1,736 results match your criteria Journal of Neural Engineering [Journal]


Decoding neural activity to predict rat locomotion using intracortical and epidural arrays.

J Neural Eng 2019 Feb 12. Epub 2019 Feb 12.

Biomedical Engineering Department, Northwestern University, Chicago, Illinois, UNITED STATES.

Objective: Recovery of voluntary gait after spinal cord injury (SCI) requires the restoration of effective motor cortical commands, either by means of a mechanical connection to the limbs, or by restored functional connections to muscles. The latter approach might use functional electrical stimulation (FES), driven by cortical activity, to restore voluntary movements. Moreover, there is evidence that this peripheral stimulation, synchronized with patients' voluntary effort, can strengthen descending projections and recovery. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0698DOI Listing
February 2019

Cortical recruitment and functional dynamics in postural control adaptation and habituation during vibratory proprioceptive stimulation.

J Neural Eng 2019 Feb 12. Epub 2019 Feb 12.

Biomedical and Neural Engineering, Haskolinn i Reykjavik, Reykjavik, ICELAND.

Objective: Maintaining upright posture is a complex task governed by the integration of afferent sensorimotor and visual information with compensatory neuromuscular reactions. The objective of the present work was to characterize the visual dependency and functional dynamics of cortical activation during postural control. Approach. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0678DOI Listing
February 2019

Intraneural sensory feedback restores grip force control and motor coordination while using a prosthetic hand.

J Neural Eng 2019 Feb 8. Epub 2019 Feb 8.

BioRobotics Institute, Scuola Superiore Sant'Anna, Pontedera, ITALY.

Objective: Tactile afferents in the human hand provide fundamental information about hand-environment interactions, which is used by the brain to adapt the motor output to the physical properties of the object being manipulated. A hand amputation disrupts both afferent and efferent pathways from/to the hand, completely invalidating the individual's motor repertoire. Although motor functions may be partially recovered by using a myoelectric prosthesis, providing functionally effective sensory feedback to users of prosthetics is a largely unsolved challenge. Read More

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http://dx.doi.org/10.1088/1741-2552/ab059bDOI Listing
February 2019
1 Read

Parallel, minimally-invasive implantation of ultra-flexible neural electrode arrays.

J Neural Eng 2019 Feb 8. Epub 2019 Feb 8.

Biomedical Engineering, University of Texas at Austin, 107 W Dean Keeton Street, Austin, Texas, 78705, UNITED STATES.

Objective: Implanted microelectrodes provide a unique means to directly interface with the nervous system, but have been limited by the lack of stable functionality. There is growing evidence suggesting that substantially reducing the mechanical rigidity of neural electrodes promotes tissue compatibility and improves their recording stability in both short- and long-terms. However, the miniaturized dimensions and ultraflexibility desired for mitigating tissue responses preclude the probe's self-supported penetration into the brain tissue. Read More

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http://dx.doi.org/10.1088/1741-2552/ab05b6DOI Listing
February 2019
1 Read

A thin-film multichannel electrode for muscle recording and stimulation in neuroprosthetics applications.

J Neural Eng 2019 Feb 5. Epub 2019 Feb 5.

Department of Bioengineering, Imperial College London, London, SW7 2AZ, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.

Objective: We propose, design and test a novel thin-film multichannel electrode that can be used for both recording from and stimulating a muscle in acute implants.

Approach: The system is built on a substrate of polyimide and contains 12 recording and 3 stimulation sites made of platinum. The structure is 420 µm wide, 20 µm thick and embeds the recording and stimulation contacts on the two sides of the polyimide over an approximate length of 2 cm. Read More

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http://dx.doi.org/10.1088/1741-2552/ab047aDOI Listing
February 2019

Dynamics of motor cortical activity during naturalistic feeding behavior.

J Neural Eng 2019 Feb 5. Epub 2019 Feb 5.

Psychiatry, New York University School of Medicine, One Park Avenue, Rm 226, New York, New York, 10016, UNITED STATES.

Objective: The orofacial primary motor cortex (MIo) plays a critical role in controlling tongue and jaw movements during oral motor functions, such as chewing, swallowing and speech. However, the neural mechanisms of MIo during naturalistic feeding are still poorly understood. There is a strong need for a systematic study of motor cortical dynamics during feeding behavior. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0474DOI Listing
February 2019
3 Reads

Potential EEG biomarkers of sedation doses in intensive care patients unveiled by using a machine learning approach.

J Neural Eng 2019 Jan 31. Epub 2019 Jan 31.

Instituto de Investigacion Sanitaria Hospital Universitario de la Princesa, Madrid, SPAIN.

