1,775 results match your criteria Journal of Neural Engineering [Journal]


Assessment of changes in neural activity during acquisition of spatial knowledge using EEG signal classification.

J Neural Eng 2019 Apr 17. Epub 2019 Apr 17.

Engineering, Memorial University of Newfoundland, Saint John's, Newfoundland and Labrador, CANADA.

This study explored the classification of electroencephalography (EEG) signals to assess changes in neural activity as individuals performed a training task in a virtual environment simulator. Commonly, task behavior and perception are used to assess a trainee's ability to perform a task, however, changes in cognition are not usually measured and could be important to provide a true indication of an individual's level of knowledge or skill. In this study, 15 participants acquired spatial knowledge via 60 navigation trials (divided into 10 blocks) in a novel virtual environment. Read More

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http://dx.doi.org/10.1088/1741-2552/ab1a95DOI Listing

Minimax-optimal decoding of movement goals from local field potentials using complex spectral features.

J Neural Eng 2019 Apr 16. Epub 2019 Apr 16.

Duke University Pratt School of Engineering, Durham, North Carolina, UNITED STATES.

Objective: We consider the problem of predicting eye movement goals from local field potentials(LFP) recorded through a multielectrode array in the macaque prefrontal cortex. The monkey is tasked with performing memory-guided saccades to one of eight targets during which LFP activity is recorded and used to train a decoder.

Approach: Previous reports have mainly relied on the spectral amplitude of the LFPs as decoding feature, while neglecting the phase without proper theoretical justification. Read More

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http://dx.doi.org/10.1088/1741-2552/ab1a1fDOI Listing

Assaying neural activity of children during video game play in public spaces: A Deep Learning Approach.

J Neural Eng 2019 Apr 11. Epub 2019 Apr 11.

Department of Electrical and Computer Engineering, University of Houston, Houston, Texas, UNITED STATES.

Objective: Understanding neural activity patterns in the developing brain remains one of the grand challenges in neuroscience. Developing neural networks are likely to be endowed with functionally important variability associated with the environmental context, age, gender, and other variables. Therefore, we conducted experiments with typically developing children in a stimulating museum setting and tested the feasibility of using deep learning techniques to help identify patterns of brain activity associated with different conditions. Read More

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http://dx.doi.org/10.1088/1741-2552/ab1876DOI Listing

The impact of evoked cutaneous afferents on voluntary reaching movement in patients with Parkinson's Disease.

J Neural Eng 2019 Apr 11. Epub 2019 Apr 11.

Laboratory of Neurorehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, CHINA.

Objective: Resting tremor may compound the effects of bradykinesia to further prolong the initiation of voluntary movement in patients with Parkinson's disease (PD). However, the interaction between resting tremor and voluntary movements in these PD patients has not been well understood. Recently, we demonstrated that cutaneous afferents evoked by surface stimulation of superficial radial nerve can inhibit resting tremor effectively. Read More

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http://dx.doi.org/10.1088/1741-2552/ab186fDOI Listing

PatcherBot: a single-cell electrophysiology robot for adherent cells and brain slices.

J Neural Eng 2019 Apr 10. Epub 2019 Apr 10.

Georgia Institute of Technology, Atlanta, UNITED STATES.

Objective: Intracellular patch-clamp electrophysiology, one of the most ubiquitous, high-fidelity techniques in biophysics, remains laborious and low-throughput. While previous efforts have succeeded at automating some steps of the technique, here we demonstrate a robotic "PatcherBot" system that can perform many patch-clamp recordings sequentially, fully unattended.

Approach: comprehensive automation is accomplished by outfitting the robot with machine vision, and cleaning pipettes instead of manually exchanging them. Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/ab1834
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http://dx.doi.org/10.1088/1741-2552/ab1834DOI Listing
April 2019
4 Reads

Tissue-engineered nerve grafts using a scaffold-independent and injectable drug delivery system: a novel design with translational advantages.

J Neural Eng 2019 Apr 9. Epub 2019 Apr 9.

Department of Hand Surgery, China-Japan Union Hospital of Jilin University, Changchun, 130031, CHINA.

