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PubMed Journal Database | Journal of neural engineering RSS

18:08 EDT 25th June 2019 | BioPortfolio

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Showing PubMed Articles 1–25 of 182 from Journal of neural engineering

Real-time isometric finger extension force estimation based on motor unit discharge information.

The goal of this study was to perform real-time estimation of isometric finger extension force using discharge information of motor units (MUs). 
 Approach: A real-time electromyogram (EMG) decomposition method based on the fast independent component analysis (FastICA) algorithm was developed to extract MU discharge events from high-density (HD) EMG recordings. The decomposition was first performed offline during an initialization period, and the obtained separation matrix was then applied to new da...

Characterization and real-time removal of motion artifacts from EEG signals.

Accurate implementation of real-time non-invasive Brain-Machine / Computer Interfaces (BMI / BCI) requires handling physiological and nonphysiological artifacts associated with the measurement modalities. For example, scalp electroencephalographic (EEG) measurements are often considered prone to excessive motion artifacts and other types of artifacts that contaminate the EEG recordings. Although the magnitude of such artifacts heavily depends on the task and the setup, complete minimization or isolation of ...

Effects of stimulation frequency and stimulation waveform on steady state visual evoked potentials using computer monitor.

Visual stimulator takes a vital part in brain-computer interfaces (BCIs) based on steady-state visual evoked potential (SSVEP). The properties of visual stimulation such as frequency, color, and waveform will influence SSVEP-based BCI performance to some extent. Recently, the computer monitor serves as a visual stimulator that is widespread in SSVEP-based BCIs because of its great flexibility in generating visual stimuli. However, stimulation properties based on computer monitor has received fairly little a...

Direct modelling of gradient artifacts for EEG-fMRI denoising and motion tracking.

Simultaneous electroencephalