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Journal of Neural Engineering

Cong Zhang, Xiang Chen, Shuai Cao, Xu Zhang, Xun Chen
OBJECTIVE: TO INVESTIGATE THE ACTIVATION HETEROGENEITY OF SKELETAL MUSCLES AND REALIZE THE JOINT FORCE ESTIMATION DURING ELBOW FLEXION TASK. APPROACH: When an isometric elbow flexion task was performed, high-density surface electromyography (HD-sEMG) signals from A 8×16 GRID covering the front and inside of the upper arm and the generated joint force were recorded synchronously. HD-sEMG signals were preprocessed and then decomposed into source signals corresponding to BICEPS BRACHHI (BB) AND BRACHIALIS (BR) and their contribution vectors using FAST INDEPENDENT COMPONENT ANALYSIS (FastICA) algorithm...
July 16, 2018: Journal of Neural Engineering
Jie Luo, Wenbo Sun, Yuanyu Wu, Huihua Liu, Xiaoyun Wang, Tiebin Yan, Rong Song
OBJECTIVE: The coordination of agonist and antagonist muscles around a single joint plays an important role in daily activities. The aim of this study was to apply a myoelectric-controlled interface (MCI) with different dimensions to investigate stroke- and aging-induced deteriorations in the coordination of agonist and antagonist muscles. APPROACH: Eight stroke patients (affected sides), ten healthy late middle-aged controls and eighteen healthy young controls were enrolled to perform tracking tasks during voluntary isometric elbow flexion and extension by modulating their biceps and triceps activities with one-dimensional or two-dimensional MCI...
July 16, 2018: Journal of Neural Engineering
Mahsa Malekmohammadi, Yalda Shahriari, Nicholas AuYong, Andrew OKeeffe, Yvette Bordelon, Xiao Hu, Nader Pouratian
β hypersynchrony within the basal ganglia-thalamocortical (BGTC) network has been suggested as a hallmark of Parkinson disease (PD) pathophysiology. Subthalamic nucleus (STN)-DBS has been shown to alter cortical-subcortical synchronization. It is unclear whether this is a generalizable phenomenon of therapeutic stimulation across targets. 
 Objectives: We aimed to evaluate whether DBS of the globus pallidus internus (GPi) results in cortical-subcortical desynchronization, despite the lack of monosynaptic connections between GPi and sensorimotor cortex...
July 4, 2018: Journal of Neural Engineering
Philipp Senn, Robert K Shepherd, James B Fallon
OBJECTIVE: Cochlear implants, while providing significant benefits to recipients, remain limited due to broad neural activation. Focussed multipolar stimulation (FMP) is an advanced stimulation strategy that uses multiple current sources to produce highly focussed patterns of neural excitation in order to overcome these shortcomings. APPROACH: This report presents single-source multipolar stimulation (SSMPsSSMPS), a novel form of stimulation based on a single current source and a passive current divider...
July 3, 2018: Journal of Neural Engineering
Ricardo Bruña, Fernando Maestú, Ernesto Pereda
Despite the increase in calculation power over the last few decades, the estimation of brain connectivity is still a tedious task. The high computational cost of the algorithms escalates with the square of the number of signals evaluated, usually within the range of thousands. In this work we propose a re-formulation of a widely used algorithm that allows the estimation of whole brain connectivity in much smaller times.
 We start from the original implementation of Phase Locking Value (PLV) and re-formulated it in a highly computational efficient way...
June 28, 2018: Journal of Neural Engineering
Roberto Guarnieri, Marco Marino, Federico Barban, Marco Ganzetti, Dante Mantini
OBJECTIVE: The performance of brain computer interfaces (BCIs) based on electroencephalography (EEG) data strongly depends on the effective attenuation of artifacts that are mixed in the recordings. To address this problem, we have developed a novel online EEG artifact removal method for BCI applications, which combines blind source separation (BSS) and regression (REG) analysis. APPROACH: The BSS-REG method relies on the availability of a calibration dataset of limited duration for the initialization of a spatial filter using BSS...
June 28, 2018: Journal of Neural Engineering
James J S Norton, Jessica Mullins, Birgit E Alitz, Timothy Bretl
In this paper, we report the performance of 9-11-year-old children using a steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) and provide control data collected from adults for comparison. Children in our study achieved much higher performance (79% accuracy; average age 9.64 years old) than the only previous investigation of children using an SSVEP-based BCI (∼50% accuracy; average age 9.86 years old). Experiments were conducted in two phases, a short calibration phase and a longer experimental phase...
