Journal of Neural Engineering (J Neural Eng )

Publisher: Institute of Physics (Great Britain)


Journal of Neural Engineering is a new forum for the interdisciplinary field of neural engineering, where neuroscientists, neurobiologists and engineers can publish their work in one periodical that bridges the gap between neuroscience and engineering. Articles will cover the field of neural engineering at the molecular, cellular and systems levels.

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    Journal of Neural Engineering website
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    Journal of neural engineering (Online), Neural engineering, JNE
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    Document, Periodical, Internet resource
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    Internet Resource, Computer File, Journal / Magazine / Newspaper

Publications in this journal

  • Journal of Neural Engineering 09/2014;
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    ABSTRACT: Myoelectric control is filled with potential to significantly change human–robot interaction due to the ability to non-invasively measure human motion intent. However, current control schemes have struggled to achieve the robust performance that is necessary for use in commercial applications. As demands in myoelectric control trend toward simultaneous multifunctional control, multi-muscle coordinations, or synergies, play larger roles in the success of the control scheme. Detecting and refining patterns in muscle activations robust to the high variance and transient changes associated with surface electromyography is essential for efficient, user-friendly control. This article reviews the role of muscle synergies in myoelectric control schemes by dissecting each component of the scheme with respect to associated challenges for achieving robust simultaneous control of myoelectric interfaces. Electromyography recording details, signal feature extraction, pattern recognition and motor learning based control schemes are considered, and future directions are proposed as steps toward fulfilling the potential of myoelectric control in clinically and commercially viable applications.
    Journal of Neural Engineering 09/2014; 11(5):051001.
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    ABSTRACT: Objective. Laser surface modification of platinum (Pt) electrodes was investigated for use in neuroprosthetics. Surface modification was applied to increase the surface area of the electrode and improve its ability to transfer charge within safe electrochemical stimulation limits. Approach. Electrode arrays were laser micromachined to produce Pt electrodes with smooth surfaces, which were then modified with four laser patterning techniques to produce surface structures which were nanosecond patterned, square profile, triangular profile and roughened on the micron scale through structured laser interference patterning (SLIP). Improvements in charge transfer were shown through electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and biphasic stimulation at clinically relevant levels. A new method was investigated and validated which enabled the assessment of in vivo electrochemically safe charge injection limits. Main results. All of the modified surfaces provided electrical advantage over the smooth Pt. The SLIP surface provided the greatest benefit both in vitro and in vivo, and this surface was the only type which had injection limits above the threshold for neural stimulation, at a level shown to produce a response in the feline visual cortex when using an electrode array implanted in the suprachoroidal space of the eye. This surface was found to be stable when stimulated with more than 150 million clinically relevant pulses in physiological saline. Significance. Critical to the assessment of implant devices is accurate determination of safe usage limits in an in vivo environment. Laser patterning, in particular SLIP, is a superior technique for improving the performance of implant electrodes without altering the interfacial electrode chemistry through coating. Future work will require chronic in vivo assessment of these electrode patterns.
    Journal of Neural Engineering 09/2014; 11(5):056017.
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    ABSTRACT: Objective. The dorsal root ganglion is an attractive target for implanting neural electrode arrays that restore sensory function or provide therapy via stimulation. However, penetrating microelectrodes designed for these applications are small and deliver low currents. For long-term performance of microstimulation devices, novel coating materials are needed in part to decrease impedance values at the electrode-tissue interface and to increase charge storage capacity. Approach. Conductive polymer poly(3,4-ethylenedioxythiophene) (PEDOT) and multi-wall carbon nanotubes (CNTs) were coated on the electrode surface and doped with the antiinflammatory drug, dexamethasone. Electrode characteristics and the tissue reaction around neural electrodes as the result of stimulation, coating and drug release were characterized. Hematoxylin and eosin staining along with antibodies recognizing Iba1 (microglia/macrophages), NF200 (neuronal axons), NeuN (neurons), vimentin (fibroblasts), caspase-3 (cell death) and L1 (neural cell adhesion molecule) were used. Quantitative image analyses were performed using MATLAB. Main results. Our results indicate that coated microelectrodes have lower in vitro and in vivo impedance values. Significantly less neuronal death/damage was observed with coated electrodes as compared to non-coated controls. The inflammatory response with the PEDOT/CNT-coated electrodes was also reduced. Significance. This study is the first to report on the utility of these coatings in stimulation applications. Our results indicate PEDOT/CNT coatings may be valuable additions to implantable electrodes used as therapeutic modalities.