Objective: Sedation of neurocritically ill patients is one of the most challenging situation in ICUs. Quantitative knowledge on the sedation effect on brain activity in that complex scenario could help to uncover new markers for sedation assessment. Hence, we aim to evaluate the existence of changes of diverse EEG-derived measures in deeply-sedated (RASS -Richmond Agitation-Sedation Scale- -4 and -5) neurocritically ill patients, and also whether sedation doses are related with those eventual changes. Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/ab039f
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http://dx.doi.org/10.1088/1741-2552/ab039fDOI Listing
January 2019
2 Reads

How does the presence of neural probes affect extracellular potentials?

J Neural Eng 2019 Jan 31. Epub 2019 Jan 31.

Simula Research Laboratory AS, Oslo, NORWAY.

Objective: Mechanistic modeling of neurons is an essential component of computational neuroscience that enables scientists to simulate, explain, and explore neural activity. The conventional approach to simulation of extracellular neural recordings first computes transmembrane currents using the cable equation and then sums their contribution to model the extracellular potential. This two-step approach relies on the assumption that the extracellular space is an infinite and homogeneous conductive medium, while measurements are performed using neural probes. Read More

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http://dx.doi.org/10.1088/1741-2552/ab03a1DOI Listing
January 2019

Feature extraction of four-class motor imagery EEG signals based on functional brain network.

J Neural Eng 2019 Jan 30. Epub 2019 Jan 30.

School of Engineering, Cardiff University, Cardiff, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.

Objective: A motor-imagery-based brain-computer interface (MI-BCI) provides an alternative way for people to interface with the outside world. However, the classification accuracy of MI signals remains challenging, especially with an increased number of classes and the presence of high variations with data from multiple individual people. This work investigates electroencephalogram (EEG) signal processing techniques, aiming to enhance the classification performance of multiple MI tasks in terms of tackling the challenges caused by the vast variety of subjects. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0328DOI Listing
January 2019

CMOS stimulating chips capable of wirelessly driving 473 electrodes for a cortical vision prosthesis.

J Neural Eng 2019 Jan 28. Epub 2019 Jan 28.

Electrical and Computer Systems Engineering, Monash University, Clayton, Victoria, AUSTRALIA.

Objective: Implantable neural stimulating and recording devices have the potential to restore capabilities such as vision or motor control to disabled patients, improving quality of life. Implants with a large number of stimulating electrodes typically utilize implanted batteries and/or subcutaneous wiring to deal with their high-power consumption and high data throughput needed to address all electrodes with low latency. The use of batteries places severe limitations on the implant's size, usable duty cycle, device longevity while subcutaneous wiring increases the risk of infection and mechanical damage due to device movement. Read More

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http://dx.doi.org/10.1088/1741-2552/ab021bDOI Listing
January 2019

Microstate functional connectivity in EEG cognitive task revealed by multivariate Gaussian hidden Markov model with phase locking value.

J Neural Eng 2019 Jan 23. Epub 2019 Jan 23.

Graduate-program of Medical System Engineering (GMSE), Gwangju Institute of Science and Technology, Gwangju, Gwangju, KOREA, REPUBLIC OF.

Objective: Tracking the spatiotemporal fast (~100 ms) transient networks remains challenging due to a limited understanding of neural activity dynamics as well as a lack of relevant sophisticated methodologies. In this study, we introduce a novel approach to identify simultaneously distinct EEG microstates and their corresponding microstate functional connectivity (μFC) networks in which each μFC network is associated with a distinguished connectivity pattern of recurrent neuronal activity. Approach: The introduced approach is based on a multivariate Gaussian hidden Markov model to decompose the sensor-space stochastic multi-subject event-related potential into quasi-stable EEG microstates. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0169DOI Listing
January 2019
1 Read

Probing prefrontal cortex hemodynamic alterations during facial emotion recognition for major depression disorder through functional near-infrared spectroscopy.

J Neural Eng 2019 Jan 22. Epub 2019 Jan 22.

Institute of Biomedical Engineering, Xi'an Jiaotong University, Xi'an, CHINA.

Objective: A serious issue in psychiatric practice is a lack of specific, objective biomarker to assist clinicians in establishing differential diagnosis and improving individualized treatment. Major depression disorder (MDD) is characterized by poorer ability in processing of facial emotional expressions.

Approach: Applying a portable neuroimaging system using near-infrared spectroscopy, we investigated the prefrontal cortex hemodynamic activation changes during facial emotion recognition and rest periods for 27 MDD patients compared with 24 healthy controls (HC). Read More

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http://dx.doi.org/10.1088/1741-2552/ab0093DOI Listing
January 2019
4 Reads

An electroneurography-based assay for identifying injured nerve segment during surgery: design and in-vivo application in the rat.

J Neural Eng 2019 Jan 17. Epub 2019 Jan 17.

Chang Gung University College of Medicine, Kwei-shan, TAIWAN.