June 28, 2018: Journal of Neural Engineering
Anita Zátonyi, Flóra Fedor, Zsolt Borhegyi, Zoltan Fekete
Intracranial EEG (iEEG) or micro-electrocorticography (µECoG) microelectrodes offer high spatial resolution in recordings of neuronal activity from the exposed brain surface. Reliability of dielectric substrates and conductive materials of these devices are under intensive research in terms functional stability in biological environments. 
 Approach. The aim of our study is to investigate the stability of electroplated platinum recording sites on 16-channel, 8 micron thick, polyimide based, flexible µECoG arrays implanted underneath the skull of rats...
June 27, 2018: Journal of Neural Engineering
Alessio Paolo Buccino, Mikkel Elle Lepperød, Svenn-Arne Dragly, Philipp Haefliger, Marianne Fyhn, Torkel Hafting
A major goal in systems neuroscience is to determine the causal relationship between neural activity and behavior. To this end, methods that combine monitoring neural activity, behavioral tracking, and targeted manipulation of neurons in closed-loop are powerful tools. However, commercial systems that allow these types of experiments are usually expensive and rely on non-standardized data formats and proprietary software which may hinder user-modifications for specific needs. In order to promote reproducibility and data-sharing in science, transparent software and standardized data formats are an advantage...
June 27, 2018: Journal of Neural Engineering
Muhammad Kaleem, Dharmendra Gurve, Aziz Guergachi, Sridhar Krishnan
The objective of the work described in this paper is development of a computationally efficient methodology for patient-specific automatic seizure detection in long-term multi-channel EEG recordings.
 Approach: A novel patient-specific seizure detection approach based on signal-derived Empirical Mode Decomposition (EMD)-based dictionary approach is proposed. For this purpose, we use an empirical framework for EMD-based dictionary creation and learning, inspired by traditional dictionary learning methods, in which the EMD-based dictionary is learned from the multi-channel EEG data being analyzed for automatic seizure detection...
June 25, 2018: Journal of Neural Engineering
James Evan Smith, Angel V Peterchev
Sham TMS coils isolate the ancillary effects of their active counterparts, but typically induce low-strength electric fields (E-fields) in the brain, which could be biologically active. We measured the E-fields induced by two pairs of commonly-used commercial active/sham coils.
 Approach: E-field distributions of the active and sham configurations of the Magstim 70 mm AFC and MagVenture Cool-B65 A/P coils were measured over a 7-cm-radius, hemispherical grid approximating the cortical surface. Peak E-field strength was recorded over a range of pulse amplitudes...
June 22, 2018: Journal of Neural Engineering
Jasper Wouters, Fabian Kloosterman, Alexander Bertrand
The process of grouping neuronal spikes in an extracellular recording according to their neuronal sources, is generally referred to as spike sorting. Currently, the use of spike sorting is mainly limited to an offline usage, where spikes are sorted after the data acquisition has been completed. In this paper, we propose a discriminative template matching algorithm for threshold-based spike sorting on high-density extracellular data. Such threshold-based spike sorting has a low and deterministic algorithmic delay, allowing for fast online spike sorting...
June 22, 2018: Journal of Neural Engineering
Vernon Lawhern, Amelia Solon, Nicholas Waytowich, Stephen M Gordon, Chou Hung, Brent J Lance
OBJECTIVE: Brain computer interfaces (BCI) enable direct communication with a computer, using neural activity as the control signal. This neural signal is generally chosen from a variety of well-studied electroencephalogram (EEG) signals. For a given BCI paradigm, feature extractors and classifiers are tailored to the distinct characteristics of its expected EEG control signal, limiting its application to that specific signal. Convolutional Neural Networks (CNNs), which have been used in computer vision and speech recognition to perform automatic feature extraction and classification, have successfully been applied to EEG-based BCIs; however, they have mainly been applied to single BCI paradigms and thus it remains unclear how these architectures generalize to other paradigms...
June 22, 2018: Journal of Neural Engineering
Antje Kilias, Andres Canales, Ulrich P Froriep, Seongjun Park, Ulrich Egert, Polina Anikeeva
Optogenetic modulation of neural activity is a ubiquitous tool for basic investigation of brain circuits. While the majority of optogenetic paradigms rely on short light pulses to evoke synchronized activity of optically sensitized cells, many neurobiological processes are associated with slow local field potential (LFP) oscillations. Therefore, we developed a hybrid fiber probe capable of simultaneous electrophysiological recording and optical stimulation and used it to investigate the utility of sinusoidal light stimulation for evoking oscillatory neural activity in vivo across a broad frequency range...
June 20, 2018: Journal of Neural Engineering
Mackenna Hill, Estefania Rios, Shyam Kumar Sudhakar, Douglas Roossien, Ciara Maria Caldwell, Dawen Cai, Omar Ahmed, Scott Lempka, Cynthia A Chestek
OBJECTIVE: Neural recording is important for a wide variety of clinical applications. Until recently, recording from the surface of the brain, even when using micro-electrocorticography (µECoG) arrays, was not thought to enable recording from individual neurons. Recent results suggest that when the surface electrode contact size is sufficiently small, it may be possible to record single neurons from the brain's surface. In this study, we use computational techniques to investigate the ability of surface electrodes to record the activity of single neurons...
June 20, 2018: Journal of Neural Engineering
Zhenghao Guo, Xia Wu, Jianhong Liu, Li Yao, Bin Hu
OBJECTIVE: Depression is a severe mental disorder. However, the neural mechanisms underlying affective interference (difficulties in directing attention away from negative distractors) in depression patients are still not well understood. In particular, the connections between brain regions remain unclear. Using the emotional face-word Stroop task, we aimed to reveal the altered electroencephalography (EEG) functional connectivity in patients with depression, using concepts from event-related potentials (ERPs) and time series clustering...
June 20, 2018: Journal of Neural Engineering
Wadood Haq, Johannes Dietter, Sylvia Bolz, Eberhart Zrenner
OBJECTIVE: A feasibility study for a transmitter based subretinal prosthesis, generating visual responses in blind mouse retina is presented. APPROACH: Degenerated rd1 mouse retina were stimulated in subretinal configuration by local glutamate (Glu) or NMDA application via micropipettes (~1.5 μm) and thereby the outer retinal activity was recorded by calcium-imaging or the ganglion cell (GC) activity was recorded by the multi-electrode array system. The network mediated activation of GC via bipolar cells was approved by the administration of Glu receptor blockers...
June 19, 2018: Journal of Neural Engineering
Matthew Dyson, Jessica Barnes, Kianoush Nazarpour
The objective of this study was to compare the use of muscles appropriate for partial-hand prostheses with those typically used for complete hand devices and to determine whether differences in their underlying neural substrates translate to different levels of myoelectric control.
 Approach: We developed a novel abstract myoelectric decoder based on motor learning. Three muscle pairs, namely, an intrinsic and independent, an intrinsic and synergist and finally, an extrinsic and antagonist, were tested during abstract myoelectric control...
June 12, 2018: Journal of Neural Engineering
Guosheng Yi, Warren M Grill
OBJECTIVE: Deep brain stimulation (DBS) generates action potentials (APs) in presynaptic axons and fibers of passage. The APs may be antidromically propagated to invade the cell body and / or orthodromically transmitted to downstream structures, thereby affecting widespread targets distant from the electrode. Activation of presynaptic terminals also causes trans-synaptic effects, which in turn alter the excitability of the post-synaptic neurons. Our aim was to determine how synaptic inputs affect the antidromic invasion of the cell body...
June 12, 2018: Journal of Neural Engineering
Timothy Esler, Matias Maturana, Robert R Kerr, David B Grayden, Anthony N Burkitt, Hamish Meffin
Responses of retinal ganglion cells to direct electrical stimulation have been shown experimentally to be well described by linear-nonlinear models. These models rely on the simplifying assumption that retinal ganglion cell responses to stimulation with an array of electrodes are driven by a simple linear weighted sum of stimulus current amplitudes from each electrode, known as the "electrical receptive field". <i>Objective</i>. This paper aims to demonstrate the biophysical basis of the linear-nonlinear model and the electrical receptive field to facilitate the development of improved stimulation strategies for retinal implants...
June 11, 2018: Journal of Neural Engineering
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