Objective: Currently commercially available nerve conduits have demonstrated suboptimal clinical efficacy in repairing peripheral nerve defects. Although tissue-engineered nerve grafts (TENGs) with sustained release of neurotrophic factors (NTFs) are experimentally proved to be more effective than these blank conduits, there remains a lack of clinical translation. NTFs are typically immobilized onto scaffold materials of the conduit via adsorption, specific binding or other incorporation techniques. Read More

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http://dx.doi.org/10.1088/1741-2552/ab17a0DOI Listing
April 2019
1 Read

Multiscale noise suppression and feature frequency extraction in SSVEP based on underdamped second-order stochastic resonance.

J Neural Eng 2019 Apr 8. Epub 2019 Apr 8.

School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, P.R. China, Xi'an, CHINA.

Objective: As one of the commonly used control signals of brain-computer interface (BCI), steady-state visual evoked potential (SSVEP) exhibits advantages of stability, periodicity and minimal training requirements. However, SSVEP retains the non-linear, non-stationary and low signal-to-noise ratio (SNR) characteristics of EEG. The traditional SSVEP extraction methods regard noise as harmful information and highlight the useful signal by suppressing the noise. Read More

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http://dx.doi.org/10.1088/1741-2552/ab16f9DOI Listing

Deep-learning for seizure forecasting in canines with epilepsy.

J Neural Eng 2019 Apr 8. Epub 2019 Apr 8.

Neurology, Mayo Clinic, Rochester, Minnesota, UNITED STATES.

Objective: This paper introduces a fully automated, subject-specific deep-learning convolutional neural network (CNN) system for forecasting seizures using ambulatory intracranial EEG (iEEG). The system was tested on a hand-held device (Mayo Epilepsy Assist Device) in a pseudo-prospective mode using iEEG from 4 canines with naturally occurring epilepsy. Approach: The system was trained and tested on 75 seizures collected over 1608 days utilizing a genetic algorithm to optimize forecasting hyper-parameters (prediction horizon, median filter window length, and probability threshold) for each subject-specific seizure forecasting model. Read More

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http://dx.doi.org/10.1088/1741-2552/ab172dDOI Listing
April 2019
2 Reads

Understanding ultrasound neuromodulation using a computationally efficient and interpretable model of intramembrane cavitation.

J Neural Eng 2019 Apr 5. Epub 2019 Apr 5.

Center for Neuroprosthetics and Institute of Bioengineering, Ecole Polytechnique Federale de Lausanne, Lausanne, SWITZERLAND.

Objective: Low-intensity focused ultrasound stimulation (LIFUS) emerges as an attracting technology for noninvasive modulation of neural circuits, yet the underlying action mechanisms remain unclear. The neuronal intramembrane cavitation excitation (NICE) model suggests that LIFUS excites neurons through a complex interplay between microsecond-scale mechanical oscillations of so-called sonophores in the plasma membrane and the development of a millisecond-scale electrical response. This model predicts cell-type-specific responses that correlate indirectly with experimental data, but it is computationally expensive and difficult to interpret, which hinders its potential validation. Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/ab1685
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http://dx.doi.org/10.1088/1741-2552/ab1685DOI Listing
April 2019
2 Reads

P300 indicates context-dependent change in speech quality beyond phonological change.

J Neural Eng 2019 Apr 5. Epub 2019 Apr 5.

Quality and Usability Lab, Technische Universitat Berlin Fakultat IV Elektrotechnik und Informatik, Berlin, Berlin, GERMANY.

Objective: Non-invasive physiological methods like electroencephalography (EEG) are increasingly employed to assess human information processing during exposure to multimedia signals. In the quality engineering domain, previous research has promoted the utility of the P300 event-related brain potential (ERP) component for indicating variation in quality perception. The present study provides a starting point to test whether the P300 and its two subcomponents, P3a and P3b, are truly reflective of changes in the perceived quality of transmitted speech signals given the presence of other, quality-independent changes in acoustic stimulation. Read More

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http://dx.doi.org/10.1088/1741-2552/ab1673DOI Listing

Visuotactile synchrony of stimulation-induced sensation and natural somatosensation.

J Neural Eng 2019 Apr 2. Epub 2019 Apr 2.

APT Center, Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio, UNITED STATES.

<i>Objective</i>: Previous studies suggest that somatosensory feedback has the potential to improve the functional performance of prostheses, reduce phantom pain, and enhance embodiment of sensory-enabled prosthetic devices. To maximize such benefits for amputees, the temporal properties of the sensory feedback must resemble those of natural somatosensation in an intact limb. <i>Approach</i>: To better understand temporal perception of artificial sensation, we characterized the perception of visuotactile synchrony for tactile perception restored via peripheral nerve stimulation. Read More

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http://dx.doi.org/10.1088/1741-2552/ab154cDOI Listing
April 2019
1 Read

Toward optical coherence tomography angiography-based biomarkers to assess the safety of peripheral nerve electrostimulation.

J Neural Eng 2019 Mar 27. Epub 2019 Mar 27.

Division of Biomedical Physics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland, UNITED STATES.

Objective: Peripheral nerves serve as a link between the central nervous system and its targets. Altering peripheral nerve activity through targeted electrical stimulation is being investigated as a therapy for modulating end organ function. To support rapid advancement in the field, novel approaches to predict and prevent nerve injury resulting from the electrical stimulation must be developed to overcome the limitations of traditional histological methods. Read More

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http://dx.doi.org/10.1088/1741-2552/ab1405DOI Listing

Latent common source extraction via generalized canonical correlation framework for frequency recognition in SSVEP based brain-computer interfaces.

J Neural Eng 2019 Mar 27. Epub 2019 Mar 27.

Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, Tamil Nadu, INDIA.

Objective: This study introduces and evaluates a novel target identification method, Latent common source extraction (LCSE), that uses subject-specific training data for the enhancement of steady-state visual evoked potential (SSVEP) detection.

Approach: LCSE seeks to construct a common latent representation of the SSVEP signal subspace that is stable across multiple trials of electroencephalographic (EEG) data. The spatial filter thus obtained improves the signal to noise ratio (SNR) of the SSVEP components by removing nuisance signals that are irrelevant to the generalized signal representation learnt from the given data. Read More

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http://dx.doi.org/10.1088/1741-2552/ab13d1DOI Listing

Thermal block of action potentials is primarily due to voltage-dependent potassium currents: A modeling study.

J Neural Eng 2019 Mar 25. Epub 2019 Mar 25.

Department of Biology, Case Western Reserve University, DeGrace Hall, 304, Case Western Reserve University, 2080 Adelbert Road, Cleveland, OH 44106 - 7080, USA, Cleveland, Ohio, UNITED STATES.

Objective: Thermal block of action potential conduction using infrared lasers is a new modality for manipulating neural activity. It could be used for analysis of the nervous system and for therapeutic applications. We sought to understand the mechanisms of thermal block. Read More

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http://dx.doi.org/10.1088/1741-2552/ab131bDOI Listing

Detection of brain stimuli using Ramanujan periodicity transforms.

J Neural Eng 2019 Mar 21. Epub 2019 Mar 21.

Electrical and Computer Engineering, University of Central Florida College of Engineering and Computer Science, Orlando, Florida, UNITED STATES.

Objective: The ability to efficiently match the frequency of the brain's response to repetitive visual stimuli in real time is the basis for reliable SSVEP-based Brain-Computer-Interfacing (BCI).

Approach: The detection of different stimuli is posed as a composite hypothesis test, where SSVEPs are assumed to admit a sparse representation in a Ramanujan Periodicity Transform (RPT) dictionary. For the binary case, we develop and analyze the performance of an RPT detector based on a derived generalized likelihood ratio test. Read More

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http://dx.doi.org/10.1088/1741-2552/ab123aDOI Listing

Three dimensional innervation zone imaging in spastic muscles of stroke survivors.

J Neural Eng 2019 Mar 14. Epub 2019 Mar 14.

Department of Biomedical Engineering, University of Houston, Room 2027, 3605 Cullen Boulevard, Houston, TX 77204-5060, USA, Houston, 77204, UNITED STATES.

Objective-Outcome of botulinum toxin (BTX) therapy of post-stroke spasticity relies largely on accuracy of BTX injection to the proximity of innervation zones (IZs). Recently developed three-dimensional IZ imaging (3DIZI) is the only technique currently available to provide 3D distributions of IZs in vivo, yet its performance has not been validated under pathological conditions. Approach-The performance of 3DIZI was evaluated in the spastic biceps brachii muscles of four chronic stroke subjects. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0fe1DOI Listing
March 2019
4 Reads

VITA-an everyday virtual reality setup for prosthetics and upper-limb rehabilitation.

J Neural Eng 2019 Apr;16(2):026039

Institute of Robotics and Mechatronics, German Aerospace Center (DLR), 82234 Oberpfaffenhofen, Germany.

Objective: Currently, there are some 95 000 people in Europe suffering from upper-limb impairment. Rehabilitation should be undertaken right after the impairment occurs and should be regularly performed thereafter. Moreover, the rehabilitation process should be tailored specifically to both patient and impairment. Read More

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http://dx.doi.org/10.1088/1741-2552/aaf35fDOI Listing
April 2019
2 Reads

Developing a personalized closed-loop controller of medically-induced coma in a rodent model.

J Neural Eng 2019 Mar 11. Epub 2019 Mar 11.

Electrical Engineering, University of Southern California Viterbi School of Engineering, Los Angeles, California, 90089, UNITED STATES.

Objective: Personalized automatic control of medically-induced coma, a critical multi-day therapy in the intensive care unit, could greatly benefit clinical care and further provide a novel scientific tool for investigating how the brain response to anesthetic infusion rate changes during therapy. Personalized control would require real-time tracking of inter- and intra-subject variabilities in the brain response to anesthetic infusion rate while simultaneously delivering the therapy, which has not been achieved. Current control systems for medically-induced coma require a separate offline model fitting experiment to deal with inter-subject variabilities, which would lead to therapy interruption. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0ea4DOI Listing
March 2019
5 Reads

Regression convolutional neural network for improved simultaneous EMG control.

J Neural Eng 2019 Mar 8;16(3):036015. Epub 2019 Mar 8.

Department of Biomedical Engineering, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Objective: Deep learning models can learn representations of data that extract useful information in order to perform prediction without feature engineering. In this paper, an electromyography (EMG) control scheme with a regression convolutional neural network (CNN) is proposed as a substitute of conventional regression models that use purposefully designed features.

Approach: The usability of the regression CNN model is validated for the first time, using an online Fitts' law style test with both individual and simultaneous wrist motions. Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/ab0e2e
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http://dx.doi.org/10.1088/1741-2552/ab0e2eDOI Listing
March 2019
2 Reads

A probabilistic recurrent neural network for decoding hind limb kinematics from multi-segment recordings of the dorsal horn neurons.

J Neural Eng 2019 Mar 8. Epub 2019 Mar 8.

Biomedical Engineering, Iran University of Science & Technology, Hengam Street, Narmak, Tehran 16844, Iran, Tehran, IRAN, ISLAMIC REPUBLIC OF.

Objective: Providing accurate and robust estimates of limb kinematics from recorded neural activities is prominent in closed-loop control of functional electrical stimulation (FES). A major issue in providing accurate decoding the limb kinematics is the decoding model. The primary goal of this study is to develop a decoding approach to model the dynamic interactions of neural systems for accurate decoding. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0e51DOI Listing
March 2019
4 Reads

EEG representation using multi-instance framework on the manifold of symmetric positive definite matrices.

J Neural Eng 2019 Mar 7;16(3):036016. Epub 2019 Mar 7.

Computer Engineering and Information Technology Department, Amirkabir University of Technology, Hafez Ave., Tehran, Iran.

Objective: The generalization and robustness of an electroencephalogram (EEG)-based system are crucial requirements in actual practices.

Approach: To reach these goals, we propose a new EEG representation that provides a more realistic view of brain functionality by applying multi-instance (MI) framework to consider the non-stationarity of the EEG signal. In this representation, the non-stationarity of EEG is considered by describing the signal as a bag of relevant and irrelevant concepts. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0dadDOI Listing
March 2019
1 Read

Offline and online myoelectric pattern recognition analysis and real-time control of a robotic hand after spinal cord injury.

