical Illusions: A Functional Magnetic Resonance Imaging Study

PubMed Central

Tabei, Ken-ichi; Satoh, Masayuki; Kida, Hirotaka; Kizaki, Moeni; Sakuma, Haruno; Sakuma, Hajime; Tomimoto, Hidekazu

2015-01-01

Research on the neural processing of optical illusions can provide clues for understanding the neural mechanisms underlying visual perception. Previous studies have shown that some visual areas contribute to the perception of optical illusions such as the Kanizsa triangle and Müller-Lyer figure; however, the neural mechanisms underlying the processing of these and other optical illusions have not been clearly identified. Using functional magnetic resonance imaging (fMRI), we determined which brain regions are active during the perception of optical illusions. For our study, we enrolled 18 participants. The illusory optical stimuli consisted of many kana letters, which are Japanese phonograms. During the shape task, participants stated aloud whether they perceived the shapes of two optical illusions as being the same or not. During the word task, participants read aloud the kana letters in the stimuli. A direct comparison between the shape and word tasks showed activation of the right inferior frontal gyrus, left medial frontal gyrus, and right pulvinar. It is well known that there are two visual pathways, the geniculate and extrageniculate systems, which belong to the higher-level and primary visual systems, respectively. The pulvinar belongs to the latter system, and the findings of the present study suggest that the extrageniculate system is involved in the cognitive processing of optical illusions. PMID:26083375

Optogenetic interrogation of neural circuits: technology for probing mammalian brain structures

PubMed Central

Zhang, Feng; Gradinaru, Viviana; Adamantidis, Antoine R; Durand, Remy; Airan, Raag D; de Lecea, Luis; Deisseroth, Karl

2015-01-01

Elucidation of the neural substrates underlying complex animal behaviors depends on precise activity control tools, as well as compatible readout methods. Recent developments in optogenetics have addressed this need, opening up new possibilities for systems neuroscience. Interrogation of even deep neural circuits can be conducted by directly probing the necessity and sufficiency of defined circuit elements with millisecond-scale, cell type-specific optical perturbations, coupled with suitable readouts such as electrophysiology, optical circuit dynamics measures and freely moving behavior in mammals. Here we collect in detail our strategies for delivering microbial opsin genes to deep mammalian brain structures in vivo, along with protocols for integrating the resulting optical control with compatible readouts (electrophysiological, optical and behavioral). The procedures described here, from initial virus preparation to systems-level functional readout, can be completed within 4–5 weeks. Together, these methods may help in providing circuit-level insight into the dynamics underlying complex mammalian behaviors in health and disease. PMID:20203662

A common-path optical coherence tomography based electrode for structural imaging of nerves and recording of action potentials

NASA Astrophysics Data System (ADS)

Islam, M. Shahidul; Haque, Md. Rezuanul; Oh, Christian M.; Wang, Yan; Park, B. Hyle

2013-03-01

Current technologies for monitoring neural activity either use different variety of electrodes (electrical recording) or require contrast agents introduced exogenously or through genetic modification (optical imaging). Here we demonstrate an optical method for non-contact and contrast agent free detection of nerve activity using phase-resolved optical coherence tomography (pr-OCT). A common-path variation of the pr-OCT is recently implemented and the developed system demonstrated the capability to detect rapid transient structural changes that accompany neural spike propagation. No averaging over multiple trials was required, indicating its capability of single-shot detection of individual impulses from functionally stimulated Limulus optic nerve. The strength of this OCT-based optical electrode is that it is a contactless method and does not require any exogenous contrast agent. With further improvements in accuracy and sensitivity, this optical electrode will play a complementary role to the existing recording technologies in future.

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

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.

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

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

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.

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.

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.

Loop Mirror Laser Neural Network with a Fast Liquid-Crystal Display

NASA Astrophysics Data System (ADS)

Mos, Evert C.; Schleipen, Jean J. H. B.; de Waardt, Huug; Khoe, Djan G. D.

1999-07-01

In our laser neural network (LNN) all-optical threshold action is obtained by application of controlled optical feedback to a laser diode. Here an extended experimental LNN is presented with as many as 32 neurons and 12 inputs. In the setup we use a fast liquid-crystal display to implement an optical matrix vector multiplier. This display, based on ferroelectric liquid-crystal material, enables us to present 125 training examples s to the LNN. To maximize the optical feedback efficiency of the setup, a loop mirror is introduced. We use a -rule learning algorithm to train the network to perform a number of functions toward the application area of telecommunication data switching.

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

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.

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).

Electro-optical interfacial effects on a graphene/π-conjugated organic semiconductor hybrid system

PubMed Central

Araujo, Karolline A S; Cury, Luiz A; Matos, Matheus J S; Fernandes, Thales F D; Cançado, Luiz G

2018-01-01

The influence of graphene and retinoic acid (RA) – a π-conjugated organic semiconductor – interface on their hybrid system is investigated. The physical properties of the interface are assessed via scanning probe microscopy, optical spectroscopy (photoluminescence and Raman) and ab initio calculations. The graphene/RA interaction induces the formation of a well-organized π-conjugated self-assembled monolayer (SAM) at the interface. Such structural organization leads to the high optical emission efficiency of the RA SAM, even at room temperature. Additionally, photo-assisted electrical force microscopy, photo-assisted scanning Kelvin probe microscopy and Raman spectroscopy indicate a RA-induced graphene doping and photo-charge generation. Finally, the optical excitation of the RA monolayer generates surface potential changes on the hybrid system. In summary, interface-induced organized structures atop 2D materials may have an important impact on both design and operation of π-conjugated nanomaterial-based hybrid systems. PMID:29600157

Detection of cortical optical changes during seizure activity using optical coherence tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ornelas, Danielle; Hasan, Md.; Gonzalez, Oscar; Krishnan, Giri; Szu, Jenny I.; Myers, Timothy; Hirota, Koji; Bazhenov, Maxim; Binder, Devin K.; Park, Boris H.

2017-02-01

Electrophysiology has remained the gold standard of neural activity detection but its resolution and high susceptibility to noise and motion artifact limit its efficiency. Imaging techniques, including fMRI, intrinsic optical imaging, and diffuse optical imaging, have been used to detect neural activity, but rely on indirect measurements such as changes in blood flow. Fluorescence-based techniques, including genetically encoded indicators, are powerful techniques, but require introduction of an exogenous fluorophore. A more direct optical imaging technique is optical coherence tomography (OCT), a label-free, high resolution, and minimally invasive imaging technique that can produce depth-resolved cross-sectional and 3D images. In this study, we sought to examine non-vascular depth-dependent optical changes directly related to neural activity. We used an OCT system centered at 1310 nm to search for changes in an ex vivo brain slice preparation and an in vivo model during 4-AP induced seizure onset and propagation with respect to electrical recording. By utilizing Doppler OCT and the depth-dependency of the attenuation coefficient, we demonstrate the ability to locate and remove the optical effects of vasculature within the upper regions of the cortex from in vivo attenuation calculations. The results of this study show a non-vascular decrease in intensity and attenuation in ex vivo and in vivo seizure models, respectively. Regions exhibiting decreased optical changes show significant temporal correlation to regions of increased electrical activity during seizure. This study allows for a thorough and biologically relevant analysis of the optical signature of seizure activity both ex vivo and in vivo using OCT.

Regression-Based Identification of Behavior-Encoding Neurons During Large-Scale Optical Imaging of Neural Activity at Cellular Resolution

PubMed Central

Miri, Andrew; Daie, Kayvon; Burdine, Rebecca D.; Aksay, Emre

2011-01-01

The advent of methods for optical imaging of large-scale neural activity at cellular resolution in behaving animals presents the problem of identifying behavior-encoding cells within the resulting image time series. Rapid and precise identification of cells with particular neural encoding would facilitate targeted activity measurements and perturbations useful in characterizing the operating principles of neural circuits. Here we report a regression-based approach to semiautomatically identify neurons that is based on the correlation of fluorescence time series with quantitative measurements of behavior. The approach is illustrated with a novel preparation allowing synchronous eye tracking and two-photon laser scanning fluorescence imaging of calcium changes in populations of hindbrain neurons during spontaneous eye movement in the larval zebrafish. Putative velocity-to-position oculomotor integrator neurons were identified that showed a broad spatial distribution and diversity of encoding. Optical identification of integrator neurons was confirmed with targeted loose-patch electrical recording and laser ablation. The general regression-based approach we demonstrate should be widely applicable to calcium imaging time series in behaving animals. PMID:21084686

An All-Optical Access Metro Interface for Hybrid WDM/TDM PON Based on OBS

NASA Astrophysics Data System (ADS)

Segarra, Josep; Sales, Vicent; Prat, Josep

2007-04-01

A new all-optical access metro network interface based on optical burst switching (OBS) is proposed. A hybrid wavelength-division multiplexing/time-division multiplexing (WDM/TDM) access architecture with reflective optical network units (ONUs), an arrayed-waveguide-grating outside plant, and a tunable laser stack at the optical line terminal (OLT) is presented as a solution for the passive optical network. By means of OBS and a dynamic bandwidth allocation (DBA) protocol, which polls the ONUs, the available access bandwidth is managed. All the network intelligence and costly equipment is located at the OLT, where the DBA module is centrally implemented, providing quality of service (QoS). To scale this access network, an optical cross connect (OXC) is then used to attain a large number of ONUs by the same OLT. The hybrid WDM/TDM structure is also extended toward the metropolitan area network (MAN) by introducing the concept of OBS multiplexer (OBS-M). The network element OBS-M bridges the MAN and access networks by offering all-optical cross connection, wavelength conversion, and data signaling. The proposed innovative OBS-M node yields a full optical data network, interfacing access and metro with a geographically distributed access control. The resulting novel access metro architectures are nonblocking and, with an improved signaling, provide QoS, scalability, and very low latency. Finally, numerical analysis and simulations demonstrate the traffic performance of the proposed access scheme and all-optical access metro interface and architectures.

Neural network-based feature point descriptors for registration of optical and SAR images

NASA Astrophysics Data System (ADS)

Abulkhanov, Dmitry; Konovalenko, Ivan; Nikolaev, Dmitry; Savchik, Alexey; Shvets, Evgeny; Sidorchuk, Dmitry

2018-04-01

Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method's effectiveness.

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

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.

Optics-Only Calibration of a Neural-Net Based Optical NDE Method for Structural Health Monitoring

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2004-01-01

A calibration process is presented that uses optical measurements alone to calibrate a neural-net based NDE method. The method itself detects small changes in the vibration mode shapes of structures. The optics-only calibration process confirms previous work that the sensitivity to vibration-amplitude changes can be as small as 10 nanometers. A more practical value in an NDE service laboratory is shown to be 50 nanometers. Both model-generated and experimental calibrations are demonstrated using two implementations of the calibration technique. The implementations are based on previously published demonstrations of the NDE method and an alternative calibration procedure that depends on comparing neural-net and point sensor measurements. The optics-only calibration method, unlike the alternative method, does not require modifications of the structure being tested or the creation of calibration objects. The calibration process can be used to test improvements in the NDE process and to develop a vibration-mode-independence of damagedetection sensitivity. The calibration effort was intended to support NASA s objective to promote safety in the operations of ground test facilities or aviation safety, in general, by allowing the detection of the gradual onset of structural changes and damage.

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

Application of Artificial Neural Network to Optical Fluid Analyzer

NASA Astrophysics Data System (ADS)

Kimura, Makoto; Nishida, Katsuhiko

1994-04-01

A three-layer artificial neural network has been applied to the presentation of optical fluid analyzer (OFA) raw data, and the accuracy of oil fraction determination has been significantly improved compared to previous approaches. To apply the artificial neural network approach to solving a problem, the first step is training to determine the appropriate weight set for calculating the target values. This involves using a series of data sets (each comprising a set of input values and an associated set of output values that the artificial neural network is required to determine) to tune artificial neural network weighting parameters so that the output of the neural network to the given set of input values is as close as possible to the required output. The physical model used to generate the series of learning data sets was the effective flow stream model, developed for OFA data presentation. The effectiveness of the training was verified by reprocessing the same input data as were used to determine the weighting parameters and then by comparing the results of the artificial neural network to the expected output values. The standard deviation of the expected and obtained values was approximately 10% (two sigma).

Interfacial behavior of confined mesogens at smectic-C*-water boundary.

PubMed

Chandran, Achu; Khanna, P K; Haranath, D; Biradar, Ashok M

2018-02-01

In this paper, we have investigated the behavior of mesogens at smectic-C*-water interface confined in a liquid crystal (LC) cell with interfacial geometry. Polarized optical microscopy was used to probe the appearance of various smectic-C* domain patterns at water interface owing to the reorientation of mesogens. The undulated stripe domains observed at the air interface of smectic-C* meniscus vanished as the water entered into the smectic layers and focal conical domain patterns appeared at smectic-C*-water boundary. A spatially variable electro-optical switching of LC molecules was also observed outside the electrode area of the interfacial cell. The electrode region at the interface, as well as on the water side, was damaged upon application of an electric field of magnitude more than 150 kV/m. The change in dielectric parameters of mesogens was extensively studied at interface after evaporating the water. These studies give fundamental insights into smectic-C*-water interface and also will be helpful in fabricating better LC devices for electro-optical and sensing applications.

Interfacial behavior of confined mesogens at smectic-C*-water boundary

NASA Astrophysics Data System (ADS)

Chandran, Achu; Khanna, P. K.; Haranath, D.; Biradar, Ashok M.

2018-02-01

In this paper, we have investigated the behavior of mesogens at smectic-C*-water interface confined in a liquid crystal (LC) cell with interfacial geometry. Polarized optical microscopy was used to probe the appearance of various smectic-C* domain patterns at water interface owing to the reorientation of mesogens. The undulated stripe domains observed at the air interface of smectic-C* meniscus vanished as the water entered into the smectic layers and focal conical domain patterns appeared at smectic-C*-water boundary. A spatially variable electro-optical switching of LC molecules was also observed outside the electrode area of the interfacial cell. The electrode region at the interface, as well as on the water side, was damaged upon application of an electric field of magnitude more than 150 kV/m. The change in dielectric parameters of mesogens was extensively studied at interface after evaporating the water. These studies give fundamental insights into smectic-C*-water interface and also will be helpful in fabricating better LC devices for electro-optical and sensing applications.

Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines

NASA Astrophysics Data System (ADS)

Sidelnikov, O. S.; Redyuk, A. A.; Sygletos, S.

2017-12-01

We consider neural network-based schemes of digital signal processing. It is shown that the use of a dynamic neural network-based scheme of signal processing ensures an increase in the optical signal transmission quality in comparison with that provided by other methods for nonlinear distortion compensation.

Optical Processing.

DTIC Science & Technology

1985-12-31

34 Optics Letters, 2 (1), 1-3 (1978). 7. Grossberg, S., "Adaptive Resonance in Development, Perception and Cognition ," SIAM-AMS Proc., 13, 107-156...Illusions," Biol. Cybernetics, 23, 187-202, (1976b). 11. Grossberg, S., "How Does A Brain Build a Cognitive Code?", Psychol. Review, 87 (1), 1-51 (1980...34perceptron" (F. Rosenblatt, Principles of Neurodynamics ), workers in the neural network field have been seeking to understand how neural networks can perform

One-Step Optogenetics with Multifunctional Flexible Polymer Fibers

PubMed Central

Park, Seongjun; Guo, Yuanyuan; Jia, Xiaoting; Choe, Han Kyoung; Grena, Benjamin; Kang, Jeewoo; Park, Jiyeon; Lu, Chi; Canales, Andres; Chen, Ritchie; Yim, Yeong Shin; Choi, Gloria B.; Fink, Yoel; Anikeeva, Polina

2017-01-01

Optogenetic interrogation of neural pathways relies on delivery of light-sensitive opsins into tissue and subsequent optical illumination and electrical recording from the regions of interest. Despite the recent development of multifunctional neural probes, integration of these modalities within a single biocompatible platform remains a challenge. Here, we introduce a device composed of an optical waveguide, six electrodes, and two microfluidic channels produced via fiber drawing. Our probes facilitated injections of viral vectors carrying opsin genes, while providing collocated neural recording and optical stimulation. The miniature (< 200 μm) footprint and modest weight (<0.5 g) of these probes allowed for multiple implantations into the mouse brain, which enabled opto-electrophysiological investigation of projections from the basolateral amygdala to the medial prefrontal cortex and ventral hippocampus during behavioral experiments. Fabricated solely from polymers and polymer composites, these flexible probes minimized tissue response to achieve chronic multimodal interrogation of brain circuits with high fidelity. PMID:28218915

Immature visual neural system in children reflected by contrast sensitivity with adaptive optics correction

PubMed Central

Liu, Rong; Zhou, Jiawei; Zhao, Haoxin; Dai, Yun; Zhang, Yudong; Tang, Yong; Zhou, Yifeng

2014-01-01

This study aimed to explore the neural development status of the visual system of children (around 8 years old) using contrast sensitivity. We achieved this by eliminating the influence of higher order aberrations (HOAs) with adaptive optics correction. We measured HOAs, modulation transfer functions (MTFs) and contrast sensitivity functions (CSFs) of six children and five adults with both corrected and uncorrected HOAs. We found that when HOAs were corrected, children and adults both showed improvements in MTF and CSF. However, the CSF of children was still lower than the adult level, indicating the difference in contrast sensitivity between groups cannot be explained by differences in optical factors. Further study showed that the difference between the groups also could not be explained by differences in non-visual factors. With these results we concluded that the neural systems underlying vision in children of around 8 years old are still immature in contrast sensitivity. PMID:24732728

Modal demultiplexing properties of tapered and nanostructured optical fibers for in vivo optogenetic control of neural activity.

PubMed

Pisanello, Marco; Della Patria, Andrea; Sileo, Leonardo; Sabatini, Bernardo L; De Vittorio, Massimo; Pisanello, Ferruccio

2015-10-01

Optogenetic approaches to manipulate neural activity have revolutionized the ability of neuroscientists to uncover the functional connectivity underlying brain function. At the same time, the increasing complexity of in vivo optogenetic experiments has increased the demand for new techniques to precisely deliver light into the brain, in particular to illuminate selected portions of the neural tissue. Tapered and nanopatterned gold-coated optical fibers were recently proposed as minimally invasive multipoint light delivery devices, allowing for site-selective optogenetic stimulation in the mammalian brain [Pisanello , Neuron82, 1245 (2014)]. Here we demonstrate that the working principle behind these devices is based on the mode-selective photonic properties of the fiber taper. Using analytical and ray tracing models we model the finite conductance of the metal coating, and show that single or multiple optical windows located at specific taper sections can outcouple only specific subsets of guided modes injected into the fiber.

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.

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.

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].

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.

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.

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.

Proceedings 5th International Conference on Optics of Surfaces and Interfaces (OSI-V), Léon, México 26-30 May 2003: physica status solidi (c) - conferences and critical reviews

NASA Astrophysics Data System (ADS)

Mendoza, Bernardo S.

2003-05-01

physica status solidi (c) conferences and critical reviews publishes conference proceedings, ranging from large international meetings to specialized topical workshops as well as collections of topical reviews on various areas of current solid state physics research. The objective of "Optics of Surfaces and Interfaces" (OSI-V) is to bridge the gap between basic and applied science. Apart from recent advances in theoretical modeling and experimental research, special attention is given to novel techniques of optical spectroscopy at interfaces.

Theory of tailorable optical response of two-dimensional arrays of plasmonic nanoparticles at dielectric interfaces.

PubMed

Sikdar, Debabrata; Kornyshev, Alexei A

2016-09-22

Two-dimensional arrays of plasmonic nanoparticles at interfaces are promising candidates for novel optical metamaterials. Such systems materialise from 'top-down' patterning or 'bottom-up' self-assembly of nanoparticles at liquid/liquid or liquid/solid interfaces. Here, we present a comprehensive analysis of an extended effective quasi-static four-layer-stack model for the description of plasmon-resonance-enhanced optical responses of such systems. We investigate in detail the effects of the size of nanoparticles, average interparticle separation, dielectric constants of the media constituting the interface, and the nanoparticle position relative to the interface. Interesting interplays of these different factors are explored first for normally incident light. For off-normal incidence, the strong effects of the polarisation of light are found at large incident angles, which allows to dynamically tune the reflectance spectra. All the predictions of the theory are tested against full-wave simulations, proving this simplistic model to be adequate within the quasi-static limit. The model takes seconds to calculate the system's optical response and makes it easy to unravel the effect of each system parameter. This helps rapid rationalization of experimental data and understanding of the optical signals from these novel 'metamaterials', optimised for light reflection or harvesting.

Theory of tailorable optical response of two-dimensional arrays of plasmonic nanoparticles at dielectric interfaces

PubMed Central

Sikdar, Debabrata; Kornyshev, Alexei A.

2016-01-01

Two-dimensional arrays of plasmonic nanoparticles at interfaces are promising candidates for novel optical metamaterials. Such systems materialise from ‘top–down’ patterning or ‘bottom–up’ self-assembly of nanoparticles at liquid/liquid or liquid/solid interfaces. Here, we present a comprehensive analysis of an extended effective quasi-static four-layer-stack model for the description of plasmon-resonance-enhanced optical responses of such systems. We investigate in detail the effects of the size of nanoparticles, average interparticle separation, dielectric constants of the media constituting the interface, and the nanoparticle position relative to the interface. Interesting interplays of these different factors are explored first for normally incident light. For off-normal incidence, the strong effects of the polarisation of light are found at large incident angles, which allows to dynamically tune the reflectance spectra. All the predictions of the theory are tested against full-wave simulations, proving this simplistic model to be adequate within the quasi-static limit. The model takes seconds to calculate the system’s optical response and makes it easy to unravel the effect of each system parameter. This helps rapid rationalization of experimental data and understanding of the optical signals from these novel ‘metamaterials’, optimised for light reflection or harvesting. PMID:27652788

Effect of shorter pulse duration in cochlear neural activation with an 810-nm near-infrared laser.

