In the last 30 days

• Open/close A silicon retina that reproduces signals in the optic nerve

  Kareem A Zaghloul and Kwabena Boahen  2006 J. Neural Eng. 3 257 Tag this article

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  Prosthetic devices may someday be used to treat lesions of the central nervous system. Similar to neural circuits, these prosthetic devices should adapt their properties over time, independent of external control. Here we describe an artificial retina, constructed in silicon using single-transistor synaptic primitives, with two forms of locally controlled adaptation: luminance adaptation and contrast gain control. Both forms of adaptation rely on local modulation of synaptic strength, thus meeting the criteria of internal control. Our device is the first to reproduce the responses of the four major ganglion cell types that drive visual cortex, producing 3600 spiking outputs in total. We demonstrate how the responses of our device's ganglion cells compare to those measured from the mammalian retina. Replicating the retina's synaptic organization in our chip made it possible to perform these computations using a hundred times less energy than a microprocessor—and to match the mammalian retina in size and weight. With this level of efficiency and autonomy, it is now possible to develop fully implantable intraocular prostheses.

• Open/close What is Neural Engineering?

  D M Durand  2006 J. Neural Eng. 4 Tag this article

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  It is only recently that the term Neural Engineering or Neuroengineering first appeared. The emergence of this new field can be attributed to the recognition that engineers, neuroscientists and clinicians should be working together to address the problems associated with the complexity of the nervous system. Neural engineering has generated a lot of excitement not only for the development of interfaces between the brain and computers but for its mostly untapped potential to develop treatment for patients with neurological disorders such as strokes or epilepsy. Now the field has matured significantly as evidenced by its strong and regular presence at various conferences around the world and the growth in the number of published papers in the area. As a result, the scope of the field has evolved and a clear definition of neural engineering is needed. The editorial board of the Journal of Neural Engineering defines the field as follows: `Neural Engineering is an emerging interdisciplinary research area that brings to bear neuroscience and engineering methods to analyze neurological function as well as to design solutions to problems associated with neurological limitations and dysfunction'. The main goal of the field is to solve neuroscience-related problems and to provide rehabilitative solutions for nervous system conditions. The emphasis on engineering and quantitative methodology applied to the nervous system distinguishes neural engineering from traditional areas in neuroscience such as neurophysiology. The integration between neuroscience and engineering separates neural engineering from other engineering disciplines such as artificial neural networks.

  Neural engineering is situated between and draws heavily from basic neuroscience on one hand and clinical neuroscience (neurology) on the other. The field of neural engineering encompasses experimental, computational, theoretical, clinical and applied aspects of research areas at the molecular, cellular and systems levels. Although overlap between various topics exists (i.e. neuromodulation and neuroprostheses), all these areas are well established and have recognizable identities.

  Neural Engineering Scope

  • brain-machine (computer) interface
  • neural interfacing
  • neurotechnology
  • neuroelectronics
  • neuromodulation
  • neural prostheses
  • neural control
  • neuro-rehabilitation
  • neuro-diagnostics
  • neuro-therapeutics
  • neuromechanical systems
  • neurorobotics
  • neuroinformatics
  • neuroimaging
  • neural circuits: artificial and biological
  • neuromorphic engineering
  • neural tissue regeneration
  • neural signal processing
  • theoretical and computational neuroscience
  • systems neuroscience
  • translational neuroscience
  

  However, the definition and scope of neural engineering are best determined by the scientists and engineers that practice it and this is only an overview of the field as it is understood today. The future of this exciting new field will be determined not by what we believe neural engineering should be but by its success in improving human health and quality of life through restoration and enhancement of the function of the nervous system.