J Neural Eng 2019 Mar 5;16(3):036018. Epub 2019 Mar 5.

Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center, Houston, TX, United States of America. TIRR Memorial Hermann Research Center, Houston, TX, United States of America.

Objective: The objective of this study was to investigate the feasibility of applying myoelectric pattern recognition for controlling a robotic hand in individuals with spinal cord injury (SCI).

Approach: Surface electromyogram (sEMG) signals of six hand motion patterns were recorded from 12 subjects with SCI. Online and offline classification performance of two classifiers (Gaussian Naive Bayes classifier, GNB, and support vector machine, SVM) were investigated. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0cf0DOI Listing

EEG decoding of the target speaker in a cocktail party scenario: considerations regarding dynamic switching of talker location.

J Neural Eng 2019 Mar 5;16(3):036017. Epub 2019 Mar 5.

School of Engineering, Trinity College Dublin, University of Dublin, Dublin, Ireland. Trinity Centre for Bioengineering, Trinity College Dublin, Dublin, Ireland.

Objective: It has been shown that attentional selection in a simple dichotic listening paradigm can be decoded offline by reconstructing the stimulus envelope from single-trial neural response data. Here, we test the efficacy of this approach in an environment with non-stationary talkers. We then look beyond the envelope reconstructions themselves and consider whether incorporating the decoder values-which reflect the weightings applied to the multichannel EEG data at different time lags and scalp locations when reconstructing the stimulus envelope-can improve decoding performance. Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/ab0cf1
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http://dx.doi.org/10.1088/1741-2552/ab0cf1DOI Listing
March 2019
5 Reads

Speech synthesis from ECoG using densely connected 3D convolutional neural networks.

J Neural Eng 2019 Mar 4;16(3):036019. Epub 2019 Mar 4.

Cognitive Systems Lab, University of Bremen, Bremen, Germany.

Objective: Direct synthesis of speech from neural signals could provide a fast and natural way of communication to people with neurological diseases. Invasively-measured brain activity (electrocorticography; ECoG) supplies the necessary temporal and spatial resolution to decode fast and complex processes such as speech production. A number of impressive advances in speech decoding using neural signals have been achieved in recent years, but the complex dynamics are still not fully understood. Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/ab0c59
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http://dx.doi.org/10.1088/1741-2552/ab0c59DOI Listing
March 2019
7 Reads

Reliability of motor and sensory neural decoding by threshold crossings for intracortical brain-machine interface.

J Neural Eng 2019 Mar 1;16(3):036011. Epub 2019 Mar 1.

Department of Neural Engineering and Biological Interdisciplinary Studies, Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, 27 Taiping Rd, Beijing 100850, People's Republic of China.

Objective: For intracortical neurophysiological studies, spike sorting is an important procedure to isolate single units for analyzing specific functions. However, whether spike sorting is necessary or not for neural decoding applications is controversial. Several studies showed that using threshold crossings (TC) instead of spike sorting could also achieve a similar satisfactory performance. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0bfbDOI Listing
March 2019
1 Read

Low-intensity ultrasound suppresses low-Mg-induced epileptiform discharges in juvenile mouse hippocampal slices.

J Neural Eng 2019 Feb 28;16(3):036006. Epub 2019 Feb 28.

School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China.

Objective: It has been shown that low-intensity ultrasound (LIUS) can suppress seizures in some laboratory studies. However, the mechanism of the suppression effect of LIUS remains unclear. The goal of this study is to investigate the modulation effects of focused LIUS on epileptiform discharges in mouse hippocampal slices as well as the underlying mechanism. Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/ab0b9a
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http://dx.doi.org/10.1088/1741-2552/ab0b9aDOI Listing
February 2019
5 Reads

Improved in vitro electrophysiology using 3D-structured microelectrode arrays with a micro-mushrooms islets architecture capable of promoting topotaxis.

J Neural Eng 2019 Feb 28;16(3):036012. Epub 2019 Feb 28.