Nerve injury is the main reason for nerve reconstruction surgery, during which the surgeon must determine the location of the injured nerve segment, resect it, and reconnect the remaining healthy nerve stump ends within a limited time. Given this importance, an assay needed to determine the exact location of the injured nerve segment, but no tool has yet fulfilled this need so that a visual inspection of the nerve is still the primary method of identifying the injured segment. We designed a flexible multi-electrode array sensor that records the electroneurographic signal (ENG) as the action potential elicited by electrical stimulation that propagates along the nerve upon both orthodromic and antidromic stimulation. Read More

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http://dx.doi.org/10.1088/1741-2552/aaff90DOI Listing
January 2019
3 Reads

Network organization of coopetitive genetic influences on morphologies of human cerebral cortex.

J Neural Eng 2019 Jan 17. Epub 2019 Jan 17.

Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.

Objective: Brain can be represented as a network, where anatomical regions are nodes and relations between regions are edges. Within a network, co-existence of cooperative and competitive relationships between different nodes is called coopetition. Inter-regional genetic influences on morphological phenotypes (thickness, surface area) of cerebral cortex display such coopetitive relationships. Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/aaff85
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http://dx.doi.org/10.1088/1741-2552/aaff85DOI Listing
January 2019
1 Read

Faces, locations, and tools: a proposed two-stimulus P300 brain computer interface.

J Neural Eng 2019 Jan 16. Epub 2019 Jan 16.

Department of Psychology, East Tennessee State University, PO Box 70649, Johnson City, TN 37614, Johnson City, Tennessee, UNITED STATES.

Brain Computer Interface (BCI) technology can be important for those unable to communicate due to loss of muscle control. Given that the P300 Speller provides a relatively slow rate of communication, highly accurate classification is of great importance. Previous studies have shown that alternative stimuli (e. Read More

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http://dx.doi.org/10.1088/1741-2552/aaff22DOI Listing
January 2019

Spatial localization of EEG electrodes using 3D scanning.

J Neural Eng 2019 Jan 11;16(2):026020. Epub 2019 Jan 11.

Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.

Objective: A reliable reconstruction of neural activity using high-density electroencephalography (EEG) requires an accurate spatial localization of EEG electrodes aligned to the structural magnetic resonance (MR) image of an individual's head. Current technologies for electrode positioning, such as electromagnetic digitization, are yet characterized by non-negligible localization and co-registration errors. In this study, we propose an automated method for spatial localization of EEG electrodes using 3D scanning, a non-invasive and easy-to-use technology with potential applications in clinical settings. Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/aafdd1
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http://dx.doi.org/10.1088/1741-2552/aafdd1DOI Listing
January 2019
8 Reads

Classification of motor imagery and execution signals with population-level feature sets: Implications for probe design in fNIRS based BCI.

J Neural Eng 2019 Jan 11. Epub 2019 Jan 11.

Department of Medical Engineering, Acibadem Universitesi, Istanbul, TURKEY.

Objective: The aim of this study was to introduce a novel methodology for classification of brain hemodynamic responses collected via functional near infrared spectroscopy (fNIRS) during rest, motor imagery (MI) and motor execution (ME) tasks which involves generating population-level training sets. Main Approach: A 48 channel fNIRS system was utilized to obtain hemodynamic signals from the frontal (FC), primary motor (PMC) and somatosensory cortex (SMC) of 10 subjects during an experimental paradigm consisting of ME and MI of various right hand movements. Classification accuracies of random forest (RF), support vector machines (SVM), and artificial neural networks (ANN) were computed at the single subject level by training each classifier with subject specific features, and at the group level by training with features from all subjects for ME vs. Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/aafdca
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http://dx.doi.org/10.1088/1741-2552/aafdcaDOI Listing
January 2019
9 Reads

A penalized time-frequency band feature selection and classification procedure for improved motor intention decoding in multichannel EEG.

J Neural Eng 2019 Feb 9;16(1):016019. Epub 2019 Jan 9.

Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional, UNL, CONICET, Santa Fe, Argentina. Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland. Facultad de Ingeniería, Universidad Nacional de Entre Ríos (FI-UNER), Oro Verde, Entre Ríos, Argentina.

Objective: Motor imagery brain-computer interfaces (MI-BCIs) based on electroencephalography (EEG), a promising technology to provide assistance and support rehabilitation of neurological patients with sensorimotor impairments, require a reliable and adaptable subject-specific model to efficiently decode motor intention. The most popular EEG feature extraction algorithm for MI-BCIs is the common spatial patterns (CSP) method, but its performance strongly depends on the predefined frequency band and time segment length for analyzing the EEG signal.

Approach: In this work, a novel method for efficiently decoding motor intention for EEG-based BCIs performing multiple frequency band analysis in multiple EEG segments is presented. Read More

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http://dx.doi.org/10.1088/1741-2552/aaf046DOI Listing
February 2019
1 Read

The first deaf-blind patient in Russia with Argus II retinal prosthesis system: what he sees and why.