PubMed

Wang, Jingxuan; Tian, Lan; Lu, Jianren; Xia, Ming; Wei, Ying

2017-02-01

Optical neural stimulation in the cochlea has been presented as an alternative technique to the electrical stimulation due to its potential in spatially selectivity enhancement. So far, few studies have selected the near-infrared (NIR) laser in cochlear neural stimulation and limited optical parameter space has been examined. This paper focused on investigating the optical parameter effect on NIR stimulation of auditory neurons, especially under shorter pulse durations. The spiral ganglion neurons in the cochlea of deafened guinea pigs were stimulated with a pulsed 810-nm NIR laser in vivo. The laser radiation was delivered by an optical fiber and irradiated towards the modiolus. Optically evoked auditory brainstem responses (OABRs) with various optical parameters were recorded and investigated. The OABRs could be elicited with the cochlear deafened animals by using the 810-nm laser in a wide pulse duration ranged from 20 to 1000 μs. Results showed that the OABR intensity increased along with the increasing laser radiant exposure of limited range at each specific pulse duration. In addition, for the pulse durations from 20 to 300 μs, the OABR intensity increased monotonically along with the pulse duration broadening. While for pulse durations above 300 μs, the OABR intensity basically kept stable with the increasing pulse duration. The 810-nm NIR laser could be an effective stimulus in evoking the cochlear neuron response. Our experimental data provided evidence to optimize the pulse duration range, and the results suggested that the pulse durations from 20 to 300 μs could be the optimized range in cochlear neural activation with the 810-nm-wavelength laser.

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.

A stereo-compound hybrid microscope for combined intracellular and optical recording of invertebrate neural network activity.

PubMed

Frost, William N; Wang, Jean; Brandon, Christopher J

2007-05-15

Optical recording studies of invertebrate neural networks with voltage-sensitive dyes seldom employ conventional intracellular electrodes. This may in part be due to the traditional reliance on compound microscopes for such work. While such microscopes have high light-gathering power, they do not provide depth of field, making working with sharp electrodes difficult. Here we describe a hybrid microscope design, with switchable compound and stereo objectives, that eases the use of conventional intracellular electrodes in optical recording experiments. We use it, in combination with a voltage-sensitive dye and photodiode array, to identify neurons participating in the swim motor program of the marine mollusk Tritonia. This microscope design should be applicable to optical recording studies in many preparations.

Compact holographic optical neural network system for real-time pattern recognition

NASA Astrophysics Data System (ADS)

Lu, Taiwei; Mintzer, David T.; Kostrzewski, Andrew A.; Lin, Freddie S.

1996-08-01

One of the important characteristics of artificial neural networks is their capability for massive interconnection and parallel processing. Recently, specialized electronic neural network processors and VLSI neural chips have been introduced in the commercial market. The number of parallel channels they can handle is limited because of the limited parallel interconnections that can be implemented with 1D electronic wires. High-resolution pattern recognition problems can require a large number of neurons for parallel processing of an image. This paper describes a holographic optical neural network (HONN) that is based on high- resolution volume holographic materials and is capable of performing massive 3D parallel interconnection of tens of thousands of neurons. A HONN with more than 16,000 neurons packaged in an attache case has been developed. Rotation- shift-scale-invariant pattern recognition operations have been demonstrated with this system. System parameters such as the signal-to-noise ratio, dynamic range, and processing speed are discussed.

Using Reinforcement Learning to Provide Stable Brain-Machine Interface Control Despite Neural Input Reorganization

PubMed Central

Pohlmeyer, Eric A.; Mahmoudi, Babak; Geng, Shijia; Prins, Noeline W.; Sanchez, Justin C.

2014-01-01

Brain-machine interface (BMI) systems give users direct neural control of robotic, communication, or functional electrical stimulation systems. As BMI systems begin transitioning from laboratory settings into activities of daily living, an important goal is to develop neural decoding algorithms that can be calibrated with a minimal burden on the user, provide stable control for long periods of time, and can be responsive to fluctuations in the decoder’s neural input space (e.g. neurons appearing or being lost amongst electrode recordings). These are significant challenges for static neural decoding algorithms that assume stationary input/output relationships. Here we use an actor-critic reinforcement learning architecture to provide an adaptive BMI controller that can successfully adapt to dramatic neural reorganizations, can maintain its performance over long time periods, and which does not require the user to produce specific kinetic or kinematic activities to calibrate the BMI. Two marmoset monkeys used the Reinforcement Learning BMI (RLBMI) to successfully control a robotic arm during a two-target reaching task. The RLBMI was initialized using random initial conditions, and it quickly learned to control the robot from brain states using only a binary evaluative feedback regarding whether previously chosen robot actions were good or bad. The RLBMI was able to maintain control over the system throughout sessions spanning multiple weeks. Furthermore, the RLBMI was able to quickly adapt and maintain control of the robot despite dramatic perturbations to the neural inputs, including a series of tests in which the neuron input space was deliberately halved or doubled. PMID:24498055

Novel neural interface for implant electrodes: improving electroactivity of polypyrrole through MWNT incorporation.

PubMed

Green, R A; Williams, C M; Lovell, N H; Poole-Warren, L A

2008-04-01

Multi-walled carbon nanotubes (MWNTs) can be incorporated into conductive polymers to produce superior materials for neural interfaces with high interfacial areas, conductivity and electrochemical stability. This paper explores the addition of MWNTs to polypyrrole (PPy) through two methods, layering and codeposition. Conductivity of PPy doped with polystyrene sulfonate (PSS), a commonly used dopant, was improved by 50% when MWNTs were layered with PPy/PSS. The film electrochemical stability was improved from 38% activity to 66% activity after 400 cycles of oxidation and reduction. Growth inhibition assays indicated that MWNTs are not growth inhibitory. The electroactive polymer-MWNT composites produced demonstrate properties that suggest they are promising candidates for biomedical electrode coatings.

Determination of optical coefficients of biological tissue from a single integrating-sphere

NASA Astrophysics Data System (ADS)

Zhang, Lianshun; Shi, Aijuan; Lu, Hongguang

2012-01-01

The detection of interactions between light and tissue can be used to characterize the optical properties of the tissue. The development is described of a method that determines optical coefficients of biological tissue from a single optical reflectance spectrum measured with an integrating-sphere. The experimental system incorporated a DH-2000 deuterium tungsten halogen light source, a USB4000-VIS-NIR miniature fiber optic spectrometer and an integrating-sphere. Fat emulsion and ink were used to mimic the scattering and absorbing properties of tissue in the tested sample. The measured optical reflectance spectrums with different scattering and absorbing properties were used to train a back-propagation neural network (BPNN). Then the neural network (BPNN) was used to determine the optical coefficients of biological tissue from a single optical reflectance spectrum measured with an integrating-sphere. Tests on tissue-simulation phantoms showed the relative errors of this technique to be 7% for the reduced scattering coefficient and 15% for the absorption coefficients. The optical properties of human skin were also measured in vivo.

Uranium(IV) Interaction with Aqueous/Solid Interfaces Studied by Nonlinear Optics

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

Geiger, Franz

2015-03-27

This is the Final Technical Report for "Uranium(IV) Interaction with Aqueous/Solid Interfaces Studied by Nonlinear Optics", by Franz M. Geiger, PI, from Northwestern University, IL, USA, Grant Number SC0004101 and/or DE-PS02-ER09-07.

Retinal and anterior eye compartments derive from a common progenitor pool in the avian optic cup

PubMed Central

Venters, Sara J.; Cuenca, Paulina D.

2011-01-01

Purpose The optic cup is created through invagination of the optic vesicle. The morphogenetic rearrangement creates a double-layered cup, with a hinge (the Optic Cup Lip) where the epithelium bends back upon itself. Shortly after the optic cup forms, it is thought to be sub-divided into separate lineages: i) pigmented epithelium in the outer layer; ii) presumptive iris and ciliary body at the most anterior aspect of the inner layer; and iii) presumptive neural retina in the remainder of the inner layer. We test the native developmental potential of the anterior cup to determine if it normally contributes to the retina. Methods Vital dye and green fluorescent protein (GFP) expressing replication-incompetent retroviral vectors were used to label cells in the nascent optic cup and follow their direct progeny throughout development. Label was applied to either the optic cup lip (n=40), or to the domain just posterior to the lip (n=20). Retroviral labeling is a permanent lineage marker and enabled the analysis of advanced stages of development. Results Labeling within the optic cup gave rise to labeled progeny in the posterior optic cup that differentiated as neural retina (20 of 20). In contrast, labeling cells in the optic cup lip gave rise to progeny of labeled cells arrayed in a linear progression, from the lip into the neural retina (36 of 40). Label was retained in cells at the optic cup lip, regardless of age at examination. In older embryos, labeled progeny delaminated from the optic cup lip to differentiate as muscle of the pupillary margin. Conclusions The data show that the cells at the optic cup lip are a common progenitor population for pigmented epithelium, anterior eye tissues (ciliary body, iris, and pupillary muscle) and retinal neurons. The findings are supportive of an interpretation where the optic cup lip is a specialized niche containing a multipotent progenitor population. PMID:22219630

Selection of neural network structure for system error correction of electro-optical tracker system with horizontal gimbal

NASA Astrophysics Data System (ADS)

Liu, Xing-fa; Cen, Ming

2007-12-01

Neural Network system error correction method is more precise than lest square system error correction method and spheric harmonics function system error correction method. The accuracy of neural network system error correction method is mainly related to the frame of Neural Network. Analysis and simulation prove that both BP neural network system error correction method and RBF neural network system error correction method have high correction accuracy; it is better to use RBF Network system error correction method than BP Network system error correction method for little studying stylebook considering training rate and neural network scale.

An efficient optical architecture for sparsely connected neural networks

NASA Technical Reports Server (NTRS)

Hine, Butler P., III; Downie, John D.; Reid, Max B.

1990-01-01

An architecture for general-purpose optical neural network processor is presented in which the interconnections and weights are formed by directing coherent beams holographically, thereby making use of the space-bandwidth products of the recording medium for sparsely interconnected networks more efficiently that the commonly used vector-matrix multiplier, since all of the hologram area is in use. An investigation is made of the use of computer-generated holograms recorded on such updatable media as thermoplastic materials, in order to define the interconnections and weights of a neural network processor; attention is given to limits on interconnection densities, diffraction efficiencies, and weighing accuracies possible with such an updatable thin film holographic device.

Optical Calibration Process Developed for Neural-Network-Based Optical Nondestructive Evaluation Method

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2004-01-01

A completely optical calibration process has been developed at Glenn for calibrating a neural-network-based nondestructive evaluation (NDE) method. The NDE method itself detects very small changes in the characteristic patterns or vibration mode shapes of vibrating structures as discussed in many references. The mode shapes or characteristic patterns are recorded using television or electronic holography and change when a structure experiences, for example, cracking, debonds, or variations in fastener properties. An artificial neural network can be trained to be very sensitive to changes in the mode shapes, but quantifying or calibrating that sensitivity in a consistent, meaningful, and deliverable manner has been challenging. The standard calibration approach has been difficult to implement, where the response to damage of the trained neural network is compared with the responses of vibration-measurement sensors. In particular, the vibration-measurement sensors are intrusive, insufficiently sensitive, and not numerous enough. In response to these difficulties, a completely optical alternative to the standard calibration approach was proposed and tested successfully. Specifically, the vibration mode to be monitored for structural damage was intentionally contaminated with known amounts of another mode, and the response of the trained neural network was measured as a function of the peak-to-peak amplitude of the contaminating mode. The neural network calibration technique essentially uses the vibration mode shapes of the undamaged structure as standards against which the changed mode shapes are compared. The published response of the network can be made nearly independent of the contaminating mode, if enough vibration modes are used to train the net. The sensitivity of the neural network can be adjusted for the environment in which the test is to be conducted. The response of a neural network trained with measured vibration patterns for use on a vibration isolation table in the presence of various sources of laboratory noise is shown. The output of the neural network is called the degradable classification index. The curve was generated by a simultaneous comparison of means, and it shows a peak-to-peak sensitivity of about 100 nm. The following graph uses model generated data from a compressor blade to show that much higher sensitivities are possible when the environment can be controlled better. The peak-to-peak sensitivity here is about 20 nm. The training procedure was modified for the second graph, and the data were subjected to an intensity-dependent transformation called folding. All the measurements for this approach to calibration were optical. The peak-to-peak amplitudes of the vibration modes were measured using heterodyne interferometry, and the modes themselves were recorded using television (electronic) holography.

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.

Local interconnection neural networks

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

Zhang Jiajun; Zhang Li; Yan Dapen

1993-06-01

The idea of a local interconnection neural network (LINN) is presentd and compared with the globally interconnected Hopfield model. Under the storage limit requirement, LINN is shown to offer the same associative memory capability as the global interconnection neural network while having a much smaller interconnection matrix. LINN can be readily implemented optically using the currently available spatial light modulators. 15 refs.

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.

Cerebral Aneurysms Fact Sheet

MedlinePlus

... Dementias Epilepsy Parkinson's Disease Spinal Cord Injury Traumatic Brain Injury Focus On Tools & Topics Bioengineering Neural Interfaces Biomarkers Health Disparities Stem Cell Trans-Agency Activities ...

Reduced Synchronization Persistence in Neural Networks Derived from Atm-Deficient Mice

PubMed Central

Levine-Small, Noah; Yekutieli, Ziv; Aljadeff, Jonathan; Boccaletti, Stefano; Ben-Jacob, Eshel; Barzilai, Ari

2011-01-01

Many neurodegenerative diseases are characterized by malfunction of the DNA damage response. Therefore, it is important to understand the connection between system level neural network behavior and DNA. Neural networks drawn from genetically engineered animals, interfaced with micro-electrode arrays allowed us to unveil connections between networks’ system level activity properties and such genome instability. We discovered that Atm protein deficiency, which in humans leads to progressive motor impairment, leads to a reduced synchronization persistence compared to wild type synchronization, after chemically imposed DNA damage. Not only do these results suggest a role for DNA stability in neural network activity, they also establish an experimental paradigm for empirically determining the role a gene plays on the behavior of a neural network. PMID:21519382

Collaborative Brain-Computer Interface for Aiding Decision-Making

PubMed Central

Poli, Riccardo; Valeriani, Davide; Cinel, Caterina

2014-01-01

We look at the possibility of integrating the percepts from multiple non-communicating observers as a means of achieving better joint perception and better group decisions. Our approach involves the combination of a brain-computer interface with human behavioural responses. To test ideas in controlled conditions, we asked observers to perform a simple matching task involving the rapid sequential presentation of pairs of visual patterns and the subsequent decision as whether the two patterns in a pair were the same or different. We recorded the response times of observers as well as a neural feature which predicts incorrect decisions and, thus, indirectly indicates the confidence of the decisions made by the observers. We then built a composite neuro-behavioural feature which optimally combines the two measures. For group decisions, we uses a majority rule and three rules which weigh the decisions of each observer based on response times and our neural and neuro-behavioural features. Results indicate that the integration of behavioural responses and neural features can significantly improve accuracy when compared with the majority rule. An analysis of event-related potentials indicates that substantial differences are present in the proximity of the response for correct and incorrect trials, further corroborating the idea of using hybrids of brain-computer interfaces and traditional strategies for improving decision making. PMID:25072739

An investigation on effects of amputee's physiological parameters on maximum pressure developed at the prosthetic socket interface using artificial neural network.

PubMed

Nayak, Chitresh; Singh, Amit; Chaudhary, Himanshu; Unune, Deepak Rajendra

2017-10-23

Technological advances in prosthetics have attracted the curiosity of researchers in monitoring design and developments of the sockets to sustain maximum pressure without any soft tissue damage, skin breakdown, and painful sores. Numerous studies have been reported in the area of pressure measurement at the limb/socket interface, though, the relation between amputee's physiological parameters and the pressure developed at the limb/socket interface is still not studied. Therefore, the purpose of this work is to investigate the effects of patient-specific physiological parameters viz. height, weight, and stump length on the pressure development at the transtibial prosthetic limb/socket interface. Initially, the pressure values at the limb/socket interface were clinically measured during stance and walking conditions for different patients using strain gauges placed at critical locations of the stump. The measured maximum pressure data related to patient's physiological parameters was used to develop an artificial neural network (ANN) model. The effects of physiological parameters on the pressure development at the limb/socket interface were examined using the ANN model. The analyzed results indicated that the weight and stump length significantly affects the maximum pressure values. The outcomes of this work could be an important platform for the design and development of patient-specific prosthetic socket which can endure the maximum pressure conditions at stance and ambulation conditions.

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.

The Neural-fuzzy Thermal Error Compensation Controller on CNC Machining Center

NASA Astrophysics Data System (ADS)

Tseng, Pai-Chung; Chen, Shen-Len

The geometric errors and structural thermal deformation are factors that influence the machining accuracy of Computer Numerical Control (CNC) machining center. Therefore, researchers pay attention to thermal error compensation technologies on CNC machine tools. Some real-time error compensation techniques have been successfully demonstrated in both laboratories and industrial sites. The compensation results still need to be enhanced. In this research, the neural-fuzzy theory has been conducted to derive a thermal prediction model. An IC-type thermometer has been used to detect the heat sources temperature variation. The thermal drifts are online measured by a touch-triggered probe with a standard bar. A thermal prediction model is then derived by neural-fuzzy theory based on the temperature variation and the thermal drifts. A Graphic User Interface (GUI) system is also built to conduct the user friendly operation interface with Insprise C++ Builder. The experimental results show that the thermal prediction model developed by neural-fuzzy theory methodology can improve machining accuracy from 80µm to 3µm. Comparison with the multi-variable linear regression analysis the compensation accuracy is increased from ±10µm to ±3µm.

Flexible Neural Electrode Array Based-on Porous Graphene for Cortical Microstimulation and Sensing

NASA Astrophysics Data System (ADS)

Lu, Yichen; Lyu, Hongming; Richardson, Andrew G.; Lucas, Timothy H.; Kuzum, Duygu

2016-09-01

Neural sensing and stimulation have been the backbone of neuroscience research, brain-machine interfaces and clinical neuromodulation therapies for decades. To-date, most of the neural stimulation systems have relied on sharp metal microelectrodes with poor electrochemical properties that induce extensive damage to the tissue and significantly degrade the long-term stability of implantable systems. Here, we demonstrate a flexible cortical microelectrode array based on porous graphene, which is capable of efficient electrophysiological sensing and stimulation from the brain surface, without penetrating into the tissue. Porous graphene electrodes show superior impedance and charge injection characteristics making them ideal for high efficiency cortical sensing and stimulation. They exhibit no physical delamination or degradation even after 1 million biphasic stimulation cycles, confirming high endurance. In in vivo experiments with rodents, same array is used to sense brain activity patterns with high spatio-temporal resolution and to control leg muscles with high-precision electrical stimulation from the cortical surface. Flexible porous graphene array offers a minimally invasive but high efficiency neuromodulation scheme with potential applications in cortical mapping, brain-computer interfaces, treatment of neurological disorders, where high resolution and simultaneous recording and stimulation of neural activity are crucial.

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.

Wide-field optical mapping of neural activity and brain haemodynamics: considerations and novel approaches

PubMed Central

Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Thibodeaux, David N.; Zhao, Hanzhi T.; Yu, Hang

2016-01-01

Although modern techniques such as two-photon microscopy can now provide cellular-level three-dimensional imaging of the intact living brain, the speed and fields of view of these techniques remain limited. Conversely, two-dimensional wide-field optical mapping (WFOM), a simpler technique that uses a camera to observe large areas of the exposed cortex under visible light, can detect changes in both neural activity and haemodynamics at very high speeds. Although WFOM may not provide single-neuron or capillary-level resolution, it is an attractive and accessible approach to imaging large areas of the brain in awake, behaving mammals at speeds fast enough to observe widespread neural firing events, as well as their dynamic coupling to haemodynamics. Although such wide-field optical imaging techniques have a long history, the advent of genetically encoded fluorophores that can report neural activity with high sensitivity, as well as modern technologies such as light emitting diodes and sensitive and high-speed digital cameras have driven renewed interest in WFOM. To facilitate the wider adoption and standardization of WFOM approaches for neuroscience and neurovascular coupling research, we provide here an overview of the basic principles of WFOM, considerations for implementation of wide-field fluorescence imaging of neural activity, spectroscopic analysis and interpretation of results. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574312

Analysis and classification of normal and pathological skin tissue spectra using neural networks

NASA Astrophysics Data System (ADS)

Bruch, Reinhard F.; Afanasyeva, Natalia I.; Gummuluri, Satyashree

2000-07-01

An innovative spectroscopic diagnostic method has been developed for investigation of different regions of normal human skin tissue, as well as cancerous and precancerous conditions in vivo, ex vivo and in vitro. This new method is a combination of fiber-optical evanescent wave Fourier Transform infrared (FEW-FTIR) spectroscopy and fiber optic techniques using low-loss, highly flexible and nontoxic fiber optical sensors. The FEW-FTIR technique is nondestructive and very sensitive to changes of vibrational spectra in the IR region without heating and staining and thus altering the skin tissue. A special software package was developed for the treatment of the spectra. This package includes a database, programs for data preparation and presentation, and neural networks for classification of disease states. An unsupervised neural competitive learning neural network is implemented for skin cancer diagnosis. In this study, we have investigated and classified skin tissue in the range of 1400 to 1800 cm-1 using these programs. The results of our surface analysis of skin tissue are discussed in terms of molecular structural similarities and differences as well as in terms of different skin states represented by eleven different skin spectra classes.

Changes in White Matter Microstructure Impact Cognition by Disrupting the Ability of Neural Assemblies to Synchronize.

PubMed

Bells, Sonya; Lefebvre, Jérémie; Prescott, Steven A; Dockstader, Colleen; Bouffet, Eric; Skocic, Jovanka; Laughlin, Suzanne; Mabbott, Donald J

2017-08-23

Cognition is compromised by white matter (WM) injury but the neurophysiological alterations linking them remain unclear. We hypothesized that reduced neural synchronization caused by disruption of neural signal propagation is involved. To test this, we evaluated group differences in: diffusion tensor WM microstructure measures within the optic radiations, primary visual area (V1), and cuneus; neural phase synchrony to a visual attention cue during visual-motor task; and reaction time to a response cue during the same task between 26 pediatric patients (17/9: male/female) treated with cranial radiation treatment for a brain tumor (12.67 ± 2.76 years), and 26 healthy children (16/10: male/female; 12.01 ± 3.9 years). We corroborated our findings using a corticocortical computational model representing perturbed signal conduction from myelin. Patients show delayed reaction time, WM compromise, and reduced phase synchrony during visual attention compared with healthy children. Notably, using partial least-squares-path modeling we found that WM insult within the optic radiations, V1, and cuneus is a strong predictor of the slower reaction times via disruption of neural synchrony in visual cortex. Observed changes in synchronization were reproduced in a computational model of WM injury. These findings provide new evidence linking cognition with WM via the reliance of neural synchronization on propagation of neural signals. SIGNIFICANCE STATEMENT By comparing brain tumor patients to healthy children, we establish that changes in the microstructure of the optic radiations and neural synchrony during visual attention predict reaction time. Furthermore, by testing the directionality of these links through statistical modeling and verifying our findings with computational modeling, we infer a causal relationship, namely that changes in white matter microstructure impact cognition in part by disturbing the ability of neural assemblies to synchronize. Together, our human imaging data and computer simulations show a fundamental connection between WM microstructure and neural synchronization that is critical for cognitive processing. Copyright © 2017 the authors 0270-6474/17/378227-12$15.00/0.

High-density stretchable microelectrode arrays: An integrated technology platform for neural and muscular surface interfacing

NASA Astrophysics Data System (ADS)

Guo, Liang

2011-12-01

Numerous applications in neuroscience research and neural prosthetics, such as retinal prostheses, spinal-cord surface stimulation for prosthetics, electrocorticogram (ECoG) recording for epilepsy detection, etc., involve electrical interaction with soft excitable tissues using a surface stimulation and/or recording approach. These applications require an interface that is able to set up electrical communications with a high throughput between electronics and the excitable tissue and that can dynamically conform to the shape of the soft tissue. Being a compliant and biocompatible material with mechanical impedance close to that of soft tissues, polydimethylsiloxane (PDMS) offers excellent potential as the substrate material for such neural interfaces. However, fabrication of electrical functionalities on PDMS has long been very challenging. This thesis work has successfully overcome many challenges associated with PDMS-based microfabrication and achieved an integrated technology platform for PDMS-based stretchable microelectrode arrays (sMEAs). This platform features a set of technological advances: (1) we have fabricated uniform current density profile microelectrodes as small as 10 mum in diameter; (2) we have patterned high-resolution (feature as small as 10 mum), high-density (pitch as small as 20 mum) thin-film gold interconnects on PDMS substrate; (3) we have developed a multilayer wiring interconnect technology within the PDMS substrate to further boost the achievable integration density of such sMEA; and (4) we have invented a bonding technology---via-bonding---to facilitate high-resolution, high-density integration of the sMEA with integrated circuits (ICs) to form a compact implant. Taken together, this platform provides a high-resolution, high-density integrated system solution for neural and muscular surface interfacing. sMEAs of example designs are evaluated through in vitro and in vivo experimentations on their biocompatibility, surface conformability, and surface recording/stimulation capabilities, with a focus on epimysial (i.e. on the surface of muscle) applications. Finally, as an example medical application, we investigate a prosthesis for unilateral vocal cord paralysis (UVCP) based on simultaneous multichannel epimysial recording and stimulation.

Dlx proteins position the neural plate border and determine adjacent cell fates.

PubMed

Woda, Juliana M; Pastagia, Julie; Mercola, Mark; Artinger, Kristin Bruk

2003-01-01

The lateral border of the neural plate is a major source of signals that induce primary neurons, neural crest cells and cranial placodes as well as provide patterning cues to mesodermal structures such as somites and heart. Whereas secreted BMP, FGF and Wnt proteins influence the differentiation of neural and non-neural ectoderm, we show here that members of the Dlx family of transcription factors position the border between neural and non-neural ectoderm and are required for the specification of adjacent cell fates. Inhibition of endogenous Dlx activity in Xenopus embryos with an EnR-Dlx homeodomain fusion protein expands the neural plate into non-neural ectoderm tissue whereas ectopic activation of Dlx target genes inhibits neural plate differentiation. Importantly, the stereotypic pattern of border cell fates in the adjacent ectoderm is re-established only under conditions where the expanded neural plate abuts Dlx-positive non-neural ectoderm. Experiments in which presumptive neural plate was grafted to ventral ectoderm reiterate induction of neural crest and placodal lineages and also demonstrate that Dlx activity is required in non-neural ectoderm for the production of signals needed for induction of these cells. We propose that Dlx proteins regulate intercellular signaling across the interface between neural and non-neural ectoderm that is critical for inducing and patterning adjacent cell fates.

Light propagation with phase discontinuities: generalized laws of reflection and refraction.

PubMed

Yu, Nanfang; Genevet, Patrice; Kats, Mikhail A; Aieta, Francesco; Tetienne, Jean-Philippe; Capasso, Federico; Gaburro, Zeno

2011-10-21

Conventional optical components rely on gradual phase shifts accumulated during light propagation to shape light beams. New degrees of freedom are attained by introducing abrupt phase changes over the scale of the wavelength. A two-dimensional array of optical resonators with spatially varying phase response and subwavelength separation can imprint such phase discontinuities on propagating light as it traverses the interface between two media. Anomalous reflection and refraction phenomena are observed in this regime in optically thin arrays of metallic antennas on silicon with a linear phase variation along the interface, which are in excellent agreement with generalized laws derived from Fermat's principle. Phase discontinuities provide great flexibility in the design of light beams, as illustrated by the generation of optical vortices through use of planar designer metallic interfaces.

ARGALI: an automatic cup-to-disc ratio measurement system for glaucoma detection and AnaLysIs framework

NASA Astrophysics Data System (ADS)

Liu, J.; Wong, D. W. K.; Lim, J. H.; Li, H.; Tan, N. M.; Wong, T. Y.

2009-02-01

Glaucoma is an irreversible ocular disease leading to permanent blindness. However, early detection can be effective in slowing or halting the progression of the disease. Physiologically, glaucoma progression is quantified by increased excavation of the optic cup. This progression can be quantified in retinal fundus images via the optic cup to disc ratio (CDR), since in increased glaucomatous neuropathy, the relative size of the optic cup to the optic disc is increased. The ARGALI framework constitutes of various segmentation approaches employing level set, color intensity thresholds and ellipse fitting for the extraction of the optic cup and disc from retinal images as preliminary steps. Following this, different combinations of the obtained results are then utilized to calculate the corresponding CDR values. The individual results are subsequently fused using a neural network. The learning function of the neural network is trained with a set of 100 retinal images For testing, a separate set 40 images is then used to compare the obtained CDR against a clinically graded CDR, and it is shown that the neural network-based result performs better than the individual components, with 96% of the results within intra-observer variability. The results indicate good promise for the further development of ARGALI as a tool for the early detection of glaucoma.

Spatial frequency domain spectroscopy of two layer media

NASA Astrophysics Data System (ADS)

Yudovsky, Dmitry; Durkin, Anthony J.

2011-10-01

Monitoring of tissue blood volume and oxygen saturation using biomedical optics techniques has the potential to inform the assessment of tissue health, healing, and dysfunction. These quantities are typically estimated from the contribution of oxyhemoglobin and deoxyhemoglobin to the absorption spectrum of the dermis. However, estimation of blood related absorption in superficial tissue such as the skin can be confounded by the strong absorption of melanin in the epidermis. Furthermore, epidermal thickness and pigmentation varies with anatomic location, race, gender, and degree of disease progression. This study describes a technique for decoupling the effect of melanin absorption in the epidermis from blood absorption in the dermis for a large range of skin types and thicknesses. An artificial neural network was used to map input optical properties to spatial frequency domain diffuse reflectance of two layer media. Then, iterative fitting was used to determine the optical properties from simulated spatial frequency domain diffuse reflectance. Additionally, an artificial neural network was trained to directly map spatial frequency domain reflectance to sets of optical properties of a two layer medium, thus bypassing the need for iteration. In both cases, the optical thickness of the epidermis and absorption and reduced scattering coefficients of the dermis were determined independently. The accuracy and efficiency of the iterative fitting approach was compared with the direct neural network inversion.

Preparing for Future Learning with a Tangible User Interface: The Case of Neuroscience

ERIC Educational Resources Information Center

Schneider, B.; Wallace, J.; Blikstein, P.; Pea, R.

2013-01-01

In this paper, we describe the development and evaluation of a microworld-based learning environment for neuroscience. Our system, BrainExplorer, allows students to discover the way neural pathways work by interacting with a tangible user interface. By severing and reconfiguring connections, users can observe how the visual field is impaired and,…

Optical data transmission technology for fixed and drag-on STS payloads umbilicals. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

St.denis, R. W.

1981-01-01

The feasibility of using optical data handling methods to transmit payload checkout and telemetry is discussed. Optical communications are superior to conventional communication systems for the following reasons: high data capacity optical channels; small and light weight optical cables; and optical signal immunity to electromagnetic interference. Task number one analyzed the ground checkout data requirements that may be expected from the payload community. Task number two selected the optical approach based on the interface requirements, the location of the interface, the amount of time required to reconfigure hardware, and the method of transporting the optical signal. Task number three surveyed and selected optical components for the two payload data link. Task number four makes a qualitative comparison of the conventional electrical communication system and the proposed optical communication system.

Neural interfaces for control of upper limb prostheses: the state of the art and future possibilities.

PubMed

Schultz, Aimee E; Kuiken, Todd A

2011-01-01

Current treatment of upper limb amputation restores some degree of functional ability, but this ability falls far below the standard set by the natural arm. Although acceptance rates can be high when patients are highly motivated and receive proper training and care, current prostheses often fail to meet the daily needs of amputees and frequently are abandoned. Recent advancements in science and technology have led to promising methods of accessing neural information for communication or control. Researchers have explored invasive and noninvasive methods of connecting with muscles, nerves, or the brain to provide increased functionality for patients experiencing disease or injury, including amputation. These techniques offer hope of more natural and intuitive prosthesis control, and therefore increased quality of life for amputees. In this review, we discuss the current state of the art of neural interfaces, particularly those that may find application within the prosthetics field. Copyright © 2011 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

Analyzing large-scale spiking neural data with HRLAnalysis™

PubMed Central

Thibeault, Corey M.; O'Brien, Michael J.; Srinivasa, Narayan

2014-01-01

The additional capabilities provided by high-performance neural simulation environments and modern computing hardware has allowed for the modeling of increasingly larger spiking neural networks. This is important for exploring more anatomically detailed networks but the corresponding accumulation in data can make analyzing the results of these simulations difficult. This is further compounded by the fact that many existing analysis packages were not developed with large spiking data sets in mind. Presented here is a software suite developed to not only process the increased amount of spike-train data in a reasonable amount of time, but also provide a user friendly Python interface. We describe the design considerations, implementation and features of the HRLAnalysis™ suite. In addition, performance benchmarks demonstrating the speedup of this design compared to a published Python implementation are also presented. The result is a high-performance analysis toolkit that is not only usable and readily extensible, but also straightforward to interface with existing Python modules. PMID:24634655

Operant conditioning of a multiple degree-of-freedom brain-machine interface in a primate model of amputation.

PubMed

Balasubramanian, Karthikeyan; Southerland, Joshua; Vaidya, Mukta; Qian, Kai; Eleryan, Ahmed; Fagg, Andrew H; Sluzky, Marc; Oweiss, Karim; Hatsopoulos, Nicholas

2013-01-01

Operant conditioning with biofeedback has been shown to be an effective method to modify neural activity to generate goal-directed actions in a brain-machine interface. It is particularly useful when neural activity cannot be mathematically mapped to motor actions of the actual body such as in the case of amputation. Here, we implement an operant conditioning approach with visual feedback in which an amputated monkey is trained to control a multiple degree-of-freedom robot to perform a reach-to-grasp behavior. A key innovation is that each controlled dimension represents a behaviorally relevant synergy among a set of joint degrees-of-freedom. We present a number of behavioral metrics by which to assess improvements in BMI control with exposure to the system. The use of non-human primates with chronic amputation is arguably the most clinically-relevant model of human amputation that could have direct implications for developing a neural prosthesis to treat humans with missing upper limbs.

Hybrid multiphoton volumetric functional imaging of large-scale bioengineered neuronal networks

NASA Astrophysics Data System (ADS)

Dana, Hod; Marom, Anat; Paluch, Shir; Dvorkin, Roman; Brosh, Inbar; Shoham, Shy

2014-06-01

Planar neural networks and interfaces serve as versatile in vitro models of central nervous system physiology, but adaptations of related methods to three dimensions (3D) have met with limited success. Here, we demonstrate for the first time volumetric functional imaging in a bioengineered neural tissue growing in a transparent hydrogel with cortical cellular and synaptic densities, by introducing complementary new developments in nonlinear microscopy and neural tissue engineering. Our system uses a novel hybrid multiphoton microscope design combining a 3D scanning-line temporal-focusing subsystem and a conventional laser-scanning multiphoton microscope to provide functional and structural volumetric imaging capabilities: dense microscopic 3D sampling at tens of volumes per second of structures with mm-scale dimensions containing a network of over 1,000 developing cells with complex spontaneous activity patterns. These developments open new opportunities for large-scale neuronal interfacing and for applications of 3D engineered networks ranging from basic neuroscience to the screening of neuroactive substances.

Cell death in neural precursor cells and neurons before neurite formation prevents the emergence of abnormal neural structures in the Drosophila optic lobe.

PubMed

Hara, Yusuke; Sudo, Tatsuya; Togane, Yu; Akagawa, Hiromi; Tsujimura, Hidenobu

2018-04-01

Programmed cell death is a conserved strategy for neural development both in vertebrates and invertebrates and is recognized at various developmental stages in the brain from neurogenesis to adulthood. To understand the development of the central nervous system, it is essential to reveal not only molecular mechanisms but also the role of neural cell death (Pinto-Teixeira et al., 2016). To understand the role of cell death in neural development, we investigated the effect of inhibition of cell death on optic lobe development. Our data demonstrate that, in the optic lobe of Drosophila, cell death occurs in neural precursor cells and neurons before neurite formation and functions to prevent various developmental abnormalities. When neuronal cell death was inhibited by an effector caspase inhibitor, p35, multiple abnormal neuropil structures arose during optic lobe development-e.g., enlarged or fused neuropils, misrouted neurons and abnormal neurite lumps. Inhibition of cell death also induced morphogenetic defects in the lamina and medulla development-e.g., failures in the separation of the lamina and medulla cortices and the medulla rotation. These defects were reproduced in the mutant of an initiator caspase, dronc. If cell death was a mechanism for removing the abnormal neuropil structures, we would also expect to observe them in mutants defective for corpse clearance. However, they were not observed in these mutants. When dead cell-membranes were visualized with Apoliner, they were observed only in cortices and not in neuropils. These results suggest that the cell death occurs before mature neurite formation. Moreover, we found that inhibition of cell death induced ectopic neuroepithelial cells, neuroblasts and ganglion mother cells in late pupal stages, at sites where the outer and inner proliferation centers were located at earlier developmental stages. Caspase-3 activation was observed in the neuroepithelial cells and neuroblasts in the proliferation centers. These results indicate that cell death is required for elimination of the precursor cells composing the proliferation centers. This study substantiates an essential role of early neural cell death for ensuring normal development of the central nervous system. Copyright © 2018 Elsevier Inc. All rights reserved.

A stereo-compound hybrid microscope for combined intracellular and optical recording of invertebrate neural network activity

PubMed Central

Frost, William N.; Wang, Jean; Brandon, Christopher J.

2007-01-01

Optical recording studies of invertebrate neural networks with voltage-sensitive dyes seldom employ conventional intracellular electrodes. This may in part be due to the traditional reliance on compound microscopes for such work. While such microscopes have high light-gathering power, they do not provide depth of field, making working with sharp electrodes difficult. Here we describe a hybrid microscope design, with switchable compound and stereo objectives, that eases the use of conventional intracellular electrodes in optical recording experiments. We use it, in combination with a voltage-sensitive dye and photodiode array, to identify neurons participating in the swim motor program of the marine mollusk Tritonia. This microscope design should be applicable to optical recording studies in many preparations. PMID:17306887

Multi-interface level in oil tanks and applications of optical fiber sensors

NASA Astrophysics Data System (ADS)

Leal-Junior, Arnaldo G.; Marques, Carlos; Frizera, Anselmo; Pontes, Maria José

2018-01-01

On the oil production also involves the production of water, gas and suspended solids, which are separated from the oil on three-phase separators. However, the control strategies of an oil separator are limited due to unavailability of suitable multi-interface level sensors. This paper presents a description of the multi-phase level problem on the oil industry and a review of the current technologies for multi-interface level assessment. Since optical fiber sensors present chemical stability, intrinsic safety, electromagnetic immunity, lightweight and multiplexing capabilities, it can be an alternative for multi-interface level measurement that can overcome some of the limitations of the current technologies. For this reason, Fiber Bragg Gratings (FBGs) based optical fiber sensor system for multi-interface level assessment is proposed, simulated and experimentally assessed. The results show that the proposed sensor system is capable of measuring interface level with a relative error of only 2.38%. Furthermore, the proposed sensor system is also capable of measuring the oil density with an error of 0.8 kg/m3.

Tunable vertical-cavity surface-emitting laser with feedback to implement a pulsed neural model. 1. Principles and experimental demonstration.

PubMed

Romariz, Alexandre R S; Wagner, Kelvin H

2007-07-20

An optoelectronic implementation of a modified FitzHugh-Nagumo neuron model is proposed, analyzed, and experimentally demonstrated. The setup uses linear optics and linear electronics for implementing an optical wavelength-domain nonlinearity. The system attains instability through a bifurcation mechanism present in a class of neuron models, a fact that is shown analytically. The implementation exhibits basic features of neural dynamics including threshold, production of short pulses (or spikes), and refractoriness.

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.

Interface Magnetoelectric Coupling in Co/Pb(Zr,Ti)O3.

PubMed

Vlašín, Ondřej; Jarrier, Romain; Arras, Rémi; Calmels, Lionel; Warot-Fonrose, Bénédicte; Marcelot, Cécile; Jamet, Matthieu; Ohresser, Philippe; Scheurer, Fabrice; Hertel, Riccardo; Herranz, Gervasi; Cherifi-Hertel, Salia

2016-03-23

Magnetoelectric coupling at multiferroic interfaces is a promising route toward the nonvolatile electric-field control of magnetization. Here, we use optical measurements to study the static and dynamic variations of the interface magnetization induced by an electric field in Co/PbZr0.2Ti0.8O3 (Co/PZT) bilayers at room temperature. The measurements allow us to identify different coupling mechanisms. We further investigate the local electronic and magnetic structure of the interface by means of transmission electron microscopy, soft X-ray magnetic circular dichroism, and density functional theory to corroborate the coupling mechanism. The measurements demonstrate a mixed linear and quadratic optical response to the electric field, which results from a magneto-electro-optical effect. We propose a decomposition method of the optical signal to discriminate between different components involved in the electric field-induced polarization rotation of the reflected light. This allows us to extract a signal that we can ascribe to interface magnetoelectric coupling. The associated surface magnetization exhibits a clear hysteretic variation of odd symmetry with respect to the electric field and nonzero remanence. The interface coupling is remarkably stable over a wide frequency range (1-50 kHz), and the application of a bias magnetic field is not necessary for the coupling to occur. These results show the potential of exploiting interface coupling with the prospect of optimizing the performance of magnetoelectric memory devices in terms of stability, as well as fast and dissipationless operation.

A USB 2.0 computer interface for the UCO/Lick CCD cameras

NASA Astrophysics Data System (ADS)

Wei, Mingzhi; Stover, Richard J.

2004-09-01

The new UCO/Lick Observatory CCD camera uses a 200 MHz fiber optic cable to transmit image data and an RS232 serial line for low speed bidirectional command and control. Increasingly RS232 is a legacy interface supported on fewer computers. The fiber optic cable requires either a custom interface board that is plugged into the mainboard of the image acquisition computer to accept the fiber directly or an interface converter that translates the fiber data onto a widely used standard interface. We present here a simple USB 2.0 interface for the UCO/Lick camera. A single USB cable connects to the image acquisition computer and the camera's RS232 serial and fiber optic cables plug into the USB interface. Since most computers now support USB 2.0 the Lick interface makes it possible to use the camera on essentially any modern computer that has the supporting software. No hardware modifications or additions to the computer are needed. The necessary device driver software has been written for the Linux operating system which is now widely used at Lick Observatory. The complete data acquisition software for the Lick CCD camera is running on a variety of PC style computers as well as an HP laptop.

Genetically Targeted All-Optical Electrophysiology with a Transgenic Cre-Dependent Optopatch Mouse

PubMed Central

Lou, Shan; Adam, Yoav; Weinstein, Eli N.; Williams, Erika; Williams, Katherine; Parot, Vicente; Kavokine, Nikita; Liberles, Stephen; Madisen, Linda; Zeng, Hongkui

2016-01-01

Recent advances in optogenetics have enabled simultaneous optical perturbation and optical readout of membrane potential in diverse cell types. Here, we develop and characterize a Cre-dependent transgenic Optopatch2 mouse line that we call Floxopatch. The animals expressed a blue-shifted channelrhodopsin, CheRiff, and a near infrared Archaerhodopsin-derived voltage indicator, QuasAr2, via targeted knock-in at the rosa26 locus. In Optopatch-expressing animals, we tested for overall health, genetically targeted expression, and function of the optogenetic components. In offspring of Floxopatch mice crossed with a variety of Cre driver lines, we observed spontaneous and optically evoked activity in vitro in acute brain slices and in vivo in somatosensory ganglia. Cell-type-specific expression allowed classification and characterization of neuronal subtypes based on their firing patterns. The Floxopatch mouse line is a useful tool for fast and sensitive characterization of neural activity in genetically specified cell types in intact tissue. SIGNIFICANCE STATEMENT Optical recordings of neural activity offer the promise of rapid and spatially resolved mapping of neural function. Calcium imaging has been widely applied in this mode, but is insensitive to the details of action potential waveforms and subthreshold events. Simultaneous optical perturbation and optical readout of single-cell electrical activity (“Optopatch”) has been demonstrated in cultured neurons and in organotypic brain slices, but not in acute brain slices or in vivo. Here, we describe a transgenic mouse in which expression of Optopatch constructs is controlled by the Cre-recombinase enzyme. This animal enables fast and robust optical measurements of single-cell electrical excitability in acute brain slices and in somatosensory ganglia in vivo, opening the door to rapid optical mapping of neuronal excitability. PMID:27798186

Quantitative first-principles theory of interface absorption in multilayer heterostructures

DOE PAGES

Hachtel, Jordan A.; Sachan, Ritesh; Mishra, Rohan; ...

2015-09-03

The unique chemical bonds and electronic states of interfaces result in optical properties that are different from those of the constituting bulk materials. In the nanoscale regime, the interface effects can be dominant and impact the optical response of devices. Using density functional theory (DFT), the interface effects can be calculated, but DFT is computationally limited to small systems. In this paper, we describe a method to combine DFT with macroscopic methodologies to extract the interface effect on absorption in a consistent and quantifiable manner. The extracted interface effects are an independent parameter and can be applied to more complicatedmore » systems. Finally, we demonstrate, using NiSi 2/Si heterostructures, that by varying the relative volume fractions of interface and bulk, we can tune the spectral range of the heterostructure absorption.« less

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

Optical neural network system for pose determination of spinning satellites

NASA Technical Reports Server (NTRS)

Lee, Andrew; Casasent, David

1990-01-01

An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.

Optical to optical interface device

NASA Technical Reports Server (NTRS)

Oliver, D. S.; Vohl, P.; Nisenson, P.

1972-01-01

The development, fabrication, and testing of a preliminary model of an optical-to-optical (noncoherent-to-coherent) interface device for use in coherent optical parallel processing systems are described. The developed device demonstrates a capability for accepting as an input a scene illuminated by a noncoherent radiation source and providing as an output a coherent light beam spatially modulated to represent the original noncoherent scene. The converter device developed under this contract employs a Pockels readout optical modulator (PROM). This is a photosensitive electro-optic element which can sense and electrostatically store optical images. The stored images can be simultaneously or subsequently readout optically by utilizing the electrostatic storage pattern to control an electro-optic light modulating property of the PROM. The readout process is parallel as no scanning mechanism is required. The PROM provides the functions of optical image sensing, modulation, and storage in a single active material.

Analytical study of acousto/optical holography-interfacing methods for acoustical and optical holography NDT research

NASA Technical Reports Server (NTRS)

El-Sum, H. M. A.

1976-01-01

The international status of the art of acousto optical imaging techniques adaptable to nondestructive testing and, interfacing methods for acoustical and optical holography in nondestructive testing research are studied. Evaluation of 20 different techniques encompassed investigation of varieties of detectors and detection schemes, all of which are described and summarized. Related investigation is reported in an Appendix. Important remarks on image quality, factors to be considered in designing a particular system, and conclusions and recommendations are presented. Three bibliographies are included.

Design of a Closed-Loop, Bidirectional Brain Machine Interface System With Energy Efficient Neural Feature Extraction and PID Control.

PubMed

Liu, Xilin; Zhang, Milin; Richardson, Andrew G; Lucas, Timothy H; Van der Spiegel, Jan

2017-08-01

This paper presents a bidirectional brain machine interface (BMI) microsystem designed for closed-loop neuroscience research, especially experiments in freely behaving animals. The system-on-chip (SoC) consists of 16-channel neural recording front-ends, neural feature extraction units, 16-channel programmable neural stimulator back-ends, in-channel programmable closed-loop controllers, global analog-digital converters (ADC), and peripheral circuits. The proposed neural feature extraction units includes 1) an ultra low-power neural energy extraction unit enabling a 64-step natural logarithmic domain frequency tuning, and 2) a current-mode action potential (AP) detection unit with time-amplitude window discriminator. A programmable proportional-integral-derivative (PID) controller has been integrated in each channel enabling a various of closed-loop operations. The implemented ADCs include a 10-bit voltage-mode successive approximation register (SAR) ADC for the digitization of the neural feature outputs and/or local field potential (LFP) outputs, and an 8-bit current-mode SAR ADC for the digitization of the action potential outputs. The multi-mode stimulator can be programmed to perform monopolar or bipolar, symmetrical or asymmetrical charge balanced stimulation with a maximum current of 4 mA in an arbitrary channel configuration. The chip has been fabricated in 0.18 μ m CMOS technology, occupying a silicon area of 3.7 mm 2 . The chip dissipates 56 μW/ch on average. General purpose low-power microcontroller with Bluetooth module are integrated in the system to provide wireless link and SoC configuration. Methods, circuit techniques and system topology proposed in this work can be used in a wide range of relevant neurophysiology research, especially closed-loop BMI experiments.

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.

Wide-field Imaging System and Rapid Direction of Optical Zoom (WOZ)

DTIC Science & Technology

2010-09-25

commercial software packages: SolidWorks, COMSOL Multiphysics, and ZEMAX optical design. SolidWorks is a computer aided design package, which as a live...interface to COMSOL. COMSOL is a finite element analysis/partial differential equation solver. ZEMAX is an optical design package. Both COMSOL and... ZEMAX have live interfaces to MatLab. Our initial investigations have enabled a model in SolidWorks to be updated in COMSOL, an FEA calculation

Neurosurgery and the dawning age of Brain-Machine Interfaces

PubMed Central

Rowland, Nathan C.; Breshears, Jonathan; Chang, Edward F.

2013-01-01

Brain–machine interfaces (BMIs) are on the horizon for clinical neurosurgery. Electrocorticography-based platforms are less invasive than implanted microelectrodes, however, the latter are unmatched in their ability to achieve fine motor control of a robotic prosthesis capable of natural human behaviors. These technologies will be crucial to restoring neural function to a large population of patients with severe neurologic impairment – including those with spinal cord injury, stroke, limb amputation, and disabling neuromuscular disorders such as amyotrophic lateral sclerosis. On the opposite end of the spectrum are neural enhancement technologies for specialized applications such as combat. An ongoing ethical dialogue is imminent as we prepare for BMI platforms to enter the neurosurgical realm of clinical management. PMID:23653884

Progress Toward Adaptive Integration and Optimization of Automated and Neural Processing Systems: Establishing Neural and Behavioral Benchmarks of Optimized Performance

DTIC Science & Technology

2014-11-01

Paradigm ............................................................................19 3.4 Collaborative BCI for Improving Overall Performance...interfaces ( BCIs ) provide the biggest improvement in performance? Can we demonstrate clear advantages with BCIs ? 2 2. Simulator Development and...stimuli in real time. Fig. 18 ROC curves for each subject after the combination of 2 trials 3.4 Collaborative BCI for Improving Overall

The eye limits the brain's learning potential

PubMed Central

Zhou, Jiawei; Zhang, Yudong; Dai, Yun; Zhao, Haoxin; Liu, Rong; Hou, Fang; Liang, Bo; Hess, Robert F.; Zhou, Yifeng

2012-01-01

The concept of a critical period for visual development early in life during which sensory experience is essential to normal neural development is now well established. However recent evidence suggests that a limited degree of plasticity remains after this period and well into adulthood. Here, we ask the question, "what limits the degree of plasticity in adulthood?" Although this limit has been assumed to be due to neural factors, we show that the optical quality of the retinal image ultimately limits the brain potential for change. We correct the high-order aberrations (HOAs) normally present in the eye's optics using adaptive optics, and reveal a greater degree of neuronal plasticity than previously appreciated. PMID:22509464

Nanophotonic particle simulation and inverse design using artificial neural networks.

PubMed

Peurifoy, John; Shen, Yichen; Jing, Li; Yang, Yi; Cano-Renteria, Fidel; DeLacy, Brendan G; Joannopoulos, John D; Tegmark, Max; Soljačić, Marin

2018-06-01

We propose a method to use artificial neural networks to approximate light scattering by multilayer nanoparticles. We find that the network needs to be trained on only a small sampling of the data to approximate the simulation to high precision. Once the neural network is trained, it can simulate such optical processes orders of magnitude faster than conventional simulations. Furthermore, the trained neural network can be used to solve nanophotonic inverse design problems by using back propagation, where the gradient is analytical, not numerical.

Optical actuators for fly-by-light applications

NASA Astrophysics Data System (ADS)

Chee, Sonny H. S.; Liu, Kexing; Measures, Raymond M.

1993-04-01

A review of optomechanical interfaces is presented. A detailed quantitative and qualitative analysis of the University of Toronto Institute for Aerospace Studies (UTIAS) box, optopneumatics, optical activation of a bimetal, optical activation of the shape memory effect, and optical activation of the pyroelectric effects is given. The UTIAS box is found to display a good conversion efficiency and a high bandwidth. A preliminary UTIAS box design has achieved a conversion efficiency of about 1/6 of the theoretical limit and a bandwidth of 2 Hz. In comparison to previous optomechanical interfaces, the UTIAS box has the highest pressure development to optical power ratio (at least an order of magnitude greater).

In−Vitro and In−Vivo Noise Analysis for Optical Neural Recording

PubMed Central

Foust, Amanda J.; Schei, Jennifer L.; Rojas, Manuel J.; Rector, David M.

2008-01-01

Laser diodes (LD) are commonly used for optical neural recordings in chronically recorded animals and humans, primarily due to their brightness and small size. However, noise introduced by LDs may counteract the benefits of brightness when compared to low−noise light emitting diodes (LEDs). To understand noise sources in optical recordings, we systematically compared instrument and physiological noise profiles in two recording paradigms. A better understanding of noise sources will help improve optical recordings and make them more practical with fewer averages. We stimulated lobster nerves and rat cortex, then compared the root mean square (RMS) noise and signal−to−noise ratios (SNRs) of data obtained with LED, superluminescent diode (SLD) and LD illumination for different numbers of averages. The LED data exhibited significantly higher SNRs in fewer averages than LD data in all recordings. In the absence of tissue, LED noise increased linearly with intensity, while LD noise increased sharply in the transition to lasing and settled to noise levels significantly higher than the LED’s, suggesting that speckle noise contributed to the LD’s higher noise and lower SNRs. Our data recommend low coherence and portable light sources for in−vivo chronic neural recording applications. PMID:19021365

Optical distortion correction of a liquid-gas interface and contact angle in cylindrical tubes

NASA Astrophysics Data System (ADS)

Darzi, Milad; Park, Chanwoo

2017-05-01

Objects inside cylindrical tubes appear distorted as seen outside the tube due to the refraction of the light passing through different media. Such an optical distortion may cause significant errors in geometrical measurements using optical observations of objects (e.g., liquid-gas interfaces, solid particles, gas bubbles) inside the tubes. In this study, an analytical method using a point-by-point correction of the optical distortion was developed. For an experimental validation, the method was used to correct the apparent profiles of the water-air interfaces (menisci) in cylindrical glass tubes with different tube diameters and wall thicknesses. Then, the corrected meniscus profiles were used to calculate the corrected static contact angles. The corrected contact angle shows an excellent agreement with the reference contact angles as compared to the conventional contact angle measurement using apparent meniscus profiles.

Enhancing Nervous System Recovery through Neurobiologics, Neural Interface Training, and Neurorehabilitation

PubMed Central

Krucoff, Max O.; Rahimpour, Shervin; Slutzky, Marc W.; Edgerton, V. Reggie; Turner, Dennis A.

2016-01-01

After an initial period of recovery, human neurological injury has long been thought to be static. In order to improve quality of life for those suffering from stroke, spinal cord injury, or traumatic brain injury, researchers have been working to restore the nervous system and reduce neurological deficits through a number of mechanisms. For example, neurobiologists have been identifying and manipulating components of the intra- and extracellular milieu to alter the regenerative potential of neurons, neuro-engineers have been producing brain-machine and neural interfaces that circumvent lesions to restore functionality, and neurorehabilitation experts have been developing new ways to revitalize the nervous system even in chronic disease. While each of these areas holds promise, their individual paths to clinical relevance remain difficult. Nonetheless, these methods are now able to synergistically enhance recovery of native motor function to levels which were previously believed to be impossible. Furthermore, such recovery can even persist after training, and for the first time there is evidence of functional axonal regrowth and rewiring in the central nervous system of animal models. To attain this type of regeneration, rehabilitation paradigms that pair cortically-based intent with activation of affected circuits and positive neurofeedback appear to be required—a phenomenon which raises new and far reaching questions about the underlying relationship between conscious action and neural repair. For this reason, we argue that multi-modal therapy will be necessary to facilitate a truly robust recovery, and that the success of investigational microscopic techniques may depend on their integration into macroscopic frameworks that include task-based neurorehabilitation. We further identify critical components of future neural repair strategies and explore the most updated knowledge, progress, and challenges in the fields of cellular neuronal repair, neural interfacing, and neurorehabilitation, all with the goal of better understanding neurological injury and how to improve recovery. PMID:28082858

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.

Microelectrodes with Three-Dimensional Structures for Improved Neural Interfacing

DTIC Science & Technology

2001-10-25

highly xible bio-interfaces [2]. Polyimides combine excellent ectrical and mechanical characteristics with biocompatibility ], and are well known in...excellent biocompatibility , polyimide -based electrodes promise for fabrication of long-term implants for the use in prostheses. The flexible structures...R. R. Richardson, J. A. Miller, and W. M. Reichert, " Polyimides as Biomaterials - Preliminary Biocompatibility Testing," Biomaterials, vol. 14, pp

Classification of Magneto-Optic Images using Neural Networks

NASA Technical Reports Server (NTRS)

Nath, Shridhar; Wincheski, Buzz; Fulton, Jim; Namkung, Min

1994-01-01

A real time imaging system with a neural network classifier has been incorporated on a Macintosh computer in conjunction with an MOI system. This system images rivets on aircraft aluminium structures using eddy currents and magnetic imaging. Moment invariant functions from the image of a rivet is used to train a multilayer perceptron neural network to classify the rivets as good or bad (rivets with cracks).

Acute damage threshold for infrared neural stimulation of the cochlea: functional and histological evaluation.

PubMed

Goyal, Vinay; Rajguru, Suhrud; Matic, Agnella I; Stock, Stuart R; Richter, Claus-Peter

2012-11-01

This article provides a mini review of the current state of infrared neural stimulation (INS), and new experimental results concerning INS damage thresholds. INS promises to be an attractive alternative for neural interfaces. With this method, one can attain spatially selective neural stimulation that is not possible with electrical stimulation. INS is based on the delivery of short laser pulses that result in a transient temperature increase in the tissue and depolarize the neurons. At a high stimulation rate and/or high pulse energy, the method bears the risk of thermal damage to the tissue from the instantaneous temperature increase or from potential accumulation of thermal energy. With the present study, we determined the injury thresholds in guinea pig cochleae for acute INS using functional measurements (compound action potentials) and histological evaluation. The selected laser parameters for INS were the wavelength (λ = 1,869 nm), the pulse duration (100 μs), the pulse repetition rate (250 Hz), and the radiant energy (0-127 μJ/pulse). For up to 5 hr of continuous irradiation at 250 Hz and at radiant energies up to 25 μJ/pulse, we did not observe any functional or histological damage in the cochlea. Functional loss was observed for energies above 25 μJ/pulse and the probability of injury to the target tissue resulting in functional loss increased with increasing radiant energy. Corresponding cochlear histology from control animals and animals exposed to 98 or 127 μJ/pulse at 250 Hz pulse repetition rate did not show a loss of spiral ganglion cells, hair cells, or other soft tissue structures of the organ of Corti. Light microscopy did not reveal any structural changes in the soft tissue either. Additionally, microcomputed tomography was used to visualize the placement of the optical fiber within the cochlea. Copyright © 2012 Wiley Periodicals, Inc.

FAST TRACK COMMUNICATION Spectral signatures of the surface reconstructions of Au(110)/electrolyte interfaces

NASA Astrophysics Data System (ADS)

Smith, C. I.; Bowfield, A.; Almond, N. J.; Mansley, C. P.; Convery, J. H.; Weightman, P.

2010-10-01

It is demonstrated that the (1 × 1) structure and the (1 × 2) and (1 × 3) surface reconstructions that occur at Au(110)/electrolyte interfaces have unique optical fingerprints. The optical fingerprints are potential, pH and anion dependent and have potential for use in monitoring dynamic changes at this interface. We also observe a specific reflection anisotropy spectroscopy signature that may arise from anions adsorbed on the (1 × 1) structure of Au(110).

Dlx proteins position the neural plate border and determine adjacent cell fates

PubMed Central

Woda, Juliana M.; Pastagia, Julie; Mercola, Mark; Artinger, Kristin Bruk

2014-01-01

Summary The lateral border of the neural plate is a major source of signals that induce primary neurons, neural crest cells and cranial placodes as well as provide patterning cues to mesodermal structures such as somites and heart. Whereas secreted BMP, FGF and Wnt proteins influence the differentiation of neural and non-neural ectoderm, we show here that members of the Dlx family of transcription factors position the border between neural and non-neural ectoderm and are required for the specification of adjacent cell fates. Inhibition of endogenous Dlx activity in Xenopus embryos with an EnR-Dlx homeodomain fusion protein expands the neural plate into non-neural ectoderm tissue whereas ectopic activation of Dlx target genes inhibits neural plate differentiation. Importantly, the stereotypic pattern of border cell fates in the adjacent ectoderm is re-established only under conditions where the expanded neural plate abuts Dlx-positive non-neural ectoderm. Experiments in which presumptive neural plate was grafted to ventral ectoderm reiterate induction of neural crest and placodal lineages and also demonstrate that Dlx activity is required in non-neural ectoderm for the production of signals needed for induction of these cells. We propose that Dlx proteins regulate intercellular signaling across the interface between neural and non-neural ectoderm that is critical for inducing and patterning adjacent cell fates. PMID:12466200

An optical disk archive for a data base management system

NASA Technical Reports Server (NTRS)

Thomas, Douglas T.

1985-01-01

An overview is given of a data base management system that can catalog and archive data at rates up to 50M bits/sec. Emphasis is on the laser disk system that is used for the archive. All key components in the system (3 Vax 11/780s, a SEL 32/2750, a high speed communication interface, and the optical disk) are interfaced to a 100M bits/sec 16-port fiber optic bus to achieve the high data rates. The basic data unit is an autonomous data packet. Each packet contains a primary and secondary header and can be up to a million bits in length. The data packets are recorded on the optical disk at the same time the packet headers are being used by the relational data base management software ORACLE to create a directory independent of the packet recording process. The user then interfaces to the VAX that contains the directory for a quick-look scan or retrieval of the packet(s). The total system functions are distributed between the VAX and the SEL. The optical disk unit records the data with an argon laser at 100M bits/sec from its buffer, which is interfaced to the fiber optic bus. The same laser is used in the read cycle by reducing the laser power. Additional information is given in the form of outlines, charts, and diagrams.

Interfacing Optical Document Scanners: Principles and Practical Considerations.

ERIC Educational Resources Information Center

Krus, David J.; Kodimer, Dennis

1987-01-01

Handlers for interfacing the ScanTron and 2700 Optical Mark Readers with the IBM AT/XT/PC and Tandy 2000/1000/3000 iAPX 88/186/286 based computers were described. Differences between programing an RS232C serial port using BIOS interrupts and directly addressing the Motorola 8550 ART microprocessor were discussed. (Author/LMO)

Designing and Using an Open Graphic Interface for Instruction in Geometrical Optics.

