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Journal of Neural Engineering

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https://www.readbyqxmd.com/read/28786397/integrated-trimodal-ssep-experimental-setup-for-visual-auditory-and-tactile-stimulation
#1
Rafal Kus, Tomasz Spustek, Magdalena Zieleniewska, Anna Duszyk, Piotr Rogowski, Piotr Suffczynski
Objective Steady-state evoked potentials (SSEPs), the brain responses to repetitive stimulation are commonly used in both clinical practice and scientific research. Particular brain mechanisms underlying SSEPs in different modalities (i.e. visual, auditory and tactile) are very complex and still not completely understood. Each response has distinct resonant frequencies and exhibits a particular brain topography. Moreover, the topography can be frequency-dependent, as in case of auditory potentials. However, to study each modality separately and also to investigate multisensory interactions through multimodal experiments, a proper experimental setup appears to be of critical importance...
August 8, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28777075/numerical-evaluation-of-the-skull-for-human-neuromodulation-with-transcranial-focused-ultrasound
#2
Jerel K Mueller, Leo Ai, Priya Bansal, Wynn Legon
OBJECTIVE: Transcranial focused ultrasound is an emerging field for human non-invasive neuromodulation, but its dosing in humans is difficult to know due to the skull. The objective of the present study was to establish modeling methods based on medical images to assess skull differences between individuals on the wave propagation of ultrasound. APPROACH: Computational models of transcranial focused ultrasound were constructed using CT and MR scans to solve for intracranial pressure...
August 4, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28776506/neural-decoding-of-attentional-selection-in-multi-speaker-environments-without-access-to-clean-sources
#3
James O'Sullivan, Zhuo Chen, Jose Herrero, Guy M McKhann, Sameer A Sheth, Ashesh D Mehta, Nima Mesgarani
OBJECTIVE: People who suffer from hearing impairments can find it difficult to follow a conversation in a multi-speaker environment. Current hearing aids can suppress background noise; however, there is little that can be done to help a user attend to a single conversation amongst many without knowing which speaker the user is attending to. Cognitively controlled hearing aids that use auditory attention decoding (AAD) methods are the next step in offering help. Translating the successes in AAD research to real-world applications poses a number of challenges, including the lack of access to the clean sound sources in the environment with which to compare with the neural signals...
August 4, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28776505/effects-of-cathodal-trans-spinal-direct-current-stimulation-on-lower-urinary-tract-function-in-normal-and-spinal-cord-injury-mice-with-overactive-bladder
#4
Zaghloul Ahmed
OBJECTIVE: Lower urinary tract (LUT) dysfunction is a monumental problem affecting quality of life following neurotrauma, such as spinal cord injury (SCI). Proper function of the bladder and its associated structures depends on coordinated activity of the neuronal circuitry in the spinal cord and brain. Disconnection between the spinal and brain centers controlling the LUT causes fundamental changes in the mechanisms involved in the micturition and storage reflexes. We investigated the effects of cathodal trans-spinal direct current stimulation (c-tsDCS) of the lumbosacral spine on bladder and external urinary sphincter (EUS) functions...
August 4, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28776500/invariance-and-variability-in-interaction-error-related-potentials-and-their-consequences-for-classification
#5
Mohammad Abu-Alqumsan, Christoph Kapeller, Christoph Hinterm├╝ller, Christoph Guger, Angelika Peer
OBJECTIVE: This paper discusses the invariance and variability in interaction error-related potentials (ErrPs), where a special focus is laid upon the factors of (1) the human mental processing required to assess interface actions (2) time (3) subjects. APPROACH: Three different experiments were designed as to vary primarily with respect to the mental processes that are necessary to assess whether an interface error has occurred or not. The three experiments were carried out with 11 subjects in a repeated-measures experimental design...
August 4, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28747582/an-improved-genetic-algorithm-for-designing-optimal-temporal-patterns-of-neural-stimulation
#6
Isaac Russell Cassar, Nathan David Titus, Warren M Grill
Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach: We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation...
July 27, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28745303/extracellular-ph-monitoring-for-use-in-closed-loop-vagus-nerve-stimulation
#7
Simon C Cork, Amir Eftekhar, Khalid B Mirza, James V Gardiner, Stephen R Bloom, Christofer Toumazou
OBJECTIVE: Vagal nerve stimulation (VNS) has shown potential benefits for obesity treatment; however current devices lack physiological feedback, which limit their efficacy. Changes in extracellular pH (pH<sub>e</sub>) have shown to be correlated with neural activity, but have traditionally been measured with glass microelectrodes, which limit their in vivo applicability. APPROACH: Iridium oxide has previously been shown to be sensitive to fluctuations in pH and is biocompatible...
July 26, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28745300/on-robust-parameter-estimation-in-brain-computer-interfacing
#8
Wojciech Samek, Shinichi Nakajima, Motoaki Kawanabe, Klaus-Robert Mueller
The reliable estimation of parameters such as mean or covariance matrix from noisy and high-dimensional observations is a prerequisite for successful application of signal processing and machine learning algorithms in Brain-Computer Interfacing (BCI). This challenging task becomes significantly more difficult if the data set contains outliers, e.g., due to subject movements, eye blinks or loose electrodes, as they may heavily bias the estimation and the subsequent statistical analysis. Although various robust estimators have been developed to tackle the outlier problem, they ignore important structural information in the data and thus may not be optimal...
July 26, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28745299/inferring-imagined-speech-using-eeg-signals-a-new-approach-using-riemannian-manifold-features
#9
Chuong H Nguyen, Georgios Karavas, Panagiotis Artemiadis
OBJECTIVE: In this paper, we investigate the suitability of imagined speech for Brain-Computer Interface applications (BCI). APPROACH: A novel method based on covariance matrix descriptors, which lie in Riemannian manifold, and the Relevance Vector Machines classifier is proposed. The method is applied on ElectroEncephaloGraphic (EEG) signals and tested in multiple subjects. MAIN RESULTS: The method is shown to outperform other approaches in the field with respect to accuracy and robustness...
July 26, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28741593/electro-cutaneous-stimulation-on-the-palm-elicits-referred-sensations-on-intact-but-not-on-amputated-digits
#10
Marco D'Alonzo, Leonard Frederik Engels, Marco Controzzi, Christian Cipriani
Objective Grasping and manipulation control critically depends on tactile feedback. Without this feedback, the ability for fine control of a prosthesis is limited in upper limb amputees. Early studies have shown that non-invasive electro-cutaneous stimulation (ES) can induce referred sensations that are spread to a wider and/or more distant area, with respect to the electrodes. Building on this, we sought to exploit this effect to provide somatotopically matched sensory feedback to people with partial hand (digital) amputations...
July 25, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28730995/decoding-human-mental-states-by-whole-head-eeg-fnirs-during-category-fluency-task-performance
#11
Ahmet Omurtag, Haleh Aghajani, Hasan Onur Keles
Concurrent scalp electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), which we refer to as EEG+fNIRS, promises greater accuracy than the individual modalities while remaining nearly as convenient as EEG. We sought to quantify the hybrid system's ability to decode mental states and compare it with its unimodal components. Approach. We recorded from healthy volunteers taking the category fluency test and applied machine learning techniques to the data. Main results...
July 21, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28722685/neural-control-of-finger-movement-via-intracortical-brain-machine-interface
#12
Zachary T Irwin, Karen E Schroeder, Philip P Vu, Autumn J Bullard, Derek M Tat, Chrono S Nu, Alex Vaskov, Samuel R Nason, David E Thompson, Nicole Bentley, Parag G Patil, Cynthia A Chestek
OBJECTIVE: Intracortical brain-machine interfaces (BMIs) are a promising source of prosthesis control signals for individuals with severe motor disabilities. Previous BMI studies have primarily focused on predicting and controlling whole-arm movements; precise control of hand kinematics, however, has not been fully demonstrated. Here, we investigate the continuous decoding of precise finger movements in rhesus macaques. APPROACH: In order to elicit precise and repeatable finger movements, we have developed a novel behavioral task paradigm which requires the subject to acquire virtual fingertip position targets...
July 19, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28718781/latent-variable-method-for-automatic-adaptation-to-background-states-in-motor-imagery-bci
#13
Nikolay Dagaev, Ksenia Volkova, Alexei Ossadtchi
<i>Objective</i>. Brain-computer interface (BCI) systems are known to be vulnerable to variabilities in background states of a user. Usually, no detailed information on these states is available even during the training stage. Thus there is a need in a method which is capable of taking background states into account in an unsupervised way. <i>Approach</i>. We propose a latent variable method that is based on a probabilistic model with a discrete latent variable. In order to estimate the model's parameters, we suggest to use the expectation maximization (EM) algorithm...
July 18, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28718779/a-review-and-experimental-study-on-application-of-classifiers-and-evolutionary-algorithms-in-eeg-based-brain-machine-interface-systems
#14
Farajollah Tahernezhad-Javazm, Vahid Azimirad, Maryam Shoaran
OBJECTIVE: Considering the importance and the near future development of noninvasive Brain-Machine Interface (BMI) systems, this paper presents a comprehensive theoretical-experimental survey on the classification and evolutionary methods for BMI-based systems in which EEG signals are used. APPROACH: The paper is divided into two main parts. In the first part a wide range of different types of the base and combinatorial classifiers including boosting and bagging classifiers and also evolutionary algorithms are reviewed and investigated...
July 18, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28718773/mouse-epileptic-seizure-detection-with-multiple-eeg-features-and-simple-thresholding-technique
#15
Quang M Tieng, Ashwin Anbazhagan, Min Chen, David Charles Reutens
Epilepsy is a common neurological disorder characterized by recurrent, unprovoked seizures. The search for new treatments for seizures and epilepsy relies upon studies in animal models of epilepsy. To capture data on seizures, many applications require prolonged electroencephalography (EEG) with recordings that generate voluminous data. The desire for efficient evaluation of these recordings motivates the development of automated seizure detection algorithms. Approach: A new seizure detection method is proposed, based on multiple features and a simple thresholding technique...
July 18, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28707628/brainframe-a-node-level-heterogeneous-accelerator-platform-for-neuron-simulations
#16
Georgios Smaragdos, Georgios Chatzikonstantis, Rahul Kukreja, Harry Sidiropoulos, Dimitrios Rodopoulos, Ioannis Sourdis, Zaid Al-Ars, Christoforos Kachris, Dimitrios Soudris, Chris de Zeeuw, Christos Strydis
OBJECTIVE: The advent of High-Performance Computing (HPC) in recent years has led to its increasing use in brain study through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though modern HPC platforms can often deal with such challenges, the vast diversity of the modeling field does not permit for a homogeneous acceleration platform to effectively address the complete array of modeling requirements...
July 14, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28704206/an-autonomous-robot-inspired-by-insect-neurophysiology-pursues-moving-features-in-natural-environments
#17
Zahra M Bagheri, Benjamin S Cazzolato, Steven Grainger, David C O'Carroll, Steven D Wiederman
OBJECTIVE: Many computer vision and robotic applications require the implementation of robust and efficient target-tracking algorithms on a moving platform. However, deployment of a real-time system is challenging, even with the computational power of modern hardware. Lightweight and low-powered flying insects, such as dragonflies, track prey or conspecifics within cluttered natural environments, illustrating an efficient biological solution to the target-tracking problem. APPROACH: We used our recent recordings from 'small target motion detector' neurons in the dragonfly brain to inspire the development of a closed-loop target detection and tracking algorithm...
July 13, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28696340/brain-actuated-gait-trainer-with-visual-and-proprioceptive-feedback
#18
Dong Liu, Weihai Chen, Kyuhwa Lee, Ricardo Chavarriaga, Mohamed Bouri, Zhongcai Pei, Jose Del R Millan
OBJECTIVE: Brain-machine interfaces (BMIs) have been proposed in closed-loop applications for neuromodulation and neurorehabilitation. This study describes the impact of different feedback modalities on the performance of an EEG-based BMI that decodes motor imagery (MI) of leg flexion and extension. APPROACH: We executed experiments in a lower-limb gait trainer (the legoPress) where nine able-bodied subjects participated in three consecutive sessions based on a crossover design...
July 11, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28695839/rapid-prototyping-of-flexible-intrafascicular-electrode-arrays-by-picosecond-laser-structuring
#19
Matthias Mueller, Natalia de la Oliva, Jaume Del Valle, Ignacio Delgado Martinez, Xavier Navarro, Thomas Stieglitz
Interfacing the peripheral nervous system can be performed with a large variety of electrode arrays. However, stimulating and recording a nerve while having a reasonable amount of channels limits the number of available systems. Translational research towards human clinical trial requires device safety and biocompatibility but would benefit from design flexibility in the development process to individualize probes. Approach. We selected established medical grade implant materials like precious metals and parylene C to develop a rapid prototyping process for novel intrafascicular electrode arrays using a picosecond laser structuring...
July 11, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28691694/context-dependent-adaptation-improves-robustness-of-myoelectric-control-for-upper-limb-prostheses
#20
Gauravkumar K Patel, Janne Mathias Hahne, Claudio Castellini, Dario Farina, Strahinja Dosen
OBJECTIVE: Dexterous upper-limb prostheses are available today to restore grasping, but an effective and reliable feed-forward control is still missing. The aim of this work was to improve the robustness and reliability of myoelectric control by using context information from sensors embedded within the prosthesis. APPROACH: We developed a context-driven myoelectric control scheme (cxMYO) that incorporates the inference of context information from proprioception (inertial measurement unit) and exteroception (force and grip aperture) sensors to modulate the outputs of myoelectric control...
July 10, 2017: Journal of Neural Engineering
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