J Neural Eng 2019 Jan 8;16(2):025002. Epub 2019 Jan 8.

ANO Laboratory Senor-Tech, 101/1 Prospect Mira, Moscow 129085, Russia.

Objective: In this study, we propose a new method for evaluating the functional results based on the sizes of phosphenes that the patient drew which were then digitalized. We also describe the methodology of psychological testing and support for a deaf-blind patient.

Approach: A 59-year-old man with retinitis pigmentosa and hearing loss (clinical Usher syndrome) underwent surgery to implant the Argus II retinal prosthesis system in his right eye. Read More

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http://dx.doi.org/10.1088/1741-2552/aafc76DOI Listing
January 2019
3 Reads

Behavioral validation of a wireless low-power neurostimulation technology in a conditioned place preference task.

J Neural Eng 2019 Jan 8;16(2):026022. Epub 2019 Jan 8.

Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02129, United States of America.

Objective: Neurostimulation technologies are important for studying neural circuits and the connections that underlie neurological and psychiatric disorders. However, current methods come with limitations such as the restraint on movement imposed by the wires delivering stimulation. The objective of this study was to assess whether the e-Particle (EP), a novel wireless neurostimulator, could sufficiently stimulate the brain to modify behavior without these limitations. Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/aafc72
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http://dx.doi.org/10.1088/1741-2552/aafc72DOI Listing
January 2019
7 Reads

An EOG-based wheelchair robotic arm system for assisting patients with severe spinal cord injuries.

J Neural Eng 2019 Jan 8;16(2):026021. Epub 2019 Jan 8.

Center for Brain Computer Interfaces and Brain Information Processing, South China University of Technology, Guangzhou 510640, People's Republic of China.

Objective: In this study, we combine a wheelchair and an intelligent robotic arm based on an electrooculogram (EOG) signal to help patients with spinal cord injuries (SCIs) accomplish a self-drinking task. The main challenge is to accurately control the wheelchair to ensure that the randomly located object is within a limited reachable space of the robotic arm (length: 0.8 m; width: 0. Read More

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http://dx.doi.org/10.1088/1741-2552/aafc88DOI Listing
January 2019
1 Read

Reconstruction of post-synaptic potentials by reverse modeling of local field potentials.

J Neural Eng 2019 Jan 4;16(2):026023. Epub 2019 Jan 4.

Univ Rennes, INSERM, LTSI-U1099, F-35000 Rennes, France.

Objective: Among electrophysiological signals, local field potentials (LFPs) are extensively used to study brain activity, either in vivo or in vitro. LFPs are recorded with extracellular electrodes implanted in brain tissue. They reflect intermingled excitatory and inhibitory processes in neuronal assemblies. Read More

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http://dx.doi.org/10.1088/1741-2552/aafbfbDOI Listing
January 2019

Comparative performance of the finite element method and the boundary element fast multipole method for problems mimicking transcranial magnetic stimulation (TMS).

J Neural Eng 2019 Jan 3;16(2):024001. Epub 2019 Jan 3.

ECE Department, Worcester Polytechnic Institute, Worcester, MA 01609, United States of America.

Objective: A study pertinent to the numerical modeling of cortical neurostimulation is conducted in an effort to compare the performance of the finite element method (FEM) and an original formulation of the boundary element fast multipole method (BEM-FMM) at matched computational performance metrics.

Approach: We consider two problems: (i) a canonic multi-sphere geometry and an external magnetic-dipole excitation where the analytical solution is available and; (ii) a problem with realistic head models excited by a realistic coil geometry. In the first case, the FEM algorithm tested is a fast open-source getDP solver running within the SimNIBS 2. Read More

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http://dx.doi.org/10.1088/1741-2552/aafbb9DOI Listing
January 2019

Benchmarking transcranial electrical stimulation finite element models: a comparison study.

J Neural Eng 2019 Jan 3;16(2):026019. Epub 2019 Jan 3.

Department of Clinical and Health Psychology, Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, United States of America.

Objective: To compare field measure differences in simulations of transcranial electrical stimulation (tES) generated by variations in finite element (FE) models due to boundary condition specification, use of tissue compartment smoothing filters, and use of free or structured tetrahedral meshes based on magnetic resonance imaging (MRI) data.

Approach: A structural MRI head volume was acquired at 1 mm resolution and segmented into ten tissue compartments. Predicted current densities and electric fields were computed in segmented models using modeling pipelines involving either an in-house (block) or a commercial platform commonly used in previous FE tES studies involving smoothed compartments and free meshing procedures (smooth). Read More

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http://dx.doi.org/10.1088/1741-2552/aafbbdDOI Listing
January 2019

Classification and regression of spatio-temporal signals using NeuCube and its realization on SpiNNaker neuromorphic hardware.

J Neural Eng 2018 Dec 21;16(2):026014. Epub 2018 Dec 21.

Department of Mechanical Engineering, Technical University of Munich, Munich, Germany.