ERIC Educational Resources Information Center

Ronen, Miky; And Others

1993-01-01

Discusses conceptual difficulties in the field of geometrical optics and describes RAY, a microcomputer-based graphic interface that was designed to serve as a teaching aid and as a learning environment. The ability to combine theory and formal representations with real demonstrations and experiments is discussed. (Contains seven references.) (LRW)

Optical digital techniques

NASA Technical Reports Server (NTRS)

1979-01-01

Optical interface losses between transmitter-to-fiber interface, connector-to-connector interface, and fiber-to-receiver interface were studied. System effects such as pulse dispersion, risetimes of the sources and detectors, type of fibers used, output power of the sources, and detector sensitivity were considered. Data bus systems such as TEE, Star, and Hybrid were analyzed. The matter of single fiber versus bundle technologies for future avionics systems was considered. The existing data bus system on Space Shuttle was examined and an optical analog was derived for a fiber bundle system, along with the associated power margin. System tests were performed on a feasibility model of a 9-port Star data bus system including BER, star losses, connector losses, etc. The same system was subjected to EMI between the range of 200 Hz to 10 GHz at 20V/m levels. A lightning test was also performed which simulated the conditions similar to those on Space Shuttle. The data bus system was found to be EMI and lightning hard. It is concluded that an optical data bus system is feasible for shuttle orbiter type vehicles.

Dynamic Determination of Some Optical and Electrical Properties of Galena Natural Mineral: Potassium Ethyl Xanthate Solution Interface

NASA Astrophysics Data System (ADS)

Todoran, D.; Todoran, R.; Anitas, E. M.; Szakacs, Zs.

2017-12-01

This paper presents results concerning optical and electrical properties of galena natural mineral and of the interface layer formed between it and the potassium ethyl xanthate solution. The applied experimental method was differential optical reflectance spectroscopy over the UV-Vis/NIR spectral domain. Computations were made using the Kramers-Kronig formalism. Spectral dependencies of the electron loss functions, determined from the reflectance data obtained from the polished mineral surface, display van Hove singularities, leading to the determination of its valence band gap and electron plasma energy. Time dependent measurement of the spectral dispersion of the relative reflectance of the film formed at the interface, using the same computational formalism, leads to the dynamical determination of the spectral variation of its optical and electrical properties. We computed behaviors of the dielectric constant (dielectric permittivity), the dielectric loss function, refractive index and extinction coefficient, effective valence number and of the electron loss functions. The measurements tend to stabilize when the dynamic adsorption-desorption equilibrium is reached at the interface level.

Interface module for transverse energy input to dye laser modules

DOEpatents

English, R.E. Jr.; Johnson, S.A.

1994-10-11

An interface module for transverse energy input to dye laser modules is provided particularly for the purpose of delivering enhancing transverse energy beams in the form of illumination bar to the lasing zone of a dye laser device, in particular to a dye laser amplifier. The preferred interface module includes an optical fiber array having a plurality of optical fibers arrayed in a co-planar fashion with their distal ends receiving coherent laser energy from an enhancing laser source, and their proximal ends delivered into a relay structure. The proximal ends of the optical fibers are arrayed so as to be coplanar and to be aimed generally at a common point. The transverse energy beam array delivered from the optical fiber array is acted upon by an optical element array to produce an illumination bar which has a cross section in the form of a elongated rectangle at the position of the lasing window. The illumination bar is selected to have substantially uniform intensity throughout. 5 figs.

High voltage photo switch package module

DOEpatents

Sullivan, James S; Sanders, David M; Hawkins, Steven A; Sampayan, Stephen E

2014-02-18

A photo-conductive switch package module having a photo-conductive substrate or wafer with opposing electrode-interface surfaces, and at least one light-input surface. First metallic layers are formed on the electrode-interface surfaces, and one or more optical waveguides having input and output ends are bonded to the substrate so that the output end of each waveguide is bonded to a corresponding one of the light-input surfaces of the photo-conductive substrate. This forms a waveguide-substrate interface for coupling light into the photo-conductive wafer. A dielectric material such as epoxy is then used to encapsulate the photo-conductive substrate and optical waveguide so that only the metallic layers and the input end of the optical waveguide are exposed. Second metallic layers are then formed on the first metallic layers so that the waveguide-substrate interface is positioned under the second metallic layers.

High Speed All-Optical Data Distribution Network

NASA Astrophysics Data System (ADS)

Braun, Steve; Hodara, Henri

2017-11-01

This article describes the performance and capabilities of an all-optical network featuring low latency, high speed file transfer between serially connected optical nodes. A basic component of the network is a network interface card (NIC) implemented through a unique planar lightwave circuit (PLC) that performs add/drop data and optical signal amplification. The network uses a linear bus topology with nodes in a "T" configuration, as described in the text. The signal is sent optically (hence, no latency) to all nodes via wavelength division multiplexing (WDM), with each node receiver tuned to wavelength of choice via an optical de-multiplexer. Each "T" node routes a portion of the signal to/from the bus through optical couplers, embedded in the network interface card (NIC), to each of the 1 through n computers.

Short-wavelength infrared laser activates the auditory neurons: comparing the effect of 980 vs. 810 nm wavelength.

PubMed

Tian, Lan; Wang, Jingxuan; Wei, Ying; Lu, Jianren; Xu, Anting; Xia, Ming

2017-02-01

Research on auditory neural triggering by optical stimulus has been developed as an emerging technique to elicit the auditory neural response, which may provide an alternative method to the cochlear implants. However, most previous studies have been focused on using longer-wavelength near-infrared (>1800 nm) laser. The effect comparison of different laser wavelengths in short-wavelength infrared (SWIR) range on the auditory neural stimulation has not been previously explored. In this study, the pulsed 980- and 810-nm SWIR lasers were applied as optical stimuli to irradiate the auditory neurons in the cochlea of five deafened guinea pigs and the neural response under the two laser wavelengths was compared by recording the evoked optical auditory brainstem responses (OABRs). In addition, the effect of radiant exposure, laser pulse width, and threshold with the two laser wavelengths was further investigated and compared. The one-way analysis of variance (ANOVA) was used to analyze those data. Results showed that the OABR amplitude with the 980-nm laser is higher than the amplitude with the 810-nm laser under the same radiant exposure from 10 to 102 mJ/cm 2 . And the laser stimulation of 980 nm wavelength has lower threshold radiant exposure than the 810 nm wavelength at varied pulse duration in 20-500 μs range. Moreover, the 810-nm laser has a wider optimized pulse duration range than the 980-nm laser for the auditory neural stimulation.

Study of interface influence on bending performance of CFRP with embedded optical fibers

NASA Astrophysics Data System (ADS)

Liu, Rong-mei; Liang, Da-kai

2008-11-01

Studies showed that the bending strength of composite would be affected by embedded optical fibers. Interface strength between the embedded optical fiber and the matrix was studied in this paper. Based on the single fiber pull out tests, the interfacial shear strength between the coating and the clad is the weakest. The shear strength of the optical fiber used in this study is near to 0.8MPa. In order to study the interfacial effect on bending property of generic smart structure, a quasi-isotropic composite laminates were produced from Toray T300C/ epoxy prepreg. Optical fibers were embedded within different orientation plies of the plates, with the optical fibers embedded in the same direction. Accordingly, five different types of plates were produced. Impact tests were carried out on the 5 different plate types. It is shown that when the fiber was embedded at the upper layer, the bending strength drops mostly. The bending normal stress on material arrives at the maximum. So does the normal stress applied on the optical fiber at the surface. Therefore, destructions could originate at the interface between the coating and the clad foremost. The ultimate strength of the smart structure will be affected furthest.

Glass Solder Approach for Robust, Low-Loss, Fiber-to-Waveguide Coupling

NASA Technical Reports Server (NTRS)

McNeil, Shirley; Battle, Philip; Hawthorne, Todd; Lower, John; Wiley, Robert; Clark, Brett

2012-01-01

The key advantages of this approach include the fact that the index of interface glass (such as Pb glass n = 1.66) greatly reduces Fresnel losses at the fiber-to-waveguide interface, resulting in lower optical losses. A contiguous structure cannot be misaligned and readily lends itself for use on aircraft or space operation. The epoxy-free, fiber-to-waveguide interface provides an optically pure, sealed interface for low-loss, highpower coupling. Proof of concept of this approach has included successful attachment of the low-melting-temperature glass to the x-y plane of the crystal, successful attachment of the low-meltingtemperature glass to the end face of a standard SMF (single-mode fiber), and successful attachment of a wetted lowmelting- temperature glass SMF to the end face of a KTP crystal. There are many photonic components on the market whose performance and robustness could benefit from this coupling approach once fully developed. It can be used in a variety of fibercoupled waveguide-based components, such as frequency conversion modules, and amplitude and phase modulators. A robust, epoxy-free, contiguous optical interface lends itself to components that require low-loss, high-optical-power handling capability, and good performance in adverse environments such as flight or space operation.

Demonstration of adaptive optics for mitigating laser propagation through a random air-water interface

NASA Astrophysics Data System (ADS)

Land, Phillip; Majumdar, Arun K.

2016-05-01

This paper describes a new concept of mitigating signal distortions caused by random air-water interface using an adaptive optics (AO) system. This is the first time the concept of using an AO for mitigating the effects of distortions caused mainly by a random air-water interface is presented. We have demonstrated the feasibility of correcting the distortions using AO in a laboratory water tank for investigating the propagation effects of a laser beam through an airwater interface. The AO system consisting of a fast steering mirror, deformable mirror, and a Shack-Hartmann Wavefront Sensor for mitigating surface water distortions has a unique way of stabilizing and aiming a laser onto an object underneath the water. Essentially the AO system mathematically takes the complex conjugate of the random phase caused by air-water interface allowing the laser beam to penetrate through the water by cancelling with the complex conjugates. The results show the improvement of a number of metrics including Strehl ratio, a measure of the quality of optical image formation for diffraction limited optical system. These are the first results demonstrating the feasibility of developing a new sensor system such as Laser Doppler Vibrometer (LDV) utilizing AO for mitigating surface water distortions.

Optics in neural computation

NASA Astrophysics Data System (ADS)

Levene, Michael John

In all attempts to emulate the considerable powers of the brain, one is struck by both its immense size, parallelism, and complexity. While the fields of neural networks, artificial intelligence, and neuromorphic engineering have all attempted oversimplifications on the considerable complexity, all three can benefit from the inherent scalability and parallelism of optics. This thesis looks at specific aspects of three modes in which optics, and particularly volume holography, can play a part in neural computation. First, holography serves as the basis of highly-parallel correlators, which are the foundation of optical neural networks. The huge input capability of optical neural networks make them most useful for image processing and image recognition and tracking. These tasks benefit from the shift invariance of optical correlators. In this thesis, I analyze the capacity of correlators, and then present several techniques for controlling the amount of shift invariance. Of particular interest is the Fresnel correlator, in which the hologram is displaced from the Fourier plane. In this case, the amount of shift invariance is limited not just by the thickness of the hologram, but by the distance of the hologram from the Fourier plane. Second, volume holography can provide the huge storage capacity and high speed, parallel read-out necessary to support large artificial intelligence systems. However, previous methods for storing data in volume holograms have relied on awkward beam-steering or on as-yet non- existent cheap, wide-bandwidth, tunable laser sources. This thesis presents a new technique, shift multiplexing, which is capable of very high densities, but which has the advantage of a very simple implementation. In shift multiplexing, the reference wave consists of a focused spot a few millimeters in front of the hologram. Multiplexing is achieved by simply translating the hologram a few tens of microns or less. This thesis describes the theory for how shift multiplexing works based on an unconventional, but very intuitive, analysis of the optical far-field. A more detailed analysis based on a path-integral interpretation of the Born approximation is also derived. The capacity of shift multiplexing is compared with that of angle and wavelength multiplexing. The last part of this thesis deals with the role of optics in neuromorphic engineering. Up until now, most neuromorphic engineering has involved one or a few VLSI circuits emulating early sensory systems. However, optical interconnects will be required in order to push towards more ambitious goals, such as the simulation of early visual cortex. I describe a preliminary approach to designing such a system, and show how shift multiplexing can be used to simultaneously store and implement the immense interconnections required by such a project.

Deformable Surface Accommodating Intraocular Lens: Second Generation Prototype Design Methodology and Testing.

PubMed

McCafferty, Sean J; Schwiegerling, Jim T

2015-04-01

Present an analysis methodology for developing and evaluating accommodating intraocular lenses incorporating a deformable interface. The next generation design of extruded gel interface intraocular lens is presented. A prototype based upon similar previously in vivo proven design was tested with measurements of actuation force, lens power, interface contour, optical transfer function, and visual Strehl ratio. Prototype verified mathematical models were used to optimize optical and mechanical design parameters to maximize the image quality and minimize the required force to accommodate. The prototype lens produced adequate image quality with the available physiologic accommodating force. The iterative mathematical modeling based upon the prototype yielded maximized optical and mechanical performance through maximum allowable gel thickness to extrusion diameter ratio, maximum feasible refractive index change at the interface, and minimum gel material properties in Poisson's ratio and Young's modulus. The design prototype performed well. It operated within the physiologic constraints of the human eye including the force available for full accommodative amplitude using the eye's natural focusing feedback, while maintaining image quality in the space available. The parameters that optimized optical and mechanical performance were delineated as those, which minimize both asphericity and actuation pressure. The design parameters outlined herein can be used as a template to maximize the performance of a deformable interface intraocular lens. The article combines a multidisciplinary basic science approach from biomechanics, optical science, and ophthalmology to optimize an intraocular lens design suitable for preliminary animal trials.

Coherence resonance in bursting neural networks

NASA Astrophysics Data System (ADS)

Kim, June Hoan; Lee, Ho Jun; Min, Cheol Hong; Lee, Kyoung J.

2015-10-01

Synchronized neural bursts are one of the most noticeable dynamic features of neural networks, being essential for various phenomena in neuroscience, yet their complex dynamics are not well understood. With extrinsic electrical and optical manipulations on cultured neural networks, we demonstrate that the regularity (or randomness) of burst sequences is in many cases determined by a (few) low-dimensional attractor(s) working under strong neural noise. Moreover, there is an optimal level of noise strength at which the regularity of the interburst interval sequence becomes maximal—a phenomenon of coherence resonance. The experimental observations are successfully reproduced through computer simulations on a well-established neural network model, suggesting that the same phenomena may occur in many in vivo as well as in vitro neural networks.

Detection of micro gap weld joint by using magneto-optical imaging and Kalman filtering compensated with RBF neural network

NASA Astrophysics Data System (ADS)

Gao, Xiangdong; Chen, Yuquan; You, Deyong; Xiao, Zhenlin; Chen, Xiaohui

2017-02-01

An approach for seam tracking of micro gap weld whose width is less than 0.1 mm based on magneto optical (MO) imaging technique during butt-joint laser welding of steel plates is investigated. Kalman filtering(KF) technology with radial basis function(RBF) neural network for weld detection by an MO sensor was applied to track the weld center position. Because the laser welding system process noises and the MO sensor measurement noises were colored noises, the estimation accuracy of traditional KF for seam tracking was degraded by the system model with extreme nonlinearities and could not be solved by the linear state-space model. Also, the statistics characteristics of noises could not be accurately obtained in actual welding. Thus, a RBF neural network was applied to the KF technique to compensate for the weld tracking errors. The neural network can restrain divergence filter and improve the system robustness. In comparison of traditional KF algorithm, the RBF with KF was not only more effectively in improving the weld tracking accuracy but also reduced noise disturbance. Experimental results showed that magneto optical imaging technique could be applied to detect micro gap weld accurately, which provides a novel approach for micro gap seam tracking.

Neural images of pursuit targets in the photoreceptor arrays of male and female houseflies Musca domestica.

PubMed

Burton, Brian G; Laughlin, Simon B

2003-11-01

Male houseflies use a sex-specific frontal eye region, the lovespot, to detect and pursue mates. We recorded the electrical responses of photoreceptors to optical stimuli that simulate the signals received by a male or female photoreceptor as a conspecific passes through its field of view. We analysed the ability of male and female frontal photoreceptors to code conspecifics over the range of speeds and distances encountered during pursuit, and reconstructed the neural images of these targets in photoreceptor arrays. A male's lovespot photoreceptor detects a conspecific at twice the distance of a female photoreceptor, largely through better optics. This detection distance greatly exceeds those reported in previous behavioural studies. Lovespot photoreceptors respond more strongly than female photoreceptors to targets tracked during pursuit, with amplitudes reaching 25 mV. The male photoreceptor also has a faster response, exhibits a unique preference for stimuli of 20-30 ms duration that selects for conspecifics and deblurs moving images with response transients. White-noise analysis substantially underestimates these improvements. We conclude that in the lovespot, both optics and phototransduction are specialised to enhance and deblur the neural images of moving targets, and propose that analogous mechanisms may sharpen the neural image still further as it is transferred to visual interneurones.

Developing a tissue-engineered neural-electrical relay using encapsulated neuronal constructs on conducting polymer fibers.

PubMed

Cullen, D Kacy; R Patel, Ankur; Doorish, John F; Smith, Douglas H; Pfister, Bryan J

2008-12-01

Neural-electrical interface platforms are being developed to extracellularly monitor neuronal population activity. Polyaniline-based electrically conducting polymer fibers are attractive substrates for sustained functional interfaces with neurons due to their flexibility, tailored geometry and controlled electro-conductive properties. In this study, we addressed the neurobiological considerations of utilizing small diameter (<400 microm) fibers consisting of a blend of electrically conductive polyaniline and polypropylene (PA-PP) as the backbone of encapsulated tissue-engineered neural-electrical relays. We devised new approaches to promote survival, adhesion and neurite outgrowth of primary dorsal root ganglion neurons on PA-PP fibers. We attained a greater than ten-fold increase in the density of viable neurons on fiber surfaces to approximately 700 neurons mm(-2) by manipulating surrounding surface charges to bias settling neuronal suspensions toward fibers coated with cell-adhesive ligands. This stark increase in neuronal density resulted in robust neuritic extension and network formation directly along the fibers. Additionally, we encapsulated these neuronal networks on PA-PP fibers using agarose to form a protective barrier while potentially facilitating network stability. Following encapsulation, the neuronal networks maintained integrity, high viability (>85%) and intimate adhesion to PA-PP fibers. These efforts accomplished key prerequisites for the establishment of functional electrical interfaces with neuronal populations using small diameter PA-PP fibers-specifically, improved neurocompatibility, high-density neuronal adhesion and neuritic network development directly on fiber surfaces.

Introduction to optical methods for characterizing liquid crystals at interfaces.

PubMed

Miller, Daniel S; Carlton, Rebecca J; Mushenheim, Peter C; Abbott, Nicholas L

2013-03-12

This Instructional Review describes methods and underlying principles that can be used to characterize both the orientations assumed spontaneously by liquid crystals (LCs) at interfaces and the strength with which the LCs are held in those orientations (so-called anchoring energies). The application of these methods to several different classes of LC interfaces is described, including solid and aqueous interfaces as well as planar and nonplanar interfaces (such as those that define a LC-in-water emulsion droplet). These methods, which enable fundamental studies of the ordering of LCs at polymeric, chemically functionalized, and biomolecular interfaces, are described in this Instructional Review on a level that can be easily understood by a nonexpert reader such as an undergraduate or graduate student. We focus on optical methods because they are based on instrumentation that is found widely in research and teaching laboratories.

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.

Optical Neural Classification Of Binary Patterns

NASA Astrophysics Data System (ADS)

Gustafson, Steven C.; Little, Gordon R.

1988-05-01

Binary pattern classification that may be implemented using optical hardware and neural network algorithms is considered. Pattern classification problems that have no concise description (as in classifying handwritten characters) or no concise computation (as in NP-complete problems) are expected to be particularly amenable to this approach. For example, optical processors that efficiently classify binary patterns in accordance with their Boolean function complexity might be designed. As a candidate for such a design, an optical neural network model is discussed that is designed for binary pattern classification and that consists of an optical resonator with a dynamic multiplex-recorded reflection hologram and a phase conjugate mirror with thresholding and gain. In this model, learning or training examples of binary patterns may be recorded on the hologram such that one bit in each pattern marks the pattern class. Any input pattern, including one with an unknown class or marker bit, will be modified by a large number of parallel interactions with the reflection hologram and nonlinear mirror. After perhaps several seconds and 100 billion interactions, a steady-state pattern may develop with a marker bit that represents a minimum-Boolean-complexity classification of the input pattern. Computer simulations are presented that illustrate progress in understanding the behavior of this model and in developing a processor design that could have commanding and enduring performance advantages compared to current pattern classification techniques.