INEB-Instituto de Engenharia Biomédica, Universidade do Porto, R. Alfredo Allen, 4200-135 Porto, Portugal. i3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, R. Alfredo Allen, 4200-135 Porto, Portugal. Instituto de Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, R. Jorge de Viterbo Ferreira, 4050-313 Porto, Portugal.

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http://dx.doi.org/10.1088/1741-2552/ab0b86DOI Listing
February 2019
2 Reads

EEG-fTCD hybrid brain-computer interface using template matching and wavelet decomposition.

J Neural Eng 2019 Feb 28;16(3):036014. Epub 2019 Feb 28.

Objective: We aim at developing a hybrid brain-computer interface that utilizes electroencephalography (EEG) and functional transcranial Doppler (fTCD). In this hybrid BCI, EEG and fTCD are used simultaneously to measure electrical brain activity and cerebral blood velocity respectively in response to flickering mental rotation (MR) and word generation (WG) tasks. In this paper, we improve both the accuracy and information transfer rate (ITR) of this novel hybrid brain computer interface (BCI) we designed in our previous work. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0b7fDOI Listing
February 2019
1 Read

Scoring upper-extremity motor function from EEG with artificial neural networks: a preliminary study.

J Neural Eng 2019 Feb 28;16(3):036013. Epub 2019 Feb 28.

Menrva Research Group, Schools of Mechatronic Systems Engineering and Engineering Science, Simon Fraser University, Metro Vancouver, BC, Canada.

Objective: Motor function of chronic stroke survivors is generally accessed using clinical motor assessments. These motor assessments are partially subjective and require prior training for the examiners. Additionally, those motor function assessments require the health professionals to be present in person. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0b82DOI Listing
February 2019
1 Read

Focal activation of neuronal circuits induced by microstimulation in the visual cortex.

J Neural Eng 2019 Feb 28;16(3):036007. Epub 2019 Feb 28.

Division of Electrical, Electronic, and Information Engineering, Graduate School of Engineering, Osaka University, 2-1 Yamada-oka, Suita, Osaka 565-0871, Japan.

Objective: Microstimulation to the cortical tissue applied with penetrating electrodes delivers current that spreads concentrically around the electrode tip and is known to evoke focal visual sensations, i.e. phosphenes. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0b80DOI Listing
February 2019
1 Read

Deep learning for electroencephalogram (EEG) classification tasks: a review.

J Neural Eng 2019 Feb 26;16(3):031001. Epub 2019 Feb 26.

Objective: Electroencephalography (EEG) analysis has been an important tool in neuroscience with applications in neuroscience, neural engineering (e.g. Brain-computer interfaces, BCI's), and even commercial applications. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0ab5DOI Listing
February 2019
32 Reads

Group-level and functional-region analysis of electric-field shape during cerebellar transcranial direct current stimulation with different electrode montages.

J Neural Eng 2019 Feb 26;16(3):036001. Epub 2019 Feb 26.

Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya, Aichi 466-8555, Japan.

Objective: Cerebellar transcranial direct current stimulation (ctDCS) is a neuromodulation scheme that delivers a small current to the cerebellum. In this work, we computationally investigate the distributions and strength of the stimulation dosage during ctDCS with the aim of determining the targeted cerebellar regions of a group of subjects with different electrode montages.

Approach: We used a new inter-individual registration method that permitted the projection of computed electric fields (EFs) from individual realistic head models (n  =  18) to standard cerebellar template for the first time. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0ac5DOI Listing
February 2019

Effect of anesthesia on motor responses evoked by spinal neural prostheses during intraoperative procedures.

J Neural Eng 2019 Feb 21;16(3):036003. Epub 2019 Feb 21.

Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada. Sensory Motor Adaptive Rehabilitative Technology (SMART) Network, University of Alberta, Edmonton, AB, Canada.

Objective: The overall goal of this study was to investigate the effects of various anesthetic protocols on the intraoperative responses to intraspinal microstimulation (ISMS). ISMS is a neuroprosthetic approach that targets the motor networks in the ventral horns of the spinal cord to restore function after spinal cord injury. In preclinical studies, ISMS in the lumbosacral enlargement produced standing and walking by activating networks controlling the hindlimb muscles. Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/ab0938
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http://dx.doi.org/10.1088/1741-2552/ab0938DOI Listing
February 2019
3 Reads

Early seizure detection for closed loop direct neurostimulation devices in epilepsy.