Objective: The objective of this work is to use the capability of spiking neural networks to capture the spatio-temporal information encoded in time-series signals and decode them without the use of hand-crafted features and vector-based learning and the realization of the spiking model on low-power neuromorphic hardware.

Approach: The NeuCube spiking model was used to classify different grasp movements directly from raw surface electromyography signals (sEMG), the estimations of the applied finger forces as well as the classification of two motor imagery movements from raw electroencephalography (EEG). In a parallel investigation, the designed spiking decoder was implemented on SpiNNaker neuromorphic hardware, which allows low-energy real-time processing. Read More

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http://dx.doi.org/10.1088/1741-2552/aafabcDOI Listing
December 2018
2 Reads

Computational modeling of a single-element transcranial focused ultrasound transducer for subthalamic nucleus stimulation.

J Neural Eng 2018 Dec 20;16(2):026015. Epub 2018 Dec 20.

Department of Information Technology, WAVES research group, Ghent University, Ghent, Belgium.

Objective: While transcranial focused ultrasound is a very promising neuromodulation technique for its non-invasiveness and high spatial resolution, its application to the human deep brain regions such as the subthalamic nucleus (STN) is relatively new. The objective of this study is to design a simple ultrasound transducer and study the transcranial wave propagation through a highly realistic human head model. The effects of skull morphology and skull and brain tissue properties on the focusing performance and energy deposition must therefore be known. Read More

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http://dx.doi.org/10.1088/1741-2552/aafa38DOI Listing
December 2018
2 Reads

Home monitoring of sleep with a temporary-tattoo EEG, EOG and EMG electrode array: a feasibility study.

J Neural Eng 2018 Dec 19;16(2):026024. Epub 2018 Dec 19.

Tel Aviv Sourasky Medical Center (TASMC), Tel Aviv, Israel. Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv, Israel.

Objective: Circadian and sleep dysfunction have long been symptomatic hallmarks of a variety of devastating neurodegenerative conditions. The gold standard for sleep monitoring is overnight sleep in a polysomnography (PSG) laboratory. However, this method has several limitations such as availability, cost and being labour-intensive. Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/aafa05
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http://dx.doi.org/10.1088/1741-2552/aafa05DOI Listing
December 2018
1 Read

Cloud computing for seizure detection in implanted neural devices.

J Neural Eng 2018 Dec 18;16(2):026016. Epub 2018 Dec 18.

Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America. Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America.

Objective: Closed-loop implantable neural stimulators are an exciting treatment option for patients with medically refractory epilepsy, with a number of new devices in or nearing clinical trials. These devices must accurately detect a variety of seizure types in order to reliably deliver therapeutic stimulation. While effective, broadly-applicable seizure detection algorithms have recently been published, these methods are too computationally intensive to be directly deployed in an implantable device. Read More

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http://dx.doi.org/10.1088/1741-2552/aaf92eDOI Listing
December 2018

Stimulation strategies for selective activation of retinal ganglion cell soma and threshold reduction.

J Neural Eng 2018 Dec 18;16(2):026017. Epub 2018 Dec 18.

Center for Bioelectronic Medicine & Biomedical Science, Feinstein Institute for Medical Research, Manhasset, NY 11030, United States of America.

Objective: Retinal prosthetic implants restore partial vision to patients blinded due to outer retinal degeneration, using a camera-guided multielectrode array (MEA) that electrically stimulates surviving retinal neurons. Commercial epi-retinal prostheses use millisecond-scale charge-balanced, symmetric, cathodic-first biphasic pulses to depolarize retinal ganglion cells (RGCs) and bipolar cells (BCs), frequently creating oblong perceptions of light related to axonal activation of RGCs. Stimulation strategies that avoid axonal stimulation and decrease the threshold of targeted neurons may significantly improve prosthetic vision in terms of spatial resolution and power efficiency. Read More

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http://dx.doi.org/10.1088/1741-2552/aaf92bDOI Listing
December 2018

Electron transfer processes occurring on platinum neural stimulating electrodes: pulsing experiments for cathodic-first, charge-imbalanced, biphasic pulses for 0.566  ⩽  k  ⩽  2.3 in rat subcutaneous tissues.

J Neural Eng 2018 Dec 18;16(2):026018. Epub 2018 Dec 18.

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America.

Objective: Charge injection through platinum neural stimulation electrodes is often constrained by the Shannon limit (Shannon 1992 IEEE Trans. Biomed. Eng. Read More

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http://dx.doi.org/10.1088/1741-2552/aaf931DOI Listing
December 2018

Tracking feature-based attention.

J Neural Eng 2019 Feb 31;16(1):016022. Epub 2018 Oct 31.

Department of Cognitive Sciences, University of California, Irvine, Irvine, CA 92627, United States of America.