Closed-Loop and Activity-Guided Optogenetic Control

PubMed Central

Grosenick, Logan; Marshel, James H.; Deisseroth, Karl

2016-01-01

Advances in optical manipulation and observation of neural activity have set the stage for widespread implementation of closed-loop and activity-guided optical control of neural circuit dynamics. Closing the loop optogenetically (i.e., basing optogenetic stimulation on simultaneously observed dynamics in a principled way) is a powerful strategy for causal investigation of neural circuitry. In particular, observing and feeding back the effects of circuit interventions on physiologically relevant timescales is valuable for directly testing whether inferred models of dynamics, connectivity, and causation are accurate in vivo. Here we highlight technical and theoretical foundations as well as recent advances and opportunities in this area, and we review in detail the known caveats and limitations of optogenetic experimentation in the context of addressing these challenges with closed-loop optogenetic control in behaving animals. PMID:25856490

Abnormal Neural Connectivity in Schizophrenia and fMRI-Brain-Computer Interface as a Potential Therapeutic Approach

PubMed Central

Ruiz, Sergio; Birbaumer, Niels; Sitaram, Ranganatha

2012-01-01

Considering that single locations of structural and functional abnormalities are insufficient to explain the diverse psychopathology of schizophrenia, new models have postulated that the impairments associated with the disease arise from a failure to integrate the activity of local and distributed neural circuits: the “abnormal neural connectivity hypothesis.” In the last years, new evidence coming from neuroimaging have supported and expanded this theory. However, despite the increasing evidence that schizophrenia is a disorder of neural connectivity, so far there are no treatments that have shown to produce a significant change in brain connectivity, or that have been specifically designed to alleviate this problem. Brain-Computer Interfaces based on real-time functional Magnetic Resonance Imaging (fMRI-BCI) are novel techniques that have allowed subjects to achieve self-regulation of circumscribed brain regions. In recent studies, experiments with this technology have resulted in new findings suggesting that this methodology could be used to train subjects to enhance brain connectivity, and therefore could potentially be used as a therapeutic tool in mental disorders including schizophrenia. The present article summarizes the findings coming from hemodynamics-based neuroimaging that support the abnormal connectivity hypothesis in schizophrenia, and discusses a new approach that could address this problem. PMID:23525496

An Analysis of EMG Electrode Configuration for Targeted Muscle Reinnervation Based Neural Machine Interface

PubMed Central

Huang, He; Zhou, Ping; Li, Guanglin; Kuiken, Todd A.

2015-01-01

Targeted muscle reinnervation (TMR) is a novel neural machine interface for improved myoelectric prosthesis control. Previous high-density (HD) surface electromyography (EMG) studies have indicated that tremendous neural control information can be extracted from the reinnervated muscles by EMG pattern recognition (PR). However, using a large number of EMG electrodes hinders clinical application of the TMR technique. This study investigated a reduced number of electrodes and the placement required to extract sufficient neural control information for accurate identification of user movement intents. An electrode selection algorithm was applied to the HD EMG recordings from each of 4 TMR amputee subjects. The results show that when using only 12 selected bipolar electrodes the average accuracy over subjects for classifying 16 movement intents was 93.0(±3.3)%, just 1.2% lower than when using the entire HD electrode complement. The locations of selected electrodes were consistent with the anatomical reinnervation sites. Additionally, a practical protocol for clinical electrode placement was developed, which does not rely on complex HD EMG experiment and analysis while maintaining a classification accuracy of 88.7±4.5%. These outcomes provide important guidelines for practical electrode placement that can promote future clinical application of TMR and EMG PR in the control of multifunctional prostheses. PMID:18303804

FRP debonding monitoring using OTDR techniques

NASA Astrophysics Data System (ADS)

Hou, Shuang; Cai, C. S. Steve; Ou, Jinping

2009-07-01

Debonding failure has been reported as the dominant failure mode for FRP strengthening in flexure. This paper explores a novel debonding monitoring method for FRP strengthened structures by means of OTDR-based fiber optic technology. Interface slip as a key factor in debonding failures will be measured through sensing optic fibers, which is instrumented in the interface between FRP and concrete in the direction perpendicular to the FRP filaments. Slip in the interface will induce power losses in the optic fiber signals at the intersection point of the FRP strip and the sensing optic fiber and the signal change will be detected through OTDR device. The FRP double shear tests and three-point bending tests were conducted to verify the effectiveness of the proposed monitoring method. It is found that the early bebonding can be detected before it causes the interface failure. The sensing optic fiber shows signal changes in the slip value at about 36~156 micrometer which is beyond sensing capacity of the conventional sensors. The tests results show that the proposed method is feasible in slip measurement with high sensitivity, and would be cost effective because of the low price of sensors used, which shows its potential of large-scale applications in civil infrastructures, especially for bridges.

Liquid lens enabling real-time focus and tilt compensation for optical image stabilization in camera modules

NASA Astrophysics Data System (ADS)

Simon, Eric; Craen, Pierre; Gaton, Hilario; Jacques-Sermet, Olivier; Laune, Frédéric; Legrand, Julien; Maillard, Mathieu; Tallaron, Nicolas; Verplanck, Nicolas; Berge, Bruno

2010-05-01

A new generation of liquid lenses based on electrowetting has been developed, using a multi-electrode design, enabling to induce optical tilt and focus corrections in the same component. The basic principle is to rely on a conical shape for supporting the liquid interface, the conical shape insuring a restoring force for the liquid liquid interface to come at the center position. The multi-electrode design enables to induce an average tilt of the liquid liquid interface when a bias voltage is applied to the different electrodes. This tilt is reversible, vanishing when voltage bias is cancelled. Possible application of this new lens component is the realization of miniature camera featuring auto-focus and optical image stabilization (OIS) without any mobile mechanical part. Experimental measurements of actual performances of liquid lens component will be presented : focus and tilt amplitude, residual optical wave front error and response time.

Enhanced magneto-optical Kerr effect at Fe/insulator interfaces

NASA Astrophysics Data System (ADS)

Gu, Bo; Takahashi, Saburo; Maekawa, Sadamichi

2017-12-01

Using density functional theory calculations, we have found an enhanced magneto-optical Kerr effect in Fe/insulator interfaces. The results of our study indicate that interfacial Fe atoms in the Fe films have a low-dimensional nature, which causes the following two effects: (i) The diagonal component σx x of the optical conductivity decreases dramatically because the hopping integral for electrons between Fe atoms is suppressed by the low dimensionality. (ii) The off-diagonal component σx y of the optical conductivity does not change at low photon energies, but it is enhanced at photon energies around 2 eV, where we obtain enhanced orbital magnetic moments and spin-orbit correlations for the interfacial Fe atoms. A large Kerr angle develops in proportion to the ratio σx y/σx x . Our findings indicate an efficient way to enhance the effect of spin-orbit coupling at metal/insulator interfaces without using heavy elements.

Optical luminescence studies of the ethyl xanthate adsorption layer on the surface of sphalerite minerals.

PubMed

Todoran, R; Todoran, D; Szakács, Zs

2016-01-05

In this work we propose optical luminescence measurements as a method to evaluate the kinetics of adsorption processes. Measurement of the intensity of the integral optical radiation obtained from the mineral-xanthate interface layer, stimulated with a monochromatic pulsating optical signal, as a function of time were made. The luminescence radiation was obtained from the thin interface layer formed at the separation surface between the sphalerite natural mineral and potassium ethyl xanthate solution, for different solution concentrations and pH-es at the constant industry standard temperature. This method enabled us to determine the time to achieve dynamic equilibrium in the formation of the interface layer of approximately 20min, gaining information on the adsorption kinetics in the case of xanthate on mineral surface and leading to the optimization of the industrial froth flotation process. Copyright © 2015 Elsevier B.V. All rights reserved.

Simulating and Synthesizing Substructures Using Neural Network and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Liu, Youhua; Kapania, Rakesh K.; VanLandingham, Hugh F.

1997-01-01

The feasibility of simulating and synthesizing substructures by computational neural network models is illustrated by investigating a statically indeterminate beam, using both a 1-D and a 2-D plane stress modelling. The beam can be decomposed into two cantilevers with free-end loads. By training neural networks to simulate the cantilever responses to different loads, the original beam problem can be solved as a match-up between two subsystems under compatible interface conditions. The genetic algorithms are successfully used to solve the match-up problem. Simulated results are found in good agreement with the analytical or FEM solutions.

Intelligent detectors modelled from the cat's eye

NASA Astrophysics Data System (ADS)

Lindblad, Th.; Becanovic, V.; Lindsey, C. S.; Szekely, G.

1997-02-01

Biologically inspired image/signal processing, in particular neural networks like the Pulse-Coupled Neural Network (PCNN), are revisited. Their use with high granularity high-energy physics detectors, as well as optical sensing devices, for filtering, de-noising, segmentation, object isolation and edge detection is discussed.

Optical patient interface in femtosecond laser-assisted cataract surgery: contact corneal applanation versus liquid immersion.

PubMed

Talamo, Jonathan H; Gooding, Philip; Angeley, David; Culbertson, William W; Schuele, Georg; Andersen, Daniel; Marcellino, George; Essock-Burns, Emma; Batlle, Juan; Feliz, Rafael; Friedman, Neil J; Palanker, Daniel

2013-04-01

To compare 2 optical patient interface designs used for femtosecond laser-assisted cataract surgery. Optimedica Corp., Santa Clara, California, USA, and Centro Laser, Santo Domingo, Dominican Republic. Experimental and clinical studies. Laser capsulotomy was performed during cataract surgery with a curved contact lens interface (CCL) or a liquid optical immersion interface (LOI). The presence of corneal folds, incomplete capsulotomy, subconjunctival hemorrhage, and eye movement during laser treatment were analyzed using video and optical coherence tomography. The induced rise of intraocular pressure (IOP) was measured in porcine and cadaver eyes. Corneal folds were identified in 70% of the CCL cohort; 63% of these had areas of incomplete capsulotomies beneath the corneal folds. No corneal folds or incomplete capsulotomies were identified in the LOI cohort. The mean eye movement during capsulotomy creation (1.5 sec) was 50 μm with a CCL and 20 μm with an LOI. The LOI cohort had 36% less subconjunctival hemorrhage than the CCL cohort. During suction, the mean IOP rise was 32.4 mm Hg ± 3.4 (SD) in the CCL group and 17.7 ± 2.1 mm Hg in the LOI group. Curved contact interfaces create corneal folds that can lead to incomplete capsulotomy during laser cataract surgery. A liquid interface eliminated corneal folds, improved globe stability, reduced subconjunctival hemorrhage, and lowered IOP rise. Copyright © 2013 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

Electro-optical processing of phased array data

NASA Technical Reports Server (NTRS)

Casasent, D.

1973-01-01

An on-line spatial light modulator for application as the input transducer for a real-time optical data processing system is described. The use of such a device in the analysis and processing of radar data in real time is reported. An interface from the optical processor to a control digital computer was designed, constructed, and tested. The input transducer, optical system, and computer interface have been operated in real time with real time radar data with the input data returns recorded on the input crystal, processed by the optical system, and the output plane pattern digitized, thresholded, and outputted to a display and storage in the computer memory. The correlation of theoretical and experimental results is discussed.

Droplet actuator analyzer with cartridge

NASA Technical Reports Server (NTRS)

Sturmer, Ryan A. (Inventor); Paik, Philip Y. (Inventor); Srinivasan, Vijay (Inventor); Brafford, Keith R. (Inventor); West, Richard M. (Inventor); Smith, Gregory F. (Inventor); Pollack, Michael G. (Inventor); Pamula, Vamsee K. (Inventor)

2011-01-01

A droplet actuator with cartridge is provided. According to one embodiment, a sample analyzer is provided and includes an analyzer unit comprising electronic or optical receiving means, a cartridge comprising self-contained droplet handling capabilities, and a wherein the cartridge is coupled to the analyzer unit by a means which aligns electronic and/or optical outputs from the cartridge with electronic or optical receiving means on the analyzer unit. According to another embodiment, a sample analyzer is provided and includes a sample analyzer comprising a cartridge coupled thereto and a means of electrical interface and/or optical interface between the cartridge and the analyzer, whereby electrical signals and/or optical signals may be transmitted from the cartridge to the analyzer.

Pattern recognition neural-net by spatial mapping of biology visual field

NASA Astrophysics Data System (ADS)

Lin, Xin; Mori, Masahiko

2000-05-01

The method of spatial mapping in biology vision field is applied to artificial neural networks for pattern recognition. By the coordinate transform that is called the complex-logarithm mapping and Fourier transform, the input images are transformed into scale- rotation- and shift- invariant patterns, and then fed into a multilayer neural network for learning and recognition. The results of computer simulation and an optical experimental system are described.

Pulse-coupled neural nets: translation, rotation, scale, distortion, and intensity signal invariance for images.

PubMed

Johnson, J L

1994-09-10

The linking-field neural network model of Eckhorn et al. [Neural Comput. 2, 293-307 (1990)] was introduced to explain the experimentally observed synchronous activity among neural assemblies in the cat cortex induced by feature-dependent visual activity. The model produces synchronous bursts of pulses from neurons with similar activity, effectively grouping them by phase and pulse frequency. It gives a basic new function: grouping by similarity. The synchronous bursts are obtained in the limit of strong linking strengths. The linking-field model in the limit of moderate-to-weak linking characterized by few if any multiple bursts is investigated. In this limit dynamic, locally periodic traveling waves exist whose time signal encodes the geometrical structure of a two-dimensional input image. The signal can be made insensitive to translation, scale, rotation, distortion, and intensity. The waves transmit information beyond the physical interconnect distance. The model is implemented in an optical hybrid demonstration system. Results of the simulations and the optical system are presented.

Beyond the visual word form area: the orthography-semantics interface in spelling and reading.

PubMed

Purcell, Jeremy J; Shea, Jennifer; Rapp, Brenda

2014-01-01

Lexical orthographic information provides the basis for recovering the meanings of words in reading and for generating correct word spellings in writing. Research has provided evidence that an area of the left ventral temporal cortex, a subregion of what is often referred to as the visual word form area (VWFA), plays a significant role specifically in lexical orthographic processing. The current investigation goes beyond this previous work by examining the neurotopography of the interface of lexical orthography with semantics. We apply a novel lesion mapping approach with three individuals with acquired dysgraphia and dyslexia who suffered lesions to left ventral temporal cortex. To map cognitive processes to their neural substrates, this lesion mapping approach applies similar logical constraints to those used in cognitive neuropsychological research. Using this approach, this investigation: (a) identifies a region anterior to the VWFA that is important in the interface of orthographic information with semantics for reading and spelling; (b) determines that, within this orthography-semantics interface region (OSIR), access to orthography from semantics (spelling) is topographically distinct from access to semantics from orthography (reading); (c) provides evidence that, within this region, there is modality-specific access to and from lexical semantics for both spoken and written modalities, in both word production and comprehension. Overall, this study contributes to our understanding of the neural architecture at the lexical orthography-semantic-phonological interface within left ventral temporal cortex.

Beyond the VWFA: The orthography-semantics interface in spelling and reading

PubMed Central

Purcell, Jeremy J.; Shea, Jennifer; Rapp, Brenda

2014-01-01

Lexical orthographic information provides the basis for recovering the meanings of words in reading and for generating correct word spellings in writing. Research has provided evidence that an area of the left ventral temporal cortex, a sub-region of what is often referred to as the Visual Word Form Area (VWFA), plays a significant role specifically in lexical orthographic processing. The current investigation goes beyond this previous work by examining the neurotopography of the interface of lexical orthography with semantics. We apply a novel lesion mapping approach with three individuals with acquired dysgraphia and dyslexia who suffered lesions to left ventral temporal cortex. To map cognitive processes to their neural substrates, this lesion mapping approach applies similar logical constraints as used in cognitive neuropsychological research. Using this approach, this investigation: (1) Identifies a region anterior to the VWFA that is important in the interface of orthographic information with semantics for reading and spelling; (2) Determines that, within this Orthography-Semantics Interface Region (OSIR), access to orthography from semantics (spelling) is topographically distinct from access to semantics from orthography (reading); (3) Provides evidence that, within this region, there is modality-specific access to and from lexical semantics for both spoken and written modalities, in both word production and comprehension. Overall, this study contributes to our understanding of the neural architecture at the lexical orthography-semantic-phonological interface within left ventral temporal cortex. PMID:24833190

Label-free nonlinear optical microscopy detects early markers for osteogenic differentiation of human stem cells.

PubMed

Hofemeier, Arne D; Hachmeister, Henning; Pilger, Christian; Schürmann, Matthias; Greiner, Johannes F W; Nolte, Lena; Sudhoff, Holger; Kaltschmidt, Christian; Huser, Thomas; Kaltschmidt, Barbara

2016-05-26

Tissue engineering by stem cell differentiation is a novel treatment option for bone regeneration. Most approaches for the detection of osteogenic differentiation are invasive or destructive and not compatible with live cell analysis. Here, non-destructive and label-free approaches of Raman spectroscopy, coherent anti-Stokes Raman scattering (CARS) and second harmonic generation (SHG) microscopy were used to detect and image osteogenic differentiation of human neural crest-derived inferior turbinate stem cells (ITSCs). Combined CARS and SHG microscopy was able to detect markers of osteogenesis within 14 days after osteogenic induction. This process increased during continued differentiation. Furthermore, Raman spectroscopy showed significant increases of the PO4(3-) symmetric stretch vibrations at 959 cm(-1) assigned to calcium hydroxyapatite between days 14 and 21. Additionally, CARS microscopy was able to image calcium hydroxyapatite deposits within 14 days following osteogenic induction, which was confirmed by Alizarin Red-Staining and RT- PCR. Taken together, the multimodal label-free analysis methods Raman spectroscopy, CARS and SHG microscopy can monitor osteogenic differentiation of adult human stem cells into osteoblasts with high sensitivity and spatial resolution in three dimensions. Our findings suggest a great potential of these optical detection methods for clinical applications including in vivo observation of bone tissue-implant-interfaces or disease diagnosis.

Label-free nonlinear optical microscopy detects early markers for osteogenic differentiation of human stem cells

NASA Astrophysics Data System (ADS)

Hofemeier, Arne D.; Hachmeister, Henning; Pilger, Christian; Schürmann, Matthias; Greiner, Johannes F. W.; Nolte, Lena; Sudhoff, Holger; Kaltschmidt, Christian; Huser, Thomas; Kaltschmidt, Barbara

2016-05-01

Tissue engineering by stem cell differentiation is a novel treatment option for bone regeneration. Most approaches for the detection of osteogenic differentiation are invasive or destructive and not compatible with live cell analysis. Here, non-destructive and label-free approaches of Raman spectroscopy, coherent anti-Stokes Raman scattering (CARS) and second harmonic generation (SHG) microscopy were used to detect and image osteogenic differentiation of human neural crest-derived inferior turbinate stem cells (ITSCs). Combined CARS and SHG microscopy was able to detect markers of osteogenesis within 14 days after osteogenic induction. This process increased during continued differentiation. Furthermore, Raman spectroscopy showed significant increases of the PO43- symmetric stretch vibrations at 959 cm-1 assigned to calcium hydroxyapatite between days 14 and 21. Additionally, CARS microscopy was able to image calcium hydroxyapatite deposits within 14 days following osteogenic induction, which was confirmed by Alizarin Red-Staining and RT- PCR. Taken together, the multimodal label-free analysis methods Raman spectroscopy, CARS and SHG microscopy can monitor osteogenic differentiation of adult human stem cells into osteoblasts with high sensitivity and spatial resolution in three dimensions. Our findings suggest a great potential of these optical detection methods for clinical applications including in vivo observation of bone tissue-implant-interfaces or disease diagnosis.

Label-free nonlinear optical microscopy detects early markers for osteogenic differentiation of human stem cells

PubMed Central

Hofemeier, Arne D.; Hachmeister, Henning; Pilger, Christian; Schürmann, Matthias; Greiner, Johannes F. W.; Nolte, Lena; Sudhoff, Holger; Kaltschmidt, Christian; Huser, Thomas; Kaltschmidt, Barbara

2016-01-01

Tissue engineering by stem cell differentiation is a novel treatment option for bone regeneration. Most approaches for the detection of osteogenic differentiation are invasive or destructive and not compatible with live cell analysis. Here, non-destructive and label-free approaches of Raman spectroscopy, coherent anti-Stokes Raman scattering (CARS) and second harmonic generation (SHG) microscopy were used to detect and image osteogenic differentiation of human neural crest-derived inferior turbinate stem cells (ITSCs). Combined CARS and SHG microscopy was able to detect markers of osteogenesis within 14 days after osteogenic induction. This process increased during continued differentiation. Furthermore, Raman spectroscopy showed significant increases of the PO43− symmetric stretch vibrations at 959 cm−1 assigned to calcium hydroxyapatite between days 14 and 21. Additionally, CARS microscopy was able to image calcium hydroxyapatite deposits within 14 days following osteogenic induction, which was confirmed by Alizarin Red-Staining and RT- PCR. Taken together, the multimodal label-free analysis methods Raman spectroscopy, CARS and SHG microscopy can monitor osteogenic differentiation of adult human stem cells into osteoblasts with high sensitivity and spatial resolution in three dimensions. Our findings suggest a great potential of these optical detection methods for clinical applications including in vivo observation of bone tissue–implant-interfaces or disease diagnosis. PMID:27225821

Neural Correlates of Phrase Quadrature Perception in Harmonic Rhythm: An EEG Study Using a Brain-Computer Interface.

PubMed

Fernández-Soto, Alicia; Martínez-Rodrigo, Arturo; Moncho-Bogani, José; Latorre, José Miguel; Fernández-Caballero, Antonio

2018-06-01

For the sake of establishing the neural correlates of phrase quadrature perception in harmonic rhythm, a musical experiment has been designed to induce music-evoked stimuli related to one important aspect of harmonic rhythm, namely the phrase quadrature. Brain activity is translated to action through electroencephalography (EEG) by using a brain-computer interface. The power spectral value of each EEG channel is estimated to obtain how power variance distributes as a function of frequency. The results of processing the acquired signals are in line with previous studies that use different musical parameters to induce emotions. Indeed, our experiment shows statistical differences in theta and alpha bands between the fulfillment and break of phrase quadrature, an important cue of harmonic rhythm, in two classical sonatas.