• Open/close Relationship between speed and EEG activity during imagined and executed hand movements

  Han Yuan et al  2010 J. Neural Eng. 7 026001 Tag this article

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  The relationship between primary motor cortex and movement kinematics has been shown in nonhuman primate studies of hand reaching or drawing tasks. Studies have demonstrated that the neural activities accompanying or immediately preceding the movement encode the direction, speed and other information. Here we investigated the relationship between the kinematics of imagined and actual hand movement, i.e. the clenching speed, and the EEG activity in ten human subjects. Study participants were asked to perform and imagine clenching of the left hand and right hand at various speeds. The EEG activity in the alpha (8–12 Hz) and beta (18–28 Hz) frequency bands were found to be linearly correlated with the speed of imagery clenching. Similar parametric modulation was also found during the execution of hand movements. A single equation relating the EEG activity to the speed and the hand (left versus right) was developed. This equation, which contained a linear independent combination of the two parameters, described the time-varying neural activity during the tasks. Based on the model, a regression approach was developed to decode the two parameters from the multiple-channel EEG signals. We demonstrated the continuous decoding of dynamic hand and speed information of the imagined clenching. In particular, the time-varying clenching speed was reconstructed in a bell-shaped profile. Our findings suggest an application to providing continuous and complex control of noninvasive brain–computer interface for movement-impaired paralytics.

• Open/close Multi-site optical excitation using ChR2 and micro-LED array

  Nir Grossman et al  2010 J. Neural Eng. 7 016004 Tag this article

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  Studying neuronal processes such as synaptic summation, dendritic physiology and neural network dynamics requires complex spatiotemporal control over neuronal activities. The recent development of neural photosensitization tools, such as channelrhodopsin-2 (ChR2), offers new opportunities for non-invasive, flexible and cell-specific neuronal stimulation. Previously, complex spatiotemporal control of photosensitized neurons has been limited by the lack of appropriate optical devices which can provide 2D stimulation with sufficient irradiance. Here we present a simple and powerful solution that is based on an array of high-power micro light-emitting diodes (micro-LEDs) that can generate arbitrary optical excitation patterns on a neuronal sample with micrometre and millisecond resolution. We first describe the design and fabrication of the system and characterize its capabilities. We then demonstrate its capacity to elicit precise electrophysiological responses in cultured and slice neurons expressing ChR2.

• Open/close Integrated device for optical stimulation and spatiotemporal electrical recording of neural activity in light-sensitized brain tissue

  Jiayi Zhang et al  2009 J. Neural Eng. 6 055007 Tag this article

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  Neural stimulation with high spatial and temporal precision is desirable both for studying the real-time dynamics of neural networks and for prospective clinical treatment of neurological diseases. Optical stimulation of genetically targeted neurons expressing the light sensitive channel protein Channelrhodopsin (ChR2) has recently been reported as a means for millisecond temporal control of neuronal spiking activities with cell-type selectivity. This offers the prospect of enabling local delivery of optical stimulation and the simultaneous monitoring of the neural activity by electrophysiological means, both in the vicinity of and distant to the stimulation site. We report here a novel dual-modality hybrid device, which consists of a tapered coaxial optical waveguide ('optrode') integrated into a 100 element intra-cortical multi-electrode recording array. We first demonstrate the dual optical delivery and electrical recording capability of the single optrode in in vitro preparations of mouse retina, photo-stimulating the native retinal photoreceptors while recording light-responsive activities from ganglion cells. The dual-modality array device was then used in ChR2 transfected mouse brain slices. Specifically, epileptiform events were reliably optically triggered by the optrode and their spatiotemporal patterns were simultaneously recorded by the multi-electrode array.

• Open/close A review of classification algorithms for EEG-based brain–computer interfaces

  F Lotte et al  2007 J. Neural Eng. 4 R1 Tag this article

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  In this paper we review classification algorithms used to design brain–computer interface (BCI) systems based on electroencephalography (EEG). We briefly present the commonly employed algorithms and describe their critical properties. Based on the literature, we compare them in terms of performance and provide guidelines to choose the suitable classification algorithm(s) for a specific BCI.

• Open/close A brain–computer interface using electrocorticographic signals in humans

  Eric C Leuthardt et al  2004 J. Neural Eng. 1 63 Tag this article

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  Brain–computer interfaces (BCIs) enable users to control devices with electroencephalographic (EEG) activity from the scalp or with single-neuron activity from within the brain. Both methods have disadvantages: EEG has limited resolution and requires extensive training, while single-neuron recording entails significant clinical risks and has limited stability. We demonstrate here for the first time that electrocorticographic (ECoG) activity recorded from the surface of the brain can enable users to control a one-dimensional computer cursor rapidly and accurately. We first identified ECoG signals that were associated with different types of motor and speech imagery. Over brief training periods of 3–24 min, four patients then used these signals to master closed-loop control and to achieve success rates of 74–100% in a one-dimensional binary task. In additional open-loop experiments, we found that ECoG signals at frequencies up to 180 Hz encoded substantial information about the direction of two-dimensional joystick movements. Our results suggest that an ECoG-based BCI could provide for people with severe motor disabilities a non-muscular communication and control option that is more powerful than EEG-based BCIs and is potentially more stable and less traumatic than BCIs that use electrodes penetrating the brain.