Objective: Feature-based attention (FBA) helps one detect objects with a particular color, motion, or orientation. FBA works globally; the attended feature is enhanced at all positions in the visual field. This global property of FBA lets one use stimuli presented in the peripheral visual field to track attention in a task presented centrally. Read More

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http://dx.doi.org/10.1088/1741-2552/aaed17DOI Listing
February 2019
1 Read

Motor unit drive: a neural interface for real-time upper limb prosthetic control.

J Neural Eng 2019 Feb 24;16(1):016012. Epub 2018 Oct 24.

Delsys Inc. and Altec Inc., Natick, MA, United States of America. Department of Robotics Engineering, Human Inspired Robotics Laboratory, Worcester Polytechnic Institute, Worcester, MA, United States of America.

Objective: Modern prosthetic limbs have made strident gains in recent years, incorporating terminal electromechanical devices that are capable of mimicking the human hand. However, access to these advanced control capabilities has been prevented by fundamental limitations of amplitude-based myoelectric neural interfaces, which have remained virtually unchanged for over four decades. Consequently, nearly 23% of adults and 32% of children with major traumatic or congenital upper-limb loss abandon regular use of their myoelectric prosthesis. Read More

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http://dx.doi.org/10.1088/1741-2552/aaeb0fDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6349039PMC
February 2019
7 Reads

Rhythmic modulation of thalamic oscillations depends on intrinsic cellular dynamics.

J Neural Eng 2019 Feb 24;16(1):016013. Epub 2018 Oct 24.

Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States of America.

Objective: Rhythmic brain stimulation has emerged as a powerful tool to modulate cognition and to target pathological oscillations related to neurological and psychiatric disorders. However, we lack a systematic understanding of how periodic stimulation interacts with endogenous neural activity as a function of the brain state and target.

Approach: To address this critical issue, we applied periodic stimulation to a unified biophysical thalamic network model that generates multiple distinct oscillations, and examined thoroughly the impact of rhythmic stimulation on different oscillatory states. Read More

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http://stacks.iop.org/1741-2552/16/i=1/a=016013?key=crossref
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http://dx.doi.org/10.1088/1741-2552/aaeb03DOI Listing
February 2019
7 Reads

Micro-channel sieve electrode for concurrent bidirectional peripheral nerve interface. Part B: stimulation.

J Neural Eng 2018 Nov 9;16(2):026002. Epub 2018 Nov 9.

Department of Biomedical Engineering, Washington University, St. Louis, MO 63130, United States of America.

Objective: Successful use of a prosthetic limb by an amputee is facilitated by haptic feedback-both a sense of touch and proprioception. Stimulating afferent fibers within peripheral nerves has been shown to provide somatosensation enabling amputees to modulate the control of prosthetic limbs. Peripheral nerve interfaces (PNIs) have also been used to decode patients' motor intentions. Read More

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http://dx.doi.org/10.1088/1741-2552/aaefabDOI Listing
November 2018
1 Read

Autoencoders for learning template spectrograms in electrocorticographic signals.

J Neural Eng 2019 Feb 15;16(1):016025. Epub 2018 Nov 15.

Department of Electrical and Computer Engineering, University of California- San Diego, San Diego, CA, United States of America.

Objective: Electrocorticography (ECoG) based studies generally analyze features from specific frequency bands selected by manual evaluation of spectral power. However, the definition of these features can vary across subjects, cortical areas, tasks and across time for a given subject. We propose an autoencoder based approach for summarizing ECoG data with 'template spectrograms', i. Read More

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http://dx.doi.org/10.1088/1741-2552/aaf13fDOI Listing
February 2019

A high-density carbon fiber neural recording array technology.

J Neural Eng 2019 Feb 16;16(1):016024. Epub 2018 Oct 16.

Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, United States of America. Center for Neural Engineering and Prostheses, University of California, Berkeley/San Francisco, CA, United States of America.

Objective: Microwire and Utah-style neural recording arrays are the predominant devices used for cortical neural recording, but the implanted electrodes cause a significant adverse biological response and suffer from well-studied performance degradation. Recent work has demonstrated that carbon fiber electrodes do not elicit this same adverse response, but these existing designs are not practically scalable to hundreds or thousands of recording sites. We present technology that overcomes these issues while additionally providing fine electrode pitch for spatial oversampling. Read More

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http://dx.doi.org/10.1088/1741-2552/aae8d9DOI Listing
February 2019

Inter-subject transfer learning with an end-to-end deep convolutional neural network for EEG-based BCI.

J Neural Eng 2018 Nov 26;16(2):026007. Epub 2018 Nov 26.

School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore. Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore.

Objective: Despite the effective application of deep learning (DL) in brain-computer interface (BCI) systems, the successful execution of this technique, especially for inter-subject classification, in cognitive BCI has not been accomplished yet. In this paper, we propose a framework based on the deep convolutional neural network (CNN) to detect the attentive mental state from single-channel raw electroencephalography (EEG) data.