Friction forces position the neural anlage

PubMed Central

Smutny, Michael; Ákos, Zsuzsa; Grigolon, Silvia; Shamipour, Shayan; Ruprecht, Verena; Čapek, Daniel; Behrndt, Martin; Papusheva, Ekaterina; Tada, Masazumi; Hof, Björn; Vicsek, Tamás; Salbreux, Guillaume; Heisenberg, Carl-Philipp

2017-01-01

During embryonic development, mechanical forces are essential for cellular rearrangements driving tissue morphogenesis. Here, we show that in the early zebrafish embryo, friction forces are generated at the interface between anterior axial mesoderm (prechordal plate, ppl) progenitors migrating towards the animal pole and neurectoderm progenitors moving in the opposite direction towards the vegetal pole of the embryo. These friction forces lead to global rearrangement of cells within the neurectoderm and determine the position of the neural anlage. Using a combination of experiments and simulations, we show that this process depends on hydrodynamic coupling between neurectoderm and ppl as a result of E-cadherin-mediated adhesion between those tissues. Our data thus establish the emergence of friction forces at the interface between moving tissues as a critical force-generating process shaping the embryo. PMID:28346437

Friction forces position the neural anlage.

PubMed

Smutny, Michael; Ákos, Zsuzsa; Grigolon, Silvia; Shamipour, Shayan; Ruprecht, Verena; Čapek, Daniel; Behrndt, Martin; Papusheva, Ekaterina; Tada, Masazumi; Hof, Björn; Vicsek, Tamás; Salbreux, Guillaume; Heisenberg, Carl-Philipp

2017-04-01

During embryonic development, mechanical forces are essential for cellular rearrangements driving tissue morphogenesis. Here, we show that in the early zebrafish embryo, friction forces are generated at the interface between anterior axial mesoderm (prechordal plate, ppl) progenitors migrating towards the animal pole and neurectoderm progenitors moving in the opposite direction towards the vegetal pole of the embryo. These friction forces lead to global rearrangement of cells within the neurectoderm and determine the position of the neural anlage. Using a combination of experiments and simulations, we show that this process depends on hydrodynamic coupling between neurectoderm and ppl as a result of E-cadherin-mediated adhesion between those tissues. Our data thus establish the emergence of friction forces at the interface between moving tissues as a critical force-generating process shaping the embryo.

Materials and technologies for soft implantable neuroprostheses

NASA Astrophysics Data System (ADS)

Lacour, Stéphanie P.; Courtine, Grégoire; Guck, Jochen

2016-10-01

Implantable neuroprostheses are engineered systems designed to restore or substitute function for individuals with neurological deficits or disabilities. These systems involve at least one uni- or bidirectional interface between a living neural tissue and a synthetic structure, through which information in the form of electrons, ions or photons flows. Despite a few notable exceptions, the clinical dissemination of implantable neuroprostheses remains limited, because many implants display inconsistent long-term stability and performance, and are ultimately rejected by the body. Intensive research is currently being conducted to untangle the complex interplay of failure mechanisms. In this Review, we emphasize the importance of minimizing the physical and mechanical mismatch between neural tissues and implantable interfaces. We explore possible materials solutions to design and manufacture neurointegrated prostheses, and outline their immense therapeutic potential.

Target detection in insects: optical, neural and behavioral optimizations.

PubMed

Gonzalez-Bellido, Paloma T; Fabian, Samuel T; Nordström, Karin

2016-12-01

Motion vision provides important cues for many tasks. Flying insects, for example, may pursue small, fast moving targets for mating or feeding purposes, even when these are detected against self-generated optic flow. Since insects are small, with size-constrained eyes and brains, they have evolved to optimize their optical, neural and behavioral target visualization solutions. Indeed, even if evolutionarily distant insects display different pursuit strategies, target neuron physiology is strikingly similar. Furthermore, the coarse spatial resolution of the insect compound eye might actually be beneficial when it comes to detection of moving targets. In conclusion, tiny insects show higher than expected performance in target visualization tasks. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

The User Interface: How Does Your Product Look and Feel?

ERIC Educational Resources Information Center

Strukhoff, Roger

1987-01-01

Discusses the importance of user cordial interfaces to the successful marketing of optical data disk products, and describes features of several online systems. The topics discussed include full text searching, indexed searching, menu driven interfaces, natural language interfaces, computer graphics, and possible future developments. (CLB)

Apparatus and method for characterizing thin film and interfaces using an optical heat generator and detector

DOEpatents

Maris, H.J.; Stoner, R.J.

1998-05-05

An optical heat generation and detection system generates a first non-destructive pulsed beam of electromagnetic radiation that is directed upon a sample containing at least one interface between similar or dissimilar materials. The first pulsed beam of electromagnetic radiation, a pump beam, produces a non-uniform temperature change within the sample. A second non-destructive pulsed beam of electromagnetic radiation, a probe beam, is also directed upon the sample. Physical and chemical properties of the materials, and of the interface, are measured by observing changes in a transient optical response of the sample to the probe beam, as revealed by a time dependence of changes in, by example, beam intensity, direction, or state of polarization. The system has increased sensitivity to interfacial properties including defects, contaminants, chemical reactions and delaminations, as compared to conventional non-destructive, non-contact techniques. One feature of this invention is a determination of a Kapitza resistance at the interface, and the correlation of the determined Kapitza resistance with a characteristic of the interface, such as roughness, delamination, the presence of contaminants, etc. 31 figs.

Apparatus and method for characterizing thin film and interfaces using an optical heat generator and detector

DOEpatents

Maris, Humphrey J; Stoner, Robert J

1998-01-01

An optical heat generation and detection system generates a first non-destructive pulsed beam of electromagnetic radiation that is directed upon a sample containing at least one interface between similar or dissimilar materials. The first pulsed beam of electromagnetic radiation, a pump beam (21a), produces a non-uniform temperature change within the sample. A second non-destructive pulsed beam of electromagnetic radiation, a probe beam (21b), is also directed upon the sample. Physical and chemical properties of the materials, and of the interface, are measured by observing changes in a transient optical response of the sample to the probe beam, as revealed by a time dependence of changes in, by example, beam intensity, direction, or state of polarization. The system has increased sensitivity to interfacial properties including defects, contaminants, chemical reactions and delaminations, as compared to conventional non-destructive, non-contact techniques. One feature of this invention is a determination of a Kapitza resistance at the interface, and the correlation of the determined Kapitza resistance with a characteristic of the interface, such as roughness, delamination, the presence of contaminants, etc.

Nanophotonic particle simulation and inverse design using artificial neural networks

PubMed Central

Peurifoy, John; Shen, Yichen; Jing, Li; Cano-Renteria, Fidel; DeLacy, Brendan G.; Joannopoulos, John D.; Tegmark, Max

2018-01-01

We propose a method to use artificial neural networks to approximate light scattering by multilayer nanoparticles. We find that the network needs to be trained on only a small sampling of the data to approximate the simulation to high precision. Once the neural network is trained, it can simulate such optical processes orders of magnitude faster than conventional simulations. Furthermore, the trained neural network can be used to solve nanophotonic inverse design problems by using back propagation, where the gradient is analytical, not numerical. PMID:29868640

Interface inequivalence of the InP/InAlAs/InP staggered double heterostructure grown by metalorganic chemical vapor deposition

NASA Astrophysics Data System (ADS)

Böhrer, J.; Krost, A.; Heitz, R.; Heinrichsdorff, F.; Eckey, L.; Bimberg, D.; Cerva, H.

1996-02-01

The optical and structural properties of the normal InAlAs on InP and the inverted InP on the InAlAs staggered band lineup interface grown by metalorganic chemical vapor deposition (MOCVD) are compared by use of transmission electron microscopy (TEM), time integrated, and time resolved photoluminescence. TEM images show that both interfaces are dissimilar. The normal interface is very abrupt. The inverted interface shows an additional graded layer of about 2.5 nm in width of In1-xAlxAsyP1-y with x (0.48-0) and y (1.0-0.0). A large optical anisotropy exists because of the inequivalence of the two interfaces. The larger spatial separation of the carriers at the inverted interface is responsible for a smaller overlap of the electron and hole wave functions and for that reason a one order of magnitude longer e-h luminescence decay time of 45 ns is observed. The normal interface transition shifts approximately to the third root of excitation while the inverted interface transition shifts logarithmically.

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.

A Neural Network Approach to Infer Optical Depth of Thick Ice Clouds at Night

NASA Technical Reports Server (NTRS)

Minnis, P.; Hong, G.; Sun-Mack, S.; Chen, Yan; Smith, W. L., Jr.

2016-01-01

One of the roadblocks to continuously monitoring cloud properties is the tendency of clouds to become optically black at cloud optical depths (COD) of 6 or less. This constraint dramatically reduces the quantitative information content at night. A recent study found that because of their diffuse nature, ice clouds remain optically gray, to some extent, up to COD of 100 at certain wavelengths. Taking advantage of this weak dependency and the availability of COD retrievals from CloudSat, an artificial neural network algorithm was developed to estimate COD values up to 70 from common satellite imager infrared channels. The method was trained using matched 2007 CloudSat and Aqua MODIS data and is tested using similar data from 2008. The results show a significant improvement over the use of default values at night with high correlation. This paper summarizes the results and suggests paths for future improvement.

Photonics: From target recognition to lesion detection

NASA Technical Reports Server (NTRS)

Henry, E. Michael

1994-01-01

Since 1989, Martin Marietta has invested in the development of an innovative concept for robust real-time pattern recognition for any two-dimensioanal sensor. This concept has been tested in simulation, and in laboratory and field hardware, for a number of DOD and commercial uses from automatic target recognition to manufacturing inspection. We have now joined Rose Health Care Systems in developing its use for medical diagnostics. The concept is based on determining regions of interest by using optical Fourier bandpassing as a scene segmentation technique, enhancing those regions using wavelet filters, passing the enhanced regions to a neural network for analysis and initial pattern identification, and following this initial identification with confirmation by optical correlation. The optical scene segmentation and pattern confirmation are performed by the same optical module. The neural network is a recursive error minimization network with a small number of connections and nodes that rapidly converges to a global minimum.

Key considerations in designing a speech brain-computer interface.

PubMed

Bocquelet, Florent; Hueber, Thomas; Girin, Laurent; Chabardès, Stéphan; Yvert, Blaise

2016-11-01

Restoring communication in case of aphasia is a key challenge for neurotechnologies. To this end, brain-computer strategies can be envisioned to allow artificial speech synthesis from the continuous decoding of neural signals underlying speech imagination. Such speech brain-computer interfaces do not exist yet and their design should consider three key choices that need to be made: the choice of appropriate brain regions to record neural activity from, the choice of an appropriate recording technique, and the choice of a neural decoding scheme in association with an appropriate speech synthesis method. These key considerations are discussed here in light of (1) the current understanding of the functional neuroanatomy of cortical areas underlying overt and covert speech production, (2) the available literature making use of a variety of brain recording techniques to better characterize and address the challenge of decoding cortical speech signals, and (3) the different speech synthesis approaches that can be considered depending on the level of speech representation (phonetic, acoustic or articulatory) envisioned to be decoded at the core of a speech BCI paradigm. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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.

A 4 μW/Ch analog front-end module with moderate inversion and power-scalable sampling operation for 3-D neural microsystems.

PubMed

Al-Ashmouny, Khaled M; Chang, Sun-Il; Yoon, Euisik

2012-10-01

We report an analog front-end prototype designed in 0.25 μm CMOS process for hybrid integration into 3-D neural recording microsystems. For scaling towards massive parallel neural recording, the prototype has investigated some critical circuit challenges in power, area, interface, and modularity. We achieved extremely low power consumption of 4 μW/channel, optimized energy efficiency using moderate inversion in low-noise amplifiers (K of 5.98 × 10⁸ or NEF of 2.9), and minimized asynchronous interface (only 2 per 16 channels) for command and data capturing. We also implemented adaptable operations including programmable-gain amplification, power-scalable sampling (up to 50 kS/s/channel), wide configuration range (9-bit) for programmable gain and bandwidth, and 5-bit site selection capability (selecting 16 out of 128 sites). The implemented front-end module has achieved a reduction in noise-energy-area product by a factor of 5-25 times as compared to the state-of-the-art analog front-end approaches reported to date.

Unsupervised Decoding of Long-Term, Naturalistic Human Neural Recordings with Automated Video and Audio Annotations

PubMed Central

Wang, Nancy X. R.; Olson, Jared D.; Ojemann, Jeffrey G.; Rao, Rajesh P. N.; Brunton, Bingni W.

2016-01-01

Fully automated decoding of human activities and intentions from direct neural recordings is a tantalizing challenge in brain-computer interfacing. Implementing Brain Computer Interfaces (BCIs) outside carefully controlled experiments in laboratory settings requires adaptive and scalable strategies with minimal supervision. Here we describe an unsupervised approach to decoding neural states from naturalistic human brain recordings. We analyzed continuous, long-term electrocorticography (ECoG) data recorded over many days from the brain of subjects in a hospital room, with simultaneous audio and video recordings. We discovered coherent clusters in high-dimensional ECoG recordings using hierarchical clustering and automatically annotated them using speech and movement labels extracted from audio and video. To our knowledge, this represents the first time techniques from computer vision and speech processing have been used for natural ECoG decoding. Interpretable behaviors were decoded from ECoG data, including moving, speaking and resting; the results were assessed by comparison with manual annotation. Discovered clusters were projected back onto the brain revealing features consistent with known functional areas, opening the door to automated functional brain mapping in natural settings. PMID:27148018

Study of the Gray Scale, Polychromatic, Distortion Invariant Neural Networks Using the Ipa Model.

NASA Astrophysics Data System (ADS)

Uang, Chii-Maw

Research in the optical neural network field is primarily motivated by the fact that humans recognize objects better than the conventional digital computers and the massively parallel inherent nature of optics. This research represents a continuous effort during the past several years in the exploitation of using neurocomputing for pattern recognition. Based on the interpattern association (IPA) model and Hamming net model, many new systems and applications are introduced. A gray level discrete associative memory that is based on object decomposition/composition is proposed for recognizing gray-level patterns. This technique extends the processing ability from the binary mode to gray-level mode, and thus the information capacity is increased. Two polychromatic optical neural networks using color liquid crystal television (LCTV) panels for color pattern recognition are introduced. By introducing a color encoding technique in conjunction with the interpattern associative algorithm, a color associative memory was realized. Based on the color decomposition and composition technique, a color exemplar-based Hamming net was built for color image classification. A shift-invariant neural network is presented through use of the translation invariant property of the modulus of the Fourier transformation and the hetero-associative interpattern association (IPA) memory. To extract the main features, a quadrantal sampling method is used to sampled data and then replace the training patterns. Using the concept of hetero-associative memory to recall the distorted object. A shift and rotation invariant neural network using an interpattern hetero-association (IHA) model is presented. To preserve the shift and rotation invariant properties, a set of binarized-encoded circular harmonic expansion (CHE) functions at the Fourier domain is used as the training set. We use the shift and symmetric properties of the modulus of the Fourier spectrum to avoid the problem of centering the CHE functions. Almost all neural networks have the positive and negative weights, which increases the difficulty of optical implementation. A method to construct a unipolar IPA IWM is discussed. By searching the redundant interconnection links, an effective way that removes all negative links is discussed.

Highly-hermetic feedthrough fiber pigtailed circular TO-can electro-optic sensor for avionics applications

NASA Astrophysics Data System (ADS)

Lauzon, Jocelyn; Leduc, Lorrain; Bessette, Daniel; Bélanger, Nicolas

2012-06-01

Electro-optic sensors made of lasers or photodetectors assemblies can be associated with a window interface. In order to use these sensors in an avionics application, this interface has to be set on the periphery of the aircraft. This creates constraints on both the position/access of the associated electronics circuit card and the aircraft fuselage. Using an optical fiber to guide the light signal to a sensor being situated inside the aircraft where electronics circuit cards are deployed is an obvious solution that can be readily available. Fiber collimators that adapt to circular TO-can type window sensors do exist. However, they are bulky, add weight to the sensor and necessitate regular maintenance of the optical interface since both the sensor window and the collimator end-face are unprotected against contamination. Such maintenance can be complex since the access to the electronics circuit card, where the sensor is sitting, is usually difficult. This interface alignment can also be affected by vibrations and mechanical shocks, thus impacting sensor performances. As a solution to this problem, we propose a highly-hermetic feedthrough fiber pigtailed circular TO-can package. The optical element to optical fiber interface being set inside the hermetic package, there is no risk of contamination and thus, such a component does not require any maintenance. The footprint of these sensors being identical to their window counterparts, they offer drop-in replacement opportunities. Moreover, we have validated such packaged electro-optic sensors can be made to operate between -55 to 115°C, sustain 250 temperature cycles, 1500G mechanical shocks, 20Grms random vibrations without any performance degradations. Their water content is much smaller than the 0.5% limit set by MIL-STD-883, Method 1018. They have also been verified to offer a fiber pigtail strain relief resistance over 400g. Depending on the electronics elements inside these sensors, they can be made to have a MTBF over 50 000h at 100°C.

Infrared neural stimulation (INS) inhibits electrically evoked neural responses in the deaf white cat

NASA Astrophysics Data System (ADS)

Richter, Claus-Peter; Rajguru, Suhrud M.; Robinson, Alan; Young, Hunter K.

2014-03-01

Infrared neural stimulation (INS) has been used in the past to evoke neural activity from hearing and partially deaf animals. All the responses were excitatory. In Aplysia californica, Duke and coworkers demonstrated that INS also inhibits neural responses [1], which similar observations were made in the vestibular system [2, 3]. In deaf white cats that have cochleae with largely reduced spiral ganglion neuron counts and a significant degeneration of the organ of Corti, no cochlear compound action potentials could be observed during INS alone. However, the combined electrical and optical stimulation demonstrated inhibitory responses during irradiation with infrared light.

Neural networks for calibration tomography

NASA Technical Reports Server (NTRS)

Decker, Arthur

1993-01-01

Artificial neural networks are suitable for performing pattern-to-pattern calibrations. These calibrations are potentially useful for facilities operations in aeronautics, the control of optical alignment, and the like. Computed tomography is compared with neural net calibration tomography for estimating density from its x-ray transform. X-ray transforms are measured, for example, in diffuse-illumination, holographic interferometry of fluids. Computed tomography and neural net calibration tomography are shown to have comparable performance for a 10 degree viewing cone and 29 interferograms within that cone. The system of tomography discussed is proposed as a relevant test of neural networks and other parallel processors intended for using flow visualization data.

Optoelectronic Inner-Product Neural Associative Memory

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang

1993-01-01

Optoelectronic apparatus acts as artificial neural network performing associative recall of binary images. Recall process is iterative one involving optical computation of inner products between binary input vector and one or more reference binary vectors in memory. Inner-product method requires far less memory space than matrix-vector method.

Instructional Review: An Introduction to Optical Methods for Characterizing Liquid Crystals at Interfaces

PubMed Central

Miller, Daniel S.; Carlton, Rebecca J.; Mushenheim, Peter C.; Abbott, Nicholas L.

2013-01-01

This Instructional Review describes methods and underlying principles that can be used to characterize both the orientations assumed spontaneously by liquid crystals (LCs) at interfaces and the strength with which the LCs are held in those orientations (so-called anchoring energies). The application of these methods to several different classes of LC interfaces is described, including solid and aqueous interfaces as well as planar and non-planar interfaces (such as those that define a LC-in-water emulsion droplet). These methods, which enable fundamental studies of the ordering of LCs at polymeric, chemically-functionalized and biomolecular interfaces, are described in this article at a level that can be easily understood by a non-expert reader such as an undergraduate or graduate student. We focus on optical methods because they are based on instrumentation that is found widely in research and teaching laboratories. PMID:23347378

Design and implementation of interface units for high speed fiber optics local area networks and broadband integrated services digital networks

NASA Technical Reports Server (NTRS)

Tobagi, Fouad A.; Dalgic, Ismail; Pang, Joseph

1990-01-01

The design and implementation of interface units for high speed Fiber Optic Local Area Networks and Broadband Integrated Services Digital Networks are discussed. During the last years, a number of network adapters that are designed to support high speed communications have emerged. This approach to the design of a high speed network interface unit was to implement package processing functions in hardware, using VLSI technology. The VLSI hardware implementation of a buffer management unit, which is required in such architectures, is described.

Electrical and optical co-stimulation in the deaf white cat

NASA Astrophysics Data System (ADS)

Cao, Zhiping; Xu, Yingyue; Tan, Xiaodong; Suematsu, Naofumi; Robinson, Alan; Richter, Claus-Peter

2018-02-01

Spatial selectivity of neural stimulation with photons, such as infrared neural stimulation (INS) is higher than the selectivity obtained with electrical stimulation. To obtain more independent channels for stimulation in neural prostheses, INS may be implemented to better restore the fidelity of the damaged neural system. However, irradiation with infrared light also bares the risk of heat accumulation in the target tissue with subsequent neural damage. Lowering the threshold for stimulation could reduce the amount of heat delivered to the tissue and the risk for subsequent tissue damage. It has been shown in the rat sciatic nerve that simultaneous irradiation with infrared light and the delivery of biphasic sub-threshold electrical pulses can reduce the threshold for INS [1]. In this study, deaf white cats have been used to test whether opto-electrical co-stimulation can reduce the stimulation threshold for INS in the auditory system too. The cochleae of the deaf white cats have largely reduced spiral ganglion neuron counts and significant degeneration of the organ of Corti and do not respond to acoustic stimuli. Combined electrical and optical stimulation was used to demonstrate that simultaneous stimulation with infrared light and biphasic electrical pulses can reduce the threshold for stimulation.

