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Journal of Neural Engineering

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https://www.readbyqxmd.com/read/29781808/tensor-driven-extraction-of-developmental-features-from-varying-paediatric-eeg-datasets
#1
Eli Kinney-Lang, Loukianos Spyrou, Ahmed Ebied, Richard Fm Chin, Javier Escudero
Constant changes in developing children's brains can pose a challenge in EEG dependant technologies. Advancing signal processing methods to identify developmental differences in paediatric populations could help improve function and usability of such technologies. Taking advantage of the multi-dimensional structure of EEG data through tensor analysis may offer a framework for extracting relevant developmental features of paediatric datasets. A proof of concept is demonstrated through identifying latent developmental features in resting-state EEG...
May 21, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29781807/word-recognition-re-thinking-prosthetic-vision-evaluation
#2
Shui'Er Han, Cheng Qiu, Kassandra R Lee, JaeHyun Jung, Eli Peli
Evaluations of vision prostheses and sensory substitution devices have frequently relied on repeated training and testing with the same small set of items. These multiple forced-choice tasks have been shown to produce above chance performance in blind patients, but it is unclear if the observed performance represents restoration of vision that transfers to novel, untrained items. Here, we tested the generalizability of the forced-choice paradigm on the discrimination of low-resolution word images. Extensive visual training was conducted with the same 10 words used in previous BrainPort tongue stimulating studies...
May 21, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29781806/the-need-for-understanding-and-engaging-the-patient-as-consumer-of-products-developed-by-neural-engineering
#3
Jennifer French, J Luis Lujan, Dawn Bardot, Emily Lauren Graczyk, Allison Hess-Dunning, Ronald J Triolo, Megan Moynahan, Winny Tan, Adeline Zbrzeski
Neural Engineering is a discipline at the intersection of neuroscience, engineering, and clinical care. Recent major efforts by government and industry aimed at bringing forth personalized therapies, increasing the potential of the neural engineering industry for future growth, eg. the National Institutes of Health (NIH) Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative and Stimulating Peripheral Activity to Relieve Conditions (SPARC) Common Fund Program, the Defense Advanced Research Projects Agency (DARPA) Electrical Prescriptions (ElectRx) and Systems-Based Neurotechnology for Emerging Therapies (SUBNETS) Programs, and the GlaxoSmithKline Bioelectric Medicines Initiative...
May 21, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29774867/incorporation-of-dynamic-stopping-strategy-into-the-high-speed-ssvep-based-bcis
#4
Jing Jiang, Erwei Yin, Chunhui Wang, Minpeng Xu, Dong Ming
OBJECTIVE: Electroencephalography (EEG) is a non-linear and non-stationary process, as a result, its features are unstable and often vary in quality across trials, which poses significant challenges to brain-computer interfaces (BCIs). One remedy to this problem is to adaptively collect sufficient EEG evidence using dynamic stopping (DS) strategies. The high-speed steady-state visual evoked potential (SSVEP)-based BCI has experienced tremendous progress in recent years. This study aims to further improve the high-speed SSVEP-based BCI by incorporating the DS strategy...
May 18, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29769435/defining-and-quantifying-users-mental-imagery-based-bci-skills-a-first-step
#5
Fabien Lotte, Camille Jeunet
While promising for many applications, Electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) are still scarcely used outside laboratories, due to a poor reliability. It is thus necessary to study and fix this reliability issue. Doing so requires the use of appropriate reliability metrics to quantify both the classification algorithm and the BCI user's performances. So far, Classification Accuracy (CA) is the typical metric used for both aspects. However, we argue in this paper that CA is a poor metric to study BCI users' skills...
May 17, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29761788/block-based-robust-control-of-stepping-using-intraspinal-microstimulation
#6
Ehsan Rouhani, Abbas Erfanian
OBJECTIVE: The problem of motor control using intraspinal microstimulation (ISMS) can be approached at two levels of the motor system: individual muscles (motor pools) and motor primitives. The major challenges of direct ISMS at the level of individual muscle are the number of electrodes that are required to be implanted in order to recruit all muscles involving the motion and the muscle selectivity. One solution to cope with these problems is the control of movement generated by appropriate combination of the movement primitives...
May 15, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29756600/the-development-of-neural-stimulators-a-review-of-preclinical-safety-and-efficacy-studies
#7
Robert K Shepherd, Joel Villalobos, Owen Burns, David Nayagam
OBJECTIVE: Given the rapid expansion of the field of neural stimulation and the rigorous regulatory approval requirements required before these devices can be applied clinically, it is important that there is clarity around conducting preclinical safety and efficacy studies required for the development of this technology. APPROACH: The present review examines basic design principles associated with the development of a safe neural stimulator and describes the suite of preclinical safety studies that need to be considered when taking a device to clinical trial...