Approach: We develop an end-to-end deep CNN to decode the attentional information from an EEG time series. Read More

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http://dx.doi.org/10.1088/1741-2552/aaf3f6DOI Listing
November 2018
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Decoding motor neuron activity from epimysial thin-film electrode recordings following targeted muscle reinnervation.

J Neural Eng 2019 Feb 1;16(1):016010. Epub 2018 Nov 1.

Department of Bioengineering, Imperial College London, London, United Kingdom.

Objective: Surface electromyography (EMG) is currently used as a control signal for active prostheses in amputees who underwent targeted muscle reinnervation (TMR) surgery. Recent research has shown that it is possible to access the spiking activity of spinal motor neurons from multi-channel surface EMG. In this study, we propose the use of multi-channel epimysial EMG electrodes as an interface for decoding motor neurons activity following TMR. Read More

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http://stacks.iop.org/1741-2552/16/i=1/a=016010?key=crossref
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http://dx.doi.org/10.1088/1741-2552/aaed85DOI Listing
February 2019
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On the robustness of real-time myoelectric control investigations: a multiday Fitts' law approach.

J Neural Eng 2018 Oct 19;16(2):026003. Epub 2018 Oct 19.

SMI, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark. SMME, National University of Sciences and Technology, Islamabad, Pakistan.

Objective: Real-time myoelectric experimental protocol is considered as a means to quantify usability of myoelectric control schemes. While usability should be considered over time to assure clinical robustness, all real-time studies reported thus far are limited to a single session or day and thus the influence of time on real-time performance is still unexplored. In this study, the aim was to develop a novel experimental protocol to quantify the effect of time on real-time performance measures over multiple days using a Fitts' law approach. Read More

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http://dx.doi.org/10.1088/1741-2552/aae9d4DOI Listing
October 2018

Calculating deep brain stimulation amplitudes and power consumption by constrained optimization.

J Neural Eng 2019 Feb 6;16(1):016020. Epub 2018 Nov 6.

Department of Information Technology, Uppsala University, Box 337, 75105 Uppsala, Sweden.

Objective: Deep brain stimulation (DBS) consists of delivering electrical stimuli to a brain target via an implanted lead to treat neurological and psychiatric conditions. Individualized stimulation is vital to ensure therapeutic results, since DBS may otherwise become ineffective or cause undesirable side effects. Since the DBS pulse generator is battery-driven, power consumption incurred by the stimulation is important. Read More

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http://dx.doi.org/10.1088/1741-2552/aaeeb7DOI Listing
February 2019

Micro-channel sieve electrode for concurrent bidirectional peripheral nerve interface. Part A: recording.

J Neural Eng 2018 Nov 9;16(2):026001. Epub 2018 Nov 9.

Department of Biomedical Engineering, Washington University, St. Louis, MO 63130, United States of America.

Objective: Advancement in prosthetic limb technology requires corresponding improvements in the capability of the amputee to naturally control the device via original motor pathways while simultaneously receiving haptic feedback via sensory pathways. Recording efferent axonal activity using a peripheral neural interface (PNI) allows a good tradeoff between invasiveness and selectivity while possibly preserving the phenomenology of controlling the original limb. One such PNI, the thin-film transverse intrafascicular multichannel electrode (tfTIME), has been shown to be successful in controlling powered prosthetics. Read More

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http://dx.doi.org/10.1088/1741-2552/aaefcfDOI Listing
November 2018

Simulation of visual perception and learning with a retinal prosthesis.

J Neural Eng 2018 Nov 20. Epub 2018 Nov 20.

Stanford University, Stanford, California, UNITED STATES.

The nature of artificial vision with a retinal prosthesis, and the degree to which the brain can adapt to the unnatural input from such a device, are poorly understood. Therefore, the development of current and future devices may be aided by theory and simulations that help to infer and understand what prosthesis patients see. A biologically-informed, extensible computational framework is presented here to predict visual perception and the potential effect of learning with a subretinal prosthesis. Read More

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http://dx.doi.org/10.1088/1741-2552/aaf270DOI Listing
November 2018

Global activity shaping strategies for a retinal implant.

J Neural Eng 2018 Nov 13;16(2):026008. Epub 2018 Nov 13.

Department of Biomedical Engineering, The University of Melbourne, Parkville, Victoria, Australia.

Objective: Retinal prostheses provide visual perception via electrical stimulation of the retina using an implanted array of electrodes. The retinal activation resulting from each electrode is not point-like; instead each electrode introduces a spread of retinal activation that may overlap with activations from other electrodes. With most conventional stimulation strategies this overlap leads to image blur. Read More

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http://dx.doi.org/10.1088/1741-2552/aaf071DOI Listing
November 2018

Development and performance of a biomimetic artificial perilymph for in vitro testing of medical devices.