J Neural Eng 2019 Feb 21. Epub 2019 Feb 21.

Epilepsy Center, Universitaetsklinikum Freiburg, Breisacher Str 64, Freiburg, 79106, GERMANY.

Current treatment concepts for epilepsy are based on a continuous drug delivery or electrical stimulation to prevent the occurrence of seizures, exposing the brain and body to mostly unneeded risk of adverse effects. To address the infrequent occurrence and short duration of epileptic seizures, intelligent implantable closed-loop devices are needed which are based on a refined analysis of ongoing brain activity with highly specific and fast detection algorithms to allow for timely, ictal interventions. Since the development and FDA approval of a first closed loop neurostimulation device relying on simple threshold-based approaches, machine learning approaches became widely available, probably outperformed in the near future by deep convolutional neural networks, which already showed to be extremely successful in pattern recognition in images and partly in signal analysis. Read More

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http://dx.doi.org/10.1088/1741-2552/ab094aDOI Listing
February 2019
1 Read

Cathodic-leading pulses are more effective than anodic-leading pulses in intracortical microstimulation of the auditory cortex.

J Neural Eng 2019 Feb 21;16(3):036002. Epub 2019 Feb 21.

Department of Experimental Otology, Institute of AudioNeuroTechnology (VIANNA), Hannover Medical School, Stadtfelddamm 34, 30625 Hannover, Germany. Cluster of Excellence 'Hearing4all', Hannover, Germany.

Objective: Intracortical microstimulation (ICMS) is widely used in neuroscientific research. Earlier work from our lab showed the possibility to combine ICMS with neuronal recordings on the same shank of multi-electrode arrays and consequently inside the same cortical column in vivo. The standard stimulus pulse shape for ICMS is a symmetric, biphasic current pulse. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0944DOI Listing
February 2019
2 Reads

A deep learning approach for real-time detection of sleep spindles.

J Neural Eng 2019 Feb 21;16(3):036004. Epub 2019 Feb 21.

Department of Psychiatry, School of Medicine, New York University, New York, NY 10016, United States of America.

Objective: Sleep spindles have been implicated in memory consolidation and synaptic plasticity during NREM sleep. Detection accuracy and latency in automatic spindle detection are critical for real-time applications.

Approach: Here we propose a novel deep learning strategy (SpindleNet) to detect sleep spindles based on a single EEG channel. Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/ab0933
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http://dx.doi.org/10.1088/1741-2552/ab0933DOI Listing
February 2019
8 Reads

System based on subject-specific bands to recognize pedaling motor imagery: Towards a BCI for lower-limb rehabilitation.

J Neural Eng 2019 Feb 20. Epub 2019 Feb 20.

Postgraduate Program in Electrical Engineering, Universidade Federal do Espirito Santo, Vitoria, ES, BRAZIL.

Objective: The aim of this study is to propose a recognition system of pedaling motor imagery for lower-limb rehabilitation, which uses unsupervised methods to improve the feature extraction, and consequently the class discrimination of EEG patterns. Approach: After applying a spectrogram based on short-time Fourier transform (SSTFT), both sparseness constraints and total power are used on the time-frequency representation to automatically locate the subject-specific bands that pack the highest power during pedaling motor imagery. The output frequency bands are employed in the recognition system to automatically adjust the cut-off frequency of a low-pass filter (Butterworth, 2nd order). Read More

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http://iopscience.iop.org/article/10.1088/1741-2552/ab08c8
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http://dx.doi.org/10.1088/1741-2552/ab08c8DOI Listing
February 2019
2 Reads

Low-intensity pulsed ultrasound modulates multi-frequency band phase synchronization between LFPs and EMG in mice.

J Neural Eng 2019 Apr 19;16(2):026036. Epub 2019 Feb 19.

Institute of Electric Engineering, Yanshan University, Qinhuangdao, Hebei 066004, People's Republic of China.

Objective: Low-intensity pulsed ultrasound stimulation (LIPUS) targeted to the mouse motor cortex can simultaneously induce local field potentials (LFPs) and electromyogram (EMG) responses. However, the functional coupling relationship between LFP and EMG signals has not been elucidated to date. This study aimed to investigate the phase synchronization between LFP and EMG signals induced by LIPUS over the mouse motor cortex. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0879DOI Listing
April 2019
3 Reads

EEG can predict speech intelligibility.

J Neural Eng 2019 Feb 18;16(3):036008. Epub 2019 Feb 18.

Biomedical Engineering, City College of New York, New York City, NY, United States of America.

Objective: Speech signals have a remarkable ability to entrain brain activity to the rapid fluctuations of speech sounds. For instance, one can readily measure a correlation of the sound amplitude with the evoked responses of the electroencephalogram (EEG), and the strength of this correlation is indicative of whether the listener is attending to the speech. In this study we asked whether this stimulus-response correlation is also predictive of speech intelligibility. Read More

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http://dx.doi.org/10.1088/1741-2552/ab07feDOI Listing
February 2019
2 Reads

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

J Neural Eng 2019 Feb 12;16(3):036005. Epub 2019 Feb 12.

Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, United States of America.

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
10 Reads

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

J Neural Eng 2019 Apr 12;16(2):026037. Epub 2019 Feb 12.

Institute for Biomedical and Neural Engineering, Reykjavık University, Reykjavık, 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: Proprioceptic vibratory stimulation of calf muscles at 85 Hz was performed to evoke postural perturbation in open-eye (OE) and closed-eye (CE) experimental trials, with pseudorandom binary stimulation phases divided into four segments of 16 stimuli. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0678DOI Listing
April 2019
5 Reads

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

J Neural Eng 2019 Apr 8;16(2):026034. Epub 2019 Feb 8.

The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, 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
April 2019
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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
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A thin-film multichannel electrode for muscle recording and stimulation in neuroprosthetics applications.

J Neural Eng 2019 Apr 5;16(2):026035. Epub 2019 Feb 5.

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

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 three 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
April 2019
2 Reads

Dynamics of motor cortical activity during naturalistic feeding behavior.

J Neural Eng 2019 Apr 5;16(2):026038. Epub 2019 Feb 5.

Department of Psychiatry, Department of Neuroscience & Physiology, New York University School of Medicine, New York, NY 10016, United States of America. Department of Biomedical Engineering, Tsinghua University, Beijing, People's Republic of China.

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
April 2019
9 Reads

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

J Neural Eng 2019 Apr 31;16(2):026031. Epub 2019 Jan 31.

Instituto de Investigación Sanitaria, Hospital de la Princesa, Madrid, España.

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://stacks.iop.org/1741-2552/16/i=2/a=026031?key=crossref
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http://dx.doi.org/10.1088/1741-2552/ab039fDOI Listing
April 2019
3 Reads

How does the presence of neural probes affect extracellular potentials?

J Neural Eng 2019 Apr 31;16(2):026030. Epub 2019 Jan 31.

Center for Integrative Neuroplasticity (CINPLA), Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway. Department of Bioengineering, University of California San Diego, San Diego, CA, United States of America.

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

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

J Neural Eng 2019 Apr 30;16(2):026032. Epub 2019 Jan 30.

School of Information Engineering, Wuhan University of Technology, Wuhan 430070, People's Republic of China.

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

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

J Neural Eng 2019 Apr 28;16(2):026025. Epub 2019 Jan 28.

Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC 3800, Australia. Department of Physiology, Monash University, Clayton, VIC 3800, 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
April 2019
2 Reads

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

J Neural Eng 2019 Apr 23;16(2):026033. Epub 2019 Jan 23.

Department of Biomedical Science and Engineering (BMSE), Institute of Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Republic of Korea.

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 (MGHMM) to decompose the sensor-space stochastic multi-subject event-related potential (ERP) into quasi-stable EEG microstates. Read More

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http://dx.doi.org/10.1088/1741-2552/ab0169DOI Listing
April 2019
6 Reads