May 14, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29749350/adaptive-optimal-input-design-and-parametric-estimation-of-nonlinear-dynamical-systems-application-to-neuronal-modeling
#8
Mahmoud K Madi, Fadi N Karameh
Many physical models of biological processes including neural systems are characterized by parametric nonlinear dynamical relations between driving inputs, internal states, and measured outputs of the process. Fitting such models using experimental data (data assimilation) is a challenging task since the physical process often operates in a noisy, possibly non-stationary environment; moreover, conducting multiple experiments under controlled and repeatable conditions can be impractical, time consuming or costly...
May 11, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29749347/electric-field-encephalography-for-brain-activity-monitoring
#9
Craig William Versek, Tyler Frasca, Jianlin Zhou, Kaushik Chowdhury, Srinivas Sridhar
Objective - We describe an early-stage prototype of a new wireless electrophysiological sensor system, called NeuroDot, which can measure neuroelectric potentials and fields at the scalp in a new modality called Electric Field Encephalography (EFEG). We aim to establish the physical validity of the EFEG modality, and examine some of its properties and relative merits compared to EEG.
 Approach - We designed a wireless neuroelectric measurement device based on the Texas Instrument ADS1299 Analog Front End platform and a sensor montage, using custom electrodes, to simultaneously measure EFEG and spatially averaged EEG over a localized patch of the scalp (2cm x 2cm)...
May 11, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29741160/adaptive-deep-brain-stimulation-for-parkinson-s-disease-using-motor-cortex-sensing
#10
Nicole C Swann, Coralie de Hemptinne, Margaret C Thompson, Svjetlana Miocinovic, Andrew M Miller, Ro'ee Gilron, Jill L Ostrem, Howard J Chizeck, Philip A Starr
OBJECTIVE: Contemporary deep brain stimulation (DBS) for Parkinson's disease is delivered continuously, and adjustments based on patient's changing symptoms must be made manually by a trained clinician. Patients may be subjected to energy intensive settings at times when they are not needed, possibly resulting in stimulation-induced adverse effects, such as dyskinesia. One solution is 'adaptive' DBS, in which stimulation is modified in real time based on neural signals that co-vary with the severity of motor signs or of stimulation-induced adverse effects...
May 9, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29737971/differential-electrical-responses-in-retinal-ganglion-cell-subtypes-effects-of-synaptic-blockade-and-stimulating-electrode-location
#11
Chih Yu Yang, David Tsai, Tianruo Guo, Socrates Dokos, Gregg J Suaning, John W Morley, Nigel H Lovell
OBJECTIVE: Visual prostheses have shown promising results in restoring visual perception to blind patients. The ability to differentially activate retinal ganglion cell (RGC) subtypes could further improve the efficacy of these medical devices. APPROACH: Using whole-cell patch clamp, we investigated membrane potential differences between ON and OFF RGCs in the mouse retina when their synaptic inputs were blocked by synaptic blockers, and examined the differences in stimulation thresholds under such conditions...
May 8, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29737970/multiband-tangent-space-mapping-and-feature-selection-for-classification-of-eeg-during-motor-imagery
#12
Md Rabiul Islam, Toshihisa Tanaka, Md Khademul Islam Molla
Abstract
 Objective. When designing multiclass motor imagery-based brain computer interface (MI-BCI), a so-called tangent space mapping (TSM) method utilizing the geometric structure of covariance matrices is an effective technique. This paper aims to introduce a method using TSM for finding accurate operational frequency bands related brain activities associated with MI tasks.
 
 Approach. A multichannel EEG signal is decomposed into multiple subbands, and tangent features are then estimated on each subband...
May 8, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29735805/in-vitro-assessment-of-the-differences-in-retinal-ganglion-cell-responses-to-intra-and-extracellular-electrical-stimulation
#13
Rebecca Kotsakidis, Hamish Meffin, Michael Ibbotson, Tatiana Kameneva
Objective
 To compare responses of retinal ganglion cells (RGCs) to intracellular and extracellular electrical stimulation of varying frequency and amplitude.
 Approach 
 In vitro patch clamp was used to record the responses of RGCs to sinusoidal current stimulation of varying frequency and amplitude. The results were simulated using the Neuron software package.
 Main results
 The stimulation frequency yielding the greatest response was higher for extracellular stimulation compared to intracellular stimulation in the same cells (256 Hz versus 64 Hz)...
May 8, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29717707/electrode-size-dependent-thresholds-in-subretinal-neuroprosthetic-stimulation
#14
Andrea Corna, Thoralf Herrmann, Guenther Zeck
Retinal prostheses have shown promising results in restoring some visual perception to blind patients but successful identification of objects of different size remains a challenge. Here we investigated electrode-size specific stimulation thresholds and their variability for subretinal electrical stimulation. Our findings indicate the range of charge densities required to achieve identification of small objects and the object-size-specific scaling of stimulation threshold.
 Approach: 
 Using biphasic voltage - limited current stimuli provided by a light-sensitive microchip, we determined threshold charge densities for stimulation with variable electrode sizes...