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 transmission testing based on asynchronous sampling techniques: images analysis containing chromatic dispersion using convolutional neural network

NASA Astrophysics Data System (ADS)

Mrozek, T.; Perlicki, K.; Tajmajer, T.; Wasilewski, P.

2017-08-01

The article presents an image analysis method, obtained from an asynchronous delay tap sampling (ADTS) technique, which is used for simultaneous monitoring of various impairments occurring in the physical layer of the optical network. The ADTS method enables the visualization of the optical signal in the form of characteristics (so called phase portraits) that change their shape under the influence of impairments such as chromatic dispersion, polarization mode dispersion and ASE noise. Using this method, a simulation model was built with OptSim 4.0. After the simulation study, data were obtained in the form of images that were further analyzed using the convolutional neural network algorithm. The main goal of the study was to train a convolutional neural network to recognize the selected impairment (distortion); then to test its accuracy and estimate the impairment for the selected set of test images. The input data consisted of processed binary images in the form of two-dimensional matrices, with the position of the pixel. This article focuses only on the analysis of images containing chromatic dispersion.

Optical path of infrared neural stimulation in the guinea pig and cat cochlea

NASA Astrophysics Data System (ADS)

Rajguru, Suhrud M.; Hwang, Margaret; Moreno, Laura E.; Matic, Agnella I.; Stock, Stuart R.; Richter, Claus-Peter

2011-03-01

It has been demonstrated previously that infrared neural stimulation (INS) can be used to stimulate spiral ganglion cells in the cochlea. With INS, neural stimulation can be achieved without direct contact of the radiation source and the tissue and is spatially well resolved. The presence of fluids or bone between the target structure and the radiation source may lead to absorption or scattering of the radiation and limit the efficacy of INS. To develop INS based cochlear implants, it is critical to determine the beam path of the radiation in the cochlea. In the present study, we utilized noninvasive X-ray microtomography (microCT) to visualize the orientation and location of the optical fiber within the guinea pig and cat cochlea. Overall, the results indicated that the optical fiber was directed towards the spiral ganglion cells in the cochlea and not the nerve fibers in the center of the modiolus. The fiber was approximately 300 μm away from the target structures. In future studies, results from the microCT will be correlated with physiology obtained from recordings in the midbrain.

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

Advances in flexible optrode hardware for use in cybernetic insects

NASA Astrophysics Data System (ADS)

Register, Joseph; Callahan, Dennis M.; Segura, Carlos; LeBlanc, John; Lissandrello, Charles; Kumar, Parshant; Salthouse, Christopher; Wheeler, Jesse

2017-08-01

Optogenetic manipulation is widely used to selectively excite and silence neurons in laboratory experiments. Recent efforts to miniaturize the components of optogenetic systems have enabled experiments on freely moving animals, but further miniaturization is required for freely flying insects. In particular, miniaturization of high channel-count optical waveguides are needed for high-resolution interfaces. Thin flexible waveguide arrays are needed to bend light around tight turns to access small anatomical targets. We present the design of lightweight miniaturized optogentic hardware and supporting electronics for the untethered steering of dragonfly flight. The system is designed to enable autonomous flight and includes processing, guidance sensors, solar power, and light stimulators. The system will weigh less than 200mg and be worn by the dragonfly as a backpack. The flexible implant has been designed to provide stimuli around nerves through micron scale apertures of adjacent neural tissue without the use of heavy hardware. We address the challenges of lightweight optogenetics and the development of high contrast polymer waveguides for this purpose.

Near-infrared signals associated with electrical stimulation of peripheral nerves

NASA Astrophysics Data System (ADS)

Fantini, Sergio; Chen, Debbie K.; Martin, Jeffrey M.; Sassaroli, Angelo; Bergethon, Peter R.

2009-02-01

We report our studies on the optical signals measured non-invasively on electrically stimulated peripheral nerves. The stimulation consists of the delivery of 0.1 ms current pulses, below the threshold for triggering any visible motion, to a peripheral nerve in human subjects (we have studied the sural nerve and the median nerve). In response to electrical stimulation, we observe an optical signal that peaks at about 100 ms post-stimulus, on a much longer time scale than the few milliseconds duration of the electrical response, or sensory nerve action potential (SNAP). While the 100 ms optical signal we measured is not a direct optical signature of neural activation, it is nevertheless indicative of a mediated response to neural activation. We argue that this may provide information useful for understanding the origin of the fast optical signal (also on a 100 ms time scale) that has been measured non-invasively in the brain in response to cerebral activation. Furthermore, the optical response to peripheral nerve activation may be developed into a diagnostic tool for peripheral neuropathies, as suggested by the delayed optical signals (average peak time: 230 ms) measured in patients with diabetic neuropathy with respect to normal subjects (average peak time: 160 ms).

Analysis of Gibbs monolayer adsorbed at the toluene/water interface by UV-visible partial internal reflection spectrometry.

PubMed

Moriya, Yoshio; Hasegawa, Takeshi; Okada, Tetsuo; Ogawa, Nobuaki; Kawai, Erika; Abe, Kosuke; Ogasawara, Masataka; Kato, Sumio; Nakata, Shinichi

2006-11-15

Gibbs monolayers of lipophilic tetraphenylporphyrinatomanganese(III) and hydrophilic diacid of meso-tetrakis(4-sulfonatopheny)porphyrin adsorbed at the liquid-liquid interface have been analyzed by UV-visible external reflection (ER) and partial internal reflection (PIR) spectra measured at different angles of incidence. The angle-dependent ER and PIR spectra over the Brewster angles (thetaERB and thetaIRB) have readily been measured at the toluene/water interface. As preliminarily expected in our previous study, the present study has first proved that the reflection-absorbance of UV-visible PIR spectra quantitatively agrees with the theoretical calculations for the Gibbs monolayer over thetaIRB. In addition, it has also been proved that the absorbance of the PIR spectra is greatly enhanced in comparison to that of the ATR spectra. The enhancement is caused by an optical effect in the monolayer sandwiched between two phases of toluene and water that have different but refractive indices close to each other. This optical enhancement requires an optically perfect contact between the phases, which is difficult to prepare for a solid-solid contact. At the liquid/liquid interface, however, an ideal optical contact is easily realized, which makes the enhancement as much as the theoretical expectation. The PIR spectrometry will be recognized to be a new high-sensitive analytical tool to study Gibbs monolayer at the liquid/liquid interface.

Railroad track inspection interface demonstration : final report.

DOT National Transportation Integrated Search

2016-01-01

This project developed a track data user interface utilizing the Google Glass optical display device. The interface allows the user : to recall data stored remotely and view the data on the Google Glass. The technical effort required developing a com...

Real-time determination of fringe pattern frequencies: An application to pressure measurement

NASA Astrophysics Data System (ADS)

Sciammarella, Cesar A.; Piroozan, Parham

2007-05-01

Retrieving information in real time from fringe patterns is a topic of a great deal of interest in scientific and engineering applications of optical methods. This paper presents a method for fringe frequency determination based on the capability of neural networks to recognize signals that are similar but not identical to signals used to train the neural network. Sampled patterns are generated by calibration and stored in memory. Incoming patterns are analyzed by a back-propagation neural network at the speed of the recording device, a CCD camera. This method of information retrieval is utilized to measure pressures on a boundary layer flow. The sensor combines optics and electronics to analyze dynamic pressure distributions and to feed information to a control system that is capable to preserve the stability of the flow.

Visible rodent brain-wide networks at single-neuron resolution

PubMed Central

Yuan, Jing; Gong, Hui; Li, Anan; Li, Xiangning; Chen, Shangbin; Zeng, Shaoqun; Luo, Qingming

2015-01-01

There are some unsolvable fundamental questions, such as cell type classification, neural circuit tracing and neurovascular coupling, though great progresses are being made in neuroscience. Because of the structural features of neurons and neural circuits, the solution of these questions needs us to break through the current technology of neuroanatomy for acquiring the exactly fine morphology of neuron and vessels and tracing long-distant circuit at axonal resolution in the whole brain of mammals. Combined with fast-developing labeling techniques, efficient whole-brain optical imaging technology emerging at the right moment presents a huge potential in the structure and function research of specific-function neuron and neural circuit. In this review, we summarize brain-wide optical tomography techniques, review the progress on visible brain neuronal/vascular networks benefit from these novel techniques, and prospect the future technical development. PMID:26074784

Interface module for transverse energy input to dye laser modules

DOEpatents

English, Jr., Ronald E.; Johnson, Steve A.

1994-01-01

An interface module (10) for transverse energy input to dye laser modules is provided particularly for the purpose of delivering enhancing transverse energy beams (36) in the form of illumination bar (54) to the lasing zone (18) of a dye laser device, in particular to a dye laser amplifier (12). The preferred interface module (10) includes an optical fiber array (30) having a plurality of optical fibers (38) arrayed in a co-planar fashion with their distal ends (44) receiving coherent laser energy from an enhancing laser source (46), and their proximal ends (4) delivered into a relay structure (3). The proximal ends (42) of the optical fibers (38) are arrayed so as to be coplanar and to be aimed generally at a common point. The transverse energy beam array (36) delivered from the optical fiber array (30) is acted upon by an optical element array (34) to produce an illumination bar (54) which has a cross section in the form of a elongated rectangle at the position of the lasing window (18). The illumination bar (54) is selected to have substantially uniform intensity throughout.

Nanoelectronics enabled chronic multimodal neural platform in a mouse ischemic model.

PubMed

Luan, Lan; Sullender, Colin T; Li, Xue; Zhao, Zhengtuo; Zhu, Hanlin; Wei, Xiaoling; Xie, Chong; Dunn, Andrew K

2018-02-01

Despite significant advancements of optical imaging techniques for mapping hemodynamics in small animal models, it remains challenging to combine imaging with spatially resolved electrical recording of individual neurons especially for longitudinal studies. This is largely due to the strong invasiveness to the living brain from the penetrating electrodes and their limited compatibility with longitudinal imaging. We implant arrays of ultraflexible nanoelectronic threads (NETs) in mice for neural recording both at the brain surface and intracortically, which maintain great tissue compatibility chronically. By mounting a cranial window atop of the NET arrays that allows for chronic optical access, we establish a multimodal platform that combines spatially resolved electrical recording of neural activity and laser speckle contrast imaging (LSCI) of cerebral blood flow (CBF) for longitudinal studies. We induce peri-infarct depolarizations (PIDs) by targeted photothrombosis, and show the ability to detect its occurrence and propagation through spatiotemporal variations in both extracellular potentials and CBF. We also demonstrate chronic tracking of single-unit neural activity and CBF over days after photothrombosis, from which we observe reperfusion and increased firing rates. This multimodal platform enables simultaneous mapping of neural activity and hemodynamic parameters at the microscale for quantitative, longitudinal comparisons with minimal perturbation to the baseline neurophysiology. The ability to spatiotemporally resolve and chronically track CBF and neural electrical activity in the same living brain region has broad applications for studying the interplay between neural and hemodynamic responses in health and in cerebrovascular and neurological pathologies. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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.

Tunable vertical-cavity surface-emitting laser with feedback to implement a pulsed neural model. 2. High-frequency effects and optical coupling.

PubMed

Romariz, Alexandre R S; Wagner, Kelvin H

2007-07-20

The operation of an optoelectronic dynamic neural model implementation is extended to higher frequencies. A simplified model of thermal effects in vertical-cavity surface-emitting lasers correctly predicts the qualitative changes in the nonlinear mapping implementation with frequency. Experiments and simulations show the expected resonance properties of this model neuron, along with the possibility of other dynamic effects in addition to the ones observed in the original FitzHugh-Nagumo equations. Results of optical coupling between two similar pulsing artificial neurons are also presented.

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

Scalable SCPPM Decoder

NASA Technical Reports Server (NTRS)

Quir, Kevin J.; Gin, Jonathan W.; Nguyen, Danh H.; Nguyen, Huy; Nakashima, Michael A.; Moision, Bruce E.

2012-01-01

A decoder was developed that decodes a serial concatenated pulse position modulation (SCPPM) encoded information sequence. The decoder takes as input a sequence of four bit log-likelihood ratios (LLR) for each PPM slot in a codeword via a XAUI 10-Gb/s quad optical fiber interface. If the decoder is unavailable, it passes the LLRs on to the next decoder via a XAUI 10-Gb/s quad optical fiber interface. Otherwise, it decodes the sequence and outputs information bits through a 1-GB/s Ethernet UDP/IP (User Datagram Protocol/Internet Protocol) interface. The throughput for a single decoder unit is 150-Mb/s at an average of four decoding iterations; by connecting a number of decoder units in series, a decoding rate equal to that of the aggregate rate is achieved. The unit is controlled through a 1-GB/s Ethernet UDP/IP interface. This ground station decoder was developed to demonstrate a deep space optical communication link capability, and is unique in the scalable design to achieve real-time SCPP decoding at the aggregate data rate.

JWST Integrated Science Instrument Module Alignment Optimization Tool

NASA Technical Reports Server (NTRS)

Bos, Brent

2013-01-01

During cryogenic vacuum testing of the James Webb Space Telescope (JWST) Integrated Science Instrument Module (ISIM), the global alignment of the ISIM with respect to the designed interface of the JWST optical telescope element (OTE) will be measured through a series of optical characterization tests. These tests will determine the locations and orientations of the JWST science instrument projected focal surfaces and entrance pupils with respect to their corresponding OTE optical interfaces. If any optical performance non-compliances are identified, the ISIM will be adjusted to improve its performance. In order to understand how to manipulate the ISIM's degrees of freedom properly and to prepare for the ISIM flight model testing, a series of optical-mechanical analyses have been completed to develop and identify the best approaches for bringing a non-compliant ISIM element into compliance. In order for JWST to meet its observatory-level optical requirements and ambitious science goals, the ISIM element has to meet approximately 150 separate optical requirements. Successfully achieving many of those optical requirements depends on the proper alignment of the ISIM element with respect to the OTE. To verify that the ISIM element will meet its optical requirements, a series of cryogenic vacuum tests will be conducted with an OTE Simulator (OSIM). An optical Ray Trace and Geometry Model tool was developed to help solve the multi-dimensional alignment problem. The tool allows the user to determine how best to adjust the alignment of the JWST ISIM with respect to the ideal telescope interfaces so that the approximately 150 ISIM optical performance requirements can be satisfied. This capability has not existed previously.

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.

Closed loop adaptive control of spectrum-producing step using neural networks

DOEpatents

Fu, Chi Yung

1998-01-01

Characteristics of the plasma in a plasma-based manufacturing process step are monitored directly and in real time by observing the spectrum which it produces. An artificial neural network analyzes the plasma spectrum and generates control signals to control one or more of the process input parameters in response to any deviation of the spectrum beyond a narrow range. In an embodiment, a plasma reaction chamber forms a plasma in response to input parameters such as gas flow, pressure and power. The chamber includes a window through which the electromagnetic spectrum produced by a plasma in the chamber, just above the subject surface, may be viewed. The spectrum is conducted to an optical spectrometer which measures the intensity of the incoming optical spectrum at different wavelengths. The output of optical spectrometer is provided to an analyzer which produces a plurality of error signals, each indicating whether a respective one of the input parameters to the chamber is to be increased or decreased. The microcontroller provides signals to control respective controls, but these lines are intercepted and first added to the error signals, before being provided to the controls for the chamber. The analyzer can include a neural network and an optional spectrum preprocessor to reduce background noise, as well as a comparator which compares the parameter values predicted by the neural network with a set of desired values provided by the microcontroller.

Closed loop adaptive control of spectrum-producing step using neural networks

DOEpatents

Fu, C.Y.

1998-11-24

Characteristics of the plasma in a plasma-based manufacturing process step are monitored directly and in real time by observing the spectrum which it produces. An artificial neural network analyzes the plasma spectrum and generates control signals to control one or more of the process input parameters in response to any deviation of the spectrum beyond a narrow range. In an embodiment, a plasma reaction chamber forms a plasma in response to input parameters such as gas flow, pressure and power. The chamber includes a window through which the electromagnetic spectrum produced by a plasma in the chamber, just above the subject surface, may be viewed. The spectrum is conducted to an optical spectrometer which measures the intensity of the incoming optical spectrum at different wavelengths. The output of optical spectrometer is provided to an analyzer which produces a plurality of error signals, each indicating whether a respective one of the input parameters to the chamber is to be increased or decreased. The microcontroller provides signals to control respective controls, but these lines are intercepted and first added to the error signals, before being provided to the controls for the chamber. The analyzer can include a neural network and an optional spectrum preprocessor to reduce background noise, as well as a comparator which compares the parameter values predicted by the neural network with a set of desired values provided by the microcontroller. 7 figs.

BP artificial neural network based wave front correction for sensor-less free space optics communication

NASA Astrophysics Data System (ADS)

Li, Zhaokun; Zhao, Xiaohui

2017-02-01

The sensor-less adaptive optics (AO) is one of the most promising methods to compensate strong wave front disturbance in free space optics communication (FSO). The back propagation (BP) artificial neural network is applied for the sensor-less AO system to design a distortion correction scheme in this study. This method only needs one or a few online measurements to correct the wave front distortion compared with other model-based approaches, by which the real-time capacity of the system is enhanced and the Strehl Ratio (SR) is largely improved. Necessary comparisons in numerical simulation with other model-based and model-free correction methods proposed in Refs. [6,8,9,10] are given to show the validity and advantage of the proposed method.

Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

PubMed

Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

Application of Hierarchical Dissociated Neural Network in Closed-Loop Hybrid System Integrating Biological and Mechanical Intelligence

PubMed Central

Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579

Spiking Neural Network Decoder for Brain-Machine Interfaces.

PubMed

Dethier, Julie; Gilja, Vikash; Nuyujukian, Paul; Elassaad, Shauki A; Shenoy, Krishna V; Boahen, Kwabena

2011-01-01

We used a spiking neural network (SNN) to decode neural data recorded from a 96-electrode array in premotor/motor cortex while a rhesus monkey performed a point-to-point reaching arm movement task. We mapped a Kalman-filter neural prosthetic decode algorithm developed to predict the arm's velocity on to the SNN using the Neural Engineering Framework and simulated it using Nengo , a freely available software package. A 20,000-neuron network matched the standard decoder's prediction to within 0.03% (normalized by maximum arm velocity). A 1,600-neuron version of this network was within 0.27%, and run in real-time on a 3GHz PC. These results demonstrate that a SNN can implement a statistical signal processing algorithm widely used as the decoder in high-performance neural prostheses (Kalman filter), and achieve similar results with just a few thousand neurons. Hardware SNN implementations-neuromorphic chips-may offer power savings, essential for realizing fully-implantable cortically controlled prostheses.

Kernel Temporal Differences for Neural Decoding

PubMed Central

Bae, Jihye; Sanchez Giraldo, Luis G.; Pohlmeyer, Eric A.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2015-01-01

We study the feasibility and capability of the kernel temporal difference (KTD)(λ) algorithm for neural decoding. KTD(λ) is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. This algorithm combines kernel-based representations with the temporal difference approach to learning. One of our key observations is that by using strictly positive definite kernels, algorithm's convergence can be guaranteed for policy evaluation. The algorithm's nonlinear functional approximation capabilities are shown in both simulations of policy evaluation and neural decoding problems (policy improvement). KTD can handle high-dimensional neural states containing spatial-temporal information at a reasonable computational complexity allowing real-time applications. When the algorithm seeks a proper mapping between a monkey's neural states and desired positions of a computer cursor or a robot arm, in both open-loop and closed-loop experiments, it can effectively learn the neural state to action mapping. Finally, a visualization of the coadaptation process between the decoder and the subject shows the algorithm's capabilities in reinforcement learning brain machine interfaces. PMID:25866504

Design and fabrication of a flexible substrate microelectrode array for brain machine interfaces.

PubMed

Patrick, Erin; Ordonez, Matthew; Alba, Nicolas; Sanchez, Justin C; Nishida, Toshikazu

2006-01-01

We report a neural microelectrode array design that leverages the recording properties of conventional microwire electrode arrays with the additional features of precise control of the electrode geometries. Using microfabrication techniques, a neural probe array is fabricated that possesses a flexible polyimide-based cable. The performance of the design was tested with electrochemical impedance spectroscopy and in vivo studies. The gold-plated electrode site has an impedance value of 0.9 M Omega at 1 kHz. Acute neural recording provided high neuronal yields, peak-to-peak amplitudes (as high as 100 microV), and signal-to-noise ratios (27 dB).

Brain connectivity study of joint attention using frequency-domain optical imaging technique

NASA Astrophysics Data System (ADS)

Chaudhary, Ujwal; Zhu, Banghe; Godavarty, Anuradha

2010-02-01

Autism is a socio-communication brain development disorder. It is marked by degeneration in the ability to respond to joint attention skill task, from as early as 12 to 18 months of age. This trait is used to distinguish autistic from nonautistic populations. In this study, diffuse optical imaging is being used to study brain connectivity for the first time in response to joint attention experience in normal adults. The prefrontal region of the brain was non-invasively imaged using a frequency-domain based optical imager. The imaging studies were performed on 11 normal right-handed adults and optical measurements were acquired in response to joint-attention based video clips. While the intensity-based optical data provides information about the hemodynamic response of the underlying neural process, the time-dependent phase-based optical data has the potential to explicate the directional information on the activation of the brain. Thus brain connectivity studies are performed by computing covariance/correlations between spatial units using this frequency-domain based optical measurements. The preliminary results indicate that the extent of synchrony and directional variation in the pattern of activation varies in the left and right frontal cortex. The results have significant implication for research in neural pathways associated with autism that can be mapped using diffuse optical imaging tools in the future.