    Journal of Neural Engineering 09/2014;
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    ABSTRACT: Objective. Stimulation of peripheral nerves is often superimposed on ongoing motor and sensory activity in the same axons, without a quantitative model of the net action potential train at the axon endpoint. Approach. We develop a model of action potential patterns elicited by superimposing constant frequency axonal stimulation on the action potentials arriving from a physiologically activated neural source. The model includes interactions due to collision block, resetting of the neural impulse generator, and the refractory period of the axon at the point of stimulation. Main results. Both the mean endpoint firing rate and the probability distribution of the action potential firing periods depend strongly on the relative firing rates of the two sources and the intersite conduction time between them. When the stimulus rate exceeds the neural rate, neural action potentials do not reach the endpoint and the rate of endpoint action potentials is the same as the stimulus rate, regardless of the intersite conduction time. However, when the stimulus rate is less than the neural rate, and the intersite conduction time is short, the two rates partially sum. Increases in stimulus rate produce non-monotonic increases in endpoint rate and continuously increasing block of neurally generated action potentials. Rate summation is reduced and more neural action potentials are blocked as the intersite conduction time increases. At long intersite conduction times, the endpoint rate simplifies to being the maximum of either the neural or the stimulus rate. Significance. This study highlights the potential of increasing the endpoint action potential rate and preserving neural information transmission by low rate stimulation with short intersite conduction times. Intersite conduction times can be decreased with proximal stimulation sites for muscles and distal stimulation sites for sensory endings. The model provides a basis for optimizing experiments and designing neuroprosthetic interventions involving motor or sensory stimulation.
    Journal of Neural Engineering 08/2014; 11(5):056016.
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    ABSTRACT: Objective. Established biophysical neurone models have achieved limited success in reproducing electrophysiological responses to non-invasive stimulation of the human nervous system. This is related to our insufficient knowledge of the induced electric currents inside the human body. Despite the numerous research and clinical applications of non-invasive stimulation, it is still unclear which internal sites are actually affected by it. Approach. We performed multi-scale computer simulations that, by making use of advances in computing power and numerical algorithms, combine a microscopic model of electrical excitation of neurones with a macroscopic electromagnetic model of the realistic whole-body anatomy. Main results. The simulations yield responses consistent with those experimentally recorded following magnetic and electrical motor root stimulation in human subjects, and reproduce the observed amplitudes and latencies for a wide variety of stimulation parameters. Significance. Our findings demonstrate that modern computational techniques can produce detailed predictions about which and where neurones are activated, leading to improved understanding of the physics and basic mechanisms of non-invasive stimulation and enabling potential new applications that make use of improved targeting of stimulation.
    Journal of Neural Engineering 08/2014; 11(5):056013.
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    ABSTRACT: Objective. Kilohertz frequency alternating current (KHFAC) waveforms have been shown to provide peripheral nerve conductivity block in many acute and chronic animal models. KHFAC nerve block could be used to address multiple disorders caused by neural over-activity, including blocking pain and spasticity. However, one drawback of KHFAC block is a transient activation of nerve fibers during the initiation of the nerve block, called the onset response. The objective of this study is to evaluate the feasibility of using charge balanced direct current (CBDC) waveforms to temporarily block motor nerve conductivity distally to the KHFAC electrodes to mitigate the block onset-response. Approach. A total of eight animals were used in this study. A set of four animals were used to assess feasibility and reproducibility of a combined KHFAC + CBDC block. A following randomized study, conducted on a second set of four animals, compared the onset response resulting from KHFAC alone and combined KHFAC + CBDC waveforms. To quantify the onset, peak forces and the force-time integral were measured during KHFAC block initiation. Nerve conductivity was monitored throughout the study by comparing muscle twitch forces evoked by supra-maximal stimulation proximal and distal to the block electrodes. Each animal of the randomized study received at least 300 s (range: 318–1563 s) of cumulative dc to investigate the impact of combined KHFAC + CBDC on nerve viability. Main results. The peak onset force was reduced significantly from 20.73 N (range: 18.6–26.5 N) with KHFAC alone to 0.45 N (range: 0.2–0.7 N) with the combined CBDC and KHFAC block waveform (p < 0.001). The area under the force curve was reduced from 6.8 Ns (range: 3.5–21.9 Ns) to 0.54 Ns (range: 0.18–0.86 Ns) (p < 0.01). No change in nerve conductivity was observed after application of the combined KHFAC + CBDC block relative to KHFAC waveforms. Significance. The distal application of CBDC can significantly reduce or even completely prevent the KHFAC onset response without a change in nerve conductivity.