May 2, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29714718/factors-that-affect-error-potentials-during-a-grasping-task-toward-a-hybrid-natural-movement-decoding-bci
#15
Jason Omedes, Andreas Schwarz, Gernot R Müller-Putz, Luis Montesano
This paper presents a hybrid BCI combining neural correlates of natural movements and interaction error-related potentials (ErrP) to perform a 3D reaching task. It focuses on the impact that design factors of such a hybrid BCI have on the ErrP signatures and in their classification.
 
 Approach. Users attempted to control a 3D virtual interface that simulated their own hand, to reach and grasp two different objects.
 Three factors of interest were modulated during the experimentation: (1) execution speed of the grasping, (2) type of grasping and (3) motor commands generated by motor imagery or real motion...
May 1, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29676287/electrophysiological-correlates-of-neurodegeneration-in-motor-and-non-motor-brain-regions-in-amyotrophic-lateral-sclerosis-implications-for-brain-computer-interfacing
#16
Philipp Kellmeyer, Moritz Grosse-Wentrup, Andreas Schulze-Bonhage, Ulf Ziemann, Tonio Ball
OBJECTIVE: For patients with amyotrophic lateral sclerosis (ALS) who are suffering from severe communication or motor problems, brain-computer interfaces (BCIs) can improve the quality of life and patient autonomy. However, current BCI systems are not as widely used as their potential and patient demand would let assume. This underutilization is a result of technological as well as user-based limitations but also of the comparatively poor performance of currently existing BCIs in patients with late-stage ALS, particularly in the locked-in state...
April 20, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29667934/brain-computer-interaction-for-online-enhancement-of-visuospatial-attention-performance
#17
Romain Trachel, Thomas Brochier, Maureen Clerc
OBJECTIVE: the goal of this study is to investigate whether BCI that decode the location of covert attention can be leveraged to enhance visuospatial attention performance. Here, the covert attention task is to discriminate the orientation of a low-contrast target embedded in dynamic noise. Visuospatial attention performance is measured by the reaction time and the accuracy of target discrimination. APPROACH: The target location is indicated by a central cue made of randomly moving dots providing either predictive or ambiguous information...
April 18, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29664415/model-based-optimal-multipolar-stimulation-without-a-priori-knowledge-of-nerve-structure-application-to-vagus-nerve-stimulation
#18
Melissa Dali, Olivier Rossel, David Andreu, Laure Laporte, Alfredo Hernandez, Jeremy Laforet, Eloi Marijon, Albert Hagège, Maureen Clerc, Christine Henry, David Guiraud
OBJECTIVE: Multipolar cuff electrode can selectively stimulate areas of peripheral nerves and therefore enable to control independent functions. However, the branching and fascicularization are known for a limited set of nerves and the specific organization remains subject-dependent. This paper presents a general modeling and optimization methods in the context of multipolar stimulation using a cuff electrode without a priori knowledge of the nerve structure. Vagus nerve stimulation experiments based on the optimization results were then investigated...
April 17, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29664414/enhanced-total-neurite-outgrowth-and-secondary-branching-in-dorsal-root-ganglion-neurons-elicited-by-low-intensity-pulsed-ultrasound
#19
Daniel Ventre, Marissa Puzan, Emily Ashbolt, Abigail Koppes
OBJECTIVE: Despite the prevalence of peripheral nerve injuries (PNI), challenges remain in restoring full functionality to those afflicted. For recovery to occur, axons must extend across the injury site to connect with distal targets, where injury gap size is a critical factor in the probability of restoration of function. Current clinical therapies often achieve limited neural regeneration, motivating the development of new therapeutic interventions such as biophysical stimulation. APPROACH: To investigate the potential for low intensity, pulsed ultrasonic simulation (LIPUS) to impact peripheral nerve regeneration, primary neonatal rat dorsal root ganglion neurons were examined in vitro in response to ultrasound (US)...
April 17, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29651998/high-resolution-local-field-potentials-measured-with-deep-brain-stimulation-arrays
#20
Simeng Zhang, Allison T Connolly, Lauren Madden, Jerrold L Vitek, Matthew D Johnson
Local field potential (LFP) recordings along a deep brain stimulation (DBS) lead can provide useful feedback for titrating DBS therapy. However, conventional DBS leads with four cylindrical macroelectrodes likely undersample the spatial distribution of sinks and sources in a given brain region. In this study, we investigated the spectral power and spatial feature sizes of LFP activity in non-human primate subthalamic nucleus and globus pallidus using chronically implanted 32-channel directional DBS arrays.
 
 Approach: Subthalamic nucleus and globus pallidus LFP signals were recorded from directional DBS arrays in the resting state and during a reach-and-retrieval task in two non-human primates in naïve and parkinsonian conditions...
April 13, 2018: Journal of Neural Engineering
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