J Neural Eng 2018 Nov 28;16(2):026006. Epub 2018 Nov 28.

Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.

Objective: Cochlear implants interface with the fluid in the cochlea called perilymph. The volume of this fluid present in human and animal model cochlea is prohibitively low for isolation for in vitro studies. Thus, there is a need for an artificial perilymph that reflects the complexity of this fluid in terms of competitive protein adsorption. Read More

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http://dx.doi.org/10.1088/1741-2552/aaf482DOI Listing
November 2018

Combination of high-frequency SSVEP-based BCI and computer vision for controlling a robotic arm.

J Neural Eng 2018 Dec 3;16(2):026012. Epub 2018 Dec 3.

Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300192, People's Republic of China.

Objective: Recent attempts in developing brain-computer interface (BCI)-controlled robots have shown the potential of this area in the field of assistive robots. However, implementing the process of picking and placing objects using a BCI-controlled robotic arm still remains challenging. BCI performance, system portability, and user comfort need to be further improved. Read More

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http://dx.doi.org/10.1088/1741-2552/aaf594DOI Listing
December 2018
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Direct information transfer rate optimisation for SSVEP-based BCI.

J Neural Eng 2019 Feb 16;16(1):016016. Epub 2018 Oct 16.

Institute of Computer Science, University of Tartu, Tartu, Estonia.

Objective: In this work, a classification method for steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) is proposed. The method is based on information transfer rate (ITR) maximisation.

Approach: The proposed classification method uses features extracted by traditional SSVEP-based BCI methods and finds optimal discrimination thresholds for each feature to classify the targets. Read More

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http://dx.doi.org/10.1088/1741-2552/aae8c7DOI Listing
February 2019

Epiretinal stimulation with local returns enhances selectivity at cellular resolution.

J Neural Eng 2018 Nov 7;16(2):025001. Epub 2018 Nov 7.

Departments of Neurosurgery, Ophthalmology, and Hansen Experimental Physics Laboratory, Stanford University, Stanford, CA, United States of America.

Objective: Epiretinal prostheses are designed to restore vision in people blinded by photoreceptor degenerative diseases, by directly activating retinal ganglion cells (RGCs) using an electrode array implanted on the retina. In present-day clinical devices, current spread from the stimulating electrode to a distant return electrode often results in the activation of many cells, potentially limiting the quality of artificial vision. In the laboratory, epiretinal activation of RGCs with cellular resolution has been demonstrated with small electrodes, but distant returns may still cause undesirable current spread. Read More

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http://dx.doi.org/10.1088/1741-2552/aaeef1DOI Listing
November 2018
3 Reads

Neural correlates of speech quality dimensions analyzed using electroencephalography (EEG).

J Neural Eng 2018 Nov 15. Epub 2018 Nov 15.

Quality and Usability Lab, Technische Universitat Berlin Fakultat IV Elektrotechnik und Informatik, Ernst-Reuter-Platz 7, TEL-18 /QULab, Berlin, Berlin, 10587, GERMANY.

Objective: By means of subjective psychophysical methods, quality of transmitted speech has been decomposed into three perceptual dimensions named "discontinuity" (F), "noisiness" (N) and "coloration" (C). Previous studies using electroencephalography (EEG) already reported effects of perceived intensity of single quality dimensions on electrical brain activity. However, it has not been investigated so far, whether the dimensions themselves are dissociable on a electrophysiological level of analysis. Read More

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http://dx.doi.org/10.1088/1741-2552/aaf122DOI Listing
November 2018
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A comprehensive review of EEG-based brain-computer interface paradigms.

J Neural Eng 2019 Feb 15;16(1):011001. Epub 2018 Nov 15.

Department of Neurology, University of California, San Francisco/Berkeley, CA 94158, United States of America. Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, United States of America.

Advances in brain science and computer technology in the past decade have led to exciting developments in brain-computer interface (BCI), thereby making BCI a top research area in applied science. The renaissance of BCI opens new methods of neurorehabilitation for physically disabled people (e.g. Read More

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http://dx.doi.org/10.1088/1741-2552/aaf12eDOI Listing
February 2019
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Diffusion geometry approach to efficiently remove electrical stimulation artifacts in intracranial electroencephalography.

J Neural Eng 2018 Nov 21. Epub 2018 Nov 21.

Department of Mathematics, University of Toronto, Toronto, Ontario, CANADA.

Objective: Cortical oscillations, electrophysiological activity patterns, associated with cognitive functions and impaired in many psychiatric disorders can be observed in intracranial electroencephalography (iEEG). Direct cortical stimulation (DCS) may directly target these oscillations and may serve as therapeutic approaches to restore functional impairments. However, the presence of electrical stimulation artifacts in neurophysiological data limits the analysis of the effects of stimulation. Read More

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http://dx.doi.org/10.1088/1741-2552/aaf2baDOI Listing
November 2018
1 Read