    Journal of Neural Engineering 08/2014; 11(5):056012.
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    ABSTRACT: Objective. Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the in vivo assessment of functional activity of the cerebral cortex as well as in the field of brain–computer interface (BCI) research. A common challenge for the utilization of fNIRS in these areas is a stable and reliable investigation of the spatio-temporal hemodynamic patterns. However, the recorded patterns may be influenced and superimposed by signals generated from physiological processes, resulting in an inaccurate estimation of the cortical activity. Up to now only a few studies have investigated these influences, and still less has been attempted to remove/reduce these influences. The present study aims to gain insights into the reduction of physiological rhythms in hemodynamic signals (oxygenated hemoglobin (oxy-Hb), deoxygenated hemoglobin (deoxy-Hb)). Approach. We introduce the use of three different signal processing approaches (spatial filtering, a common average reference (CAR) method; independent component analysis (ICA); and transfer function (TF) models) to reduce the influence of respiratory and blood pressure (BP) rhythms on the hemodynamic responses. Main results. All approaches produce large reductions in BP and respiration influences on the oxy-Hb signals and, therefore, improve the contrast-to-noise ratio (CNR). In contrast, for deoxy-Hb signals CAR and ICA did not improve the CNR. However, for the TF approach, a CNR-improvement in deoxy-Hb can also be found. Significance. The present study investigates the application of different signal processing approaches to reduce the influences of physiological rhythms on the hemodynamic responses. In addition to the identification of the best signal processing method, we also show the importance of noise reduction in fNIRS data.
    Journal of Neural Engineering 08/2014; 11(5):056010.
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    ABSTRACT: Objective. The fact that all human action is preceded by brain processes partially observable through neuroimaging devices such as electroencephalography (EEG) is currently being explored in a number of applications. A recent study by Haufe et al (2011 J. Neural Eng. 8 056001) demonstrates the possibility of performing fast detection of forced emergency brakings during driving based on EEG and electromyography, and discusses the use of such neurotechnology for braking assistance systems. Since the study was conducted in a driving simulator, its significance regarding real-world applicability needs to be assessed. Approach. Here, we replicate that experimental paradigm in a real car on a non-public test track. Main results. Our results resemble those of the simulator study, both qualitatively (in terms of the neurophysiological phenomena observed and utilized) and quantitatively (in terms of the predictive improvement achievable using electrophysiology in addition to behavioral measures). Moreover, our findings are robust with respect to a temporary secondary auditory task mimicking verbal input from a fellow passenger. Significance. Our study serves as a real-world verification of the feasibility of electrophysiology-based detection of emergency braking intention as proposed in Haufe et al (2011 J. Neural Eng. 8 056001).
    Journal of Neural Engineering 08/2014; 11(5):056011.
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    ABSTRACT: Objective. Recent studies have shown the possibility of simultaneous and proportional control of electrically powered upper-limb prostheses, but there has been little investigation on optimal channel selection. The objective of this study is to find a robust channel selection method and the channel subsets most suitable for simultaneous and proportional myoelectric prosthesis control of multiple degrees-of-freedom (DoFs). Approach. Ten able-bodied subjects and one person with congenital upper-limb deficiency took part in this study, and performed wrist movements with various combinations of two DoFs (flexion/extension and radial/ulnar deviation). During the experiment, high density electromyographic (EMG) signals and the actual wrist angles were recorded with an 8 × 24 electrode array and a motion tracking system, respectively. The wrist angles were estimated from EMG features with ridge regression using the subsets of channels chosen by three different channel selection methods: (1) least absolute shrinkage and selection operator (LASSO), (2) sequential feature selection (SFS), and (3) uniform selection (UNI). Main results. SFS generally showed higher estimation accuracy than LASSO and UNI, but LASSO always outperformed SFS in terms of robustness, such as noise addition, channel shift and training data reduction. It was also confirmed that about 95% of the original performance obtained using all channels can be retained with only 12 bipolar channels individually selected by LASSO and SFS. Significance. From the analysis results, it can be concluded that LASSO is a promising channel selection method for accurate simultaneous and proportional prosthesis control. We expect that our results will provide a useful guideline to select optimal channel subsets when developing clinical myoelectric prosthesis control systems based on continuous movements with multiple DoFs.
    Journal of Neural Engineering 08/2014; 11(5):056008.
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    ABSTRACT: Objective. Brain-computer interfaces (BCIs) are a promising technology for restoring motor ability to paralyzed patients. Spiking-based BCIs have successfully been used in clinical trials to control multi-degree-of-freedom robotic devices. Current implementations of these devices require a lengthy spike-sorting step, which is an obstacle to moving this technology from the lab to the clinic. A viable alternative is to avoid spike-sorting, treating all threshold crossings of the voltage waveform on an electrode as coming from one putative neuron. It is not known, however, how much decoding information might be lost by ignoring spike identity. Approach. We present a full analysis of the effects of spike-sorting schemes on decoding performance. Specifically, we compare how well two common decoders, the optimal linear estimator and the Kalman filter, reconstruct the arm movements of non-human primates performing reaching tasks, when receiving input from various sorting schemes. The schemes we tested included: using threshold crossings without spike-sorting; expert-sorting discarding the noise; expert-sorting, including the noise as if it were another neuron; and automatic spike-sorting using waveform features. We also decoded from a joint statistical model for the waveforms and tuning curves, which does not involve an explicit spike-sorting step. Main results. Discarding the threshold crossings that cannot be assigned to neurons degrades decoding: no spikes should be discarded. Decoding based on spike-sorted units outperforms decoding based on electrodes voltage crossings: spike-sorting is useful. The four waveform based spike-sorting methods tested here yield similar decoding efficiencies: a fast and simple method is competitive. Decoding using the joint waveform and tuning model shows promise but is not consistently superior. Significance. Our results indicate that simple automated spike-sorting performs as well as the more computationally or manually intensive methods used here. Even basic spike-sorting adds value to the low-threshold waveform-crossing methods often employed in BCI decoding.
    Journal of Neural Engineering 08/2014; 11(5):056005.
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    ABSTRACT: Objective. We developed a detailed model of the spinal circuitry plus musculoskeletal system (SC + MS) for the primate arm and investigated its role in sensorimotor control, learning and storing of movement repertoires. Approach. Recently developed models of spinal circuit connectivity, neurons and muscle force/energetics were integrated and in some cases refined to construct the most comprehensive model of the SC + MS to date. The SC + MS's potential contributions to center-out reaching movement were assessed by employing an extremely simple model of the brain that issued only step commands. Main results. The SC + MS was able to generate physiological muscle dynamics underlying reaching across different directions, distances, speeds, and even in the midst of strong dynamic perturbations (i.e. viscous curl field). For each task, there were many different combinations of brain inputs that generated physiological performance. Natural patterns of recruitment and low metabolic cost emerged for about half of the learning trials when a purely kinematic cost function was used and for all of the trials when an estimate of metabolic energy consumption was added to the cost function. Solutions for different tasks could be interpolated to generate intermediate movement and the range over which interpolation was successful was consistent with experimental reports. Significance. This is the first demonstration that a realistic model of the SC + MS is capable of generating the required dynamics of center-out reaching. The interpolability observed is important for the feasibility of storing motor programs in memory rather than computing them from internal models of the musculoskeletal plant. Successful interpolation of command programs required them to have similar muscle recruitment patterns, which are thought by many to arise from hard-wired muscle synergies rather than learned as in our model system. These properties of the SC + MS along with its tendency to generate energetically efficient solutions might usefully be employed by motor cortex to generate voluntary behaviors such as reaching to targets.