• Open/close The synchronous neural interactions test as a functional neuromarker for post-traumatic stress disorder (PTSD): a robust classification method based on the bootstrap

  A P Georgopoulos et al  2010 J. Neural Eng. 7 016011 Tag this article

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  Traumatic experiences can produce post-traumatic stress disorder (PTSD) which is a debilitating condition and for which no biomarker currently exists (Institute of Medicine (US) 2006 Posttraumatic Stress Disorder: Diagnosis and Assessment (Washington, DC: National Academies)). Here we show that the synchronous neural interactions (SNI) test which assesses the functional interactions among neural populations derived from magnetoencephalographic (MEG) recordings ( Georgopoulos A P et al 2007 J. Neural Eng. 4 349–55) can successfully differentiate PTSD patients from healthy control subjects. Externally cross-validated, bootstrap-based analyses yielded >90% overall accuracy of classification. In addition, all but one of 18 patients who were not receiving medications for their disease were correctly classified. Altogether, these findings document robust differences in brain function between the PTSD and control groups that can be used for differential diagnosis and which possess the potential for assessing and monitoring disease progression and effects of therapy.

• Open/close An optical neural interface: in vivo control of rodent motor cortex with integrated fiberoptic and optogenetic technology

  Alexander M Aravanis et al  2007 J. Neural Eng. 4 S143 Tag this article

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  Neural interface technology has made enormous strides in recent years but stimulating electrodes remain incapable of reliably targeting specific cell types (e.g. excitatory or inhibitory neurons) within neural tissue. This obstacle has major scientific and clinical implications. For example, there is intense debate among physicians, neuroengineers and neuroscientists regarding the relevant cell types recruited during deep brain stimulation (DBS); moreover, many debilitating side effects of DBS likely result from lack of cell-type specificity. We describe here a novel optical neural interface technology that will allow neuroengineers to optically address specific cell types in vivo with millisecond temporal precision. Channelrhodopsin-2 (ChR2), an algal light-activated ion channel we developed for use in mammals, can give rise to safe, light-driven stimulation of CNS neurons on a timescale of milliseconds. Because ChR2 is genetically targetable, specific populations of neurons even sparsely embedded within intact circuitry can be stimulated with high temporal precision. Here we report the first in vivo behavioral demonstration of a functional optical neural interface (ONI) in intact animals, involving integrated fiberoptic and optogenetic technology. We developed a solid-state laser diode system that can be pulsed with millisecond precision, outputs 20 mW of power at 473 nm, and is coupled to a lightweight, flexible multimode optical fiber, ~200 µm in diameter. To capitalize on the unique advantages of this system, we specifically targeted ChR2 to excitatory cells in vivo with the CaMKIIα promoter. Under these conditions, the intensity of light exiting the fiber (~380 mW mm ⁻²) was sufficient to drive excitatory neurons in vivo and control motor cortex function with behavioral output in intact rodents. No exogenous chemical cofactor was needed at any point, a crucial finding for in vivo work in large mammals. Achieving modulation of behavior with optical control of neuronal subtypes may give rise to fundamental network-level insights complementary to what electrode methodologies have taught us, and the emerging optogenetic toolkit may find application across a broad range of neuroscience, neuroengineering and clinical questions.

• Open/close A survey of signal processing algorithms in brain–computer interfaces based on electrical brain signals

  Ali Bashashati et al  2007 J. Neural Eng. 4 R32 Tag this article

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  Brain–computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals. In the BCI literature, however, there is no comprehensive review of the signal processing techniques used. This work presents the first such comprehensive survey of all BCI designs using electrical signal recordings published prior to January 2006. Detailed results from this survey are presented and discussed. The following key research questions are addressed: (1) what are the key signal processing components of a BCI, (2) what signal processing algorithms have been used in BCIs and (3) which signal processing techniques have received more attention?