    Journal of Neural Engineering 08/2014; 11(5):056006.
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    ABSTRACT: Objective. Characterizing the intention to move by means of electroencephalographic activity can be used in rehabilitation protocols with patients' cortical activity taking an active role during the intervention. In such applications, the reliability of the intention estimation is critical both in terms of specificity 'number of misclassifications' and temporal accuracy. Here, a detector of the onset of voluntary upper-limb reaching movements based on the cortical rhythms and the slow cortical potentials is proposed. The improvement in detections due to the combination of these two cortical patterns is also studied. Approach. Upper-limb movements and cortical activity were recorded in healthy subjects and stroke patients performing self-paced reaching movements. A logistic regression combined the output of two classifiers: (i) a naïve Bayes classifier trained to detect the event-related desynchronization preceding the movement onset and (ii) a matched filter detecting the bereitschaftspotential. The proposed detector was compared with the detectors by using each one of these cortical patterns separately. In addition, differences between the patients and healthy subjects were analysed. Main results. On average, 74.5 ± 13.8% and 82.2 ± 10.4% of the movements were detected with 1.32 ± 0.87 and 1.50 ± 1.09 false detections generated per minute in the healthy subjects and the patients, respectively. A significantly better performance was achieved by the combined detector (as compared to the detectors of the two cortical patterns separately) in terms of true detections (p = 0.099) and false positives (p = 0.0083). Significance. A rationale is provided for combining information from cortical rhythms and slow cortical potentials to detect the onsets of voluntary upper-limb movements. It is demonstrated that the two cortical processes supply complementary information that can be summed up to boost the performance of the detector. Successful results have been also obtained with stroke patients, which supports the use of the proposed system in brain-computer interface applications with this group of patients.
    Journal of Neural Engineering 08/2014; 11(5):056009.
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    ABSTRACT: Objective. The speed of brain-computer interfaces (BCI), based on event-related potentials (ERP), is inherently limited by the commonly used one-stimulus paradigm. In this paper, we introduce a novel paradigm that can increase the spelling speed by a factor of 2, thereby extending the one-stimulus paradigm to a two-stimulus paradigm. Two different stimuli (a face and a symbol) are presented at the same time, superimposed on different characters and ERPs are classified using a multi-class classifier. Here, we present the proof-of-principle that is achieved with healthy participants. Approach. Eight participants were confronted with the novel two-stimulus paradigm and, for comparison, with two one-stimulus paradigms that used either one of the stimuli. Classification accuracies (percentage of correctly predicted letters) and elicited ERPs from the three paradigms were compared in a comprehensive offline analysis. Main results. The accuracies slightly decreased with the novel system compared to the established one-stimulus face paradigm. However, the use of two stimuli allowed for spelling at twice the maximum speed of the one-stimulus paradigms, and participants still achieved an average accuracy of 81.25%. This study introduced an alternative way of increasing the spelling speed in ERP-BCIs and illustrated that ERP-BCIs may not yet have reached their speed limit. Future research is needed in order to improve the reliability of the novel approach, as some participants displayed reduced accuracies. Furthermore, a comparison to the most recent BCI systems with individually adjusted, rapid stimulus timing is needed to draw conclusions about the practical relevance of the proposed paradigm. Significance. We introduced a novel two-stimulus paradigm that might be of high value for users who have reached the speed limit with the current one-stimulus ERP-BCI systems.
    Journal of Neural Engineering 07/2014; 11(5):056004.
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    ABSTRACT: Objective. Before peripheral nerve electrodes can be used for the restoration of sensory and motor functions in patients with neurological disorders, the behavioral and histological consequences of these devices must be investigated. These indices of biocompatibility can be defined in terms of desired functional outcomes; for example, a device may be considered for use as a therapeutic intervention if the implanted subject retains functional neurons post-implantation even in the presence of a foreign body response. The consequences of an indwelling device may remain localized to cellular responses at the device-tissue interface, such as fibrotic encapsulation of the device, or they may affect the animal more globally, such as impacting behavioral or sensorimotor functions. The objective of this study was to investigate the overall consequences of implantation of high-electrode count intrafascicular peripheral nerve arrays, High Density Utah Slanted Electrode Arrays (HD-USEAs; 25 electrodes mm−2). Approach. HD-USEAs were implanted in rat sciatic nerves for one and two month periods. We monitored wheel running, noxious sensory paw withdrawal reflexes, footprints, nerve morphology and macrophage presence at the tissue-device interface. In addition, we used a novel approach to contain the arrays in actively behaving animals that consisted of an organic nerve wrap. A total of 500 electrodes were implanted across all ten animals. Main results. The results demonstrated that chronic implantation (≤8 weeks) of HD-USEAs into peripheral nerves can evoke behavioral deficits that recover over time. Morphology of the nerve distal to the implantation site showed variable signs of nerve fiber degeneration and regeneration. Cytology adjacent to the device-tissue interface also showed a variable response, with some electrodes having many macrophages surrounding the electrodes, while other electrodes had few or no macrophages present. This variability was also seen along the length of the electrodes. Axons remained within the proximity of the electrode tips at the distances required for theoretically effective stimulation and recording (≤100 μm). Significance. We conclude from these studies that HD-USEAs do not cause overall global effects on the animals, at least up to the two-month period investigated here. These results demonstrate for the first time that the consequences of high-electrode count intrafascicular arrays compare with other peripheral nerve electrodes currently available for clinical or investigational neuromodulation.
    Journal of Neural Engineering 07/2014; 11(4):046027.
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    ABSTRACT: Objective. We have developed an image analysis methodology for quantifying the anisotropy of neuronal projections on patterned substrates. Approach. Our method is based on the fitting of smoothing splines to the digital traces produced using a non-maximum suppression technique. This enables precise estimates of the local tangents uniformly along the neurite length, and leads to unbiased orientation distributions suitable for objectively assessing the anisotropy induced by tailored surfaces. Main results. In our application, we demonstrate that carbon nanotubes arrayed in parallel bundles over gold surfaces induce a considerable neurite anisotropy; a result which is relevant for regenerative medicine. Significance. Our pipeline is generally applicable to the study of fibrous materials on 2D surfaces and should also find applications in the study of DNA, microtubules, and other polymeric materials.
    Journal of Neural Engineering 06/2014; 11(4):046006.
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    ABSTRACT: Objective. Both electrical stimuli (endogenous and exogenous) and topographical cues are instructive to axonal extension. This report, for the first time, investigated the relative dominance of directional topographical guidance cues and directional electrical cues to enhance and/or direct primary neurite extension. We hypothesized the combination of electrical stimulation with electrospun fiber topography would induce longer neurite extension from dorsal root ganglia neurons than the presence of electrical stimulation or aligned topography alone. Approach. To test the hypothesis, neurite outgrowth was examined on laminin-coated poly-L-lactide films or electrospun fibers (2 µm in diameter) in the presence or absence of electrical stimulation. Immunostained neurons were semi-automatically traced using Neurolucida software and morphology was evaluated. Main Results. Neurite extension increased 74% on the aligned fibers compared to film controls. Stimulation alone increased outgrowth by 32% on films or fibers relative to unstimulated film controls. The co-presentation of topographical (fibers) with biophysical (electrical stimulation) cues resulted in a synergistic 126% increase in outgrowth relative to unstimulated film controls. Field polarity had no influence on the directionality of neurites, indicating topographical cues are responsible for guiding neurite extension. Significance. Both cues (electrical stimulation and fiber geometry) are modular in nature and can be synergistically applied in conjunction with other common methods in regenerative medicine such as controlled release of growth factors to further influence axonal growth in vivo. The combined application of electrical and aligned fiber topographical guidance cues described herein, if translated in vivo, could provide a more supportive environment for directed and robust axonal regeneration following peripheral nerve injury.
    Journal of Neural Engineering 06/2014; 11(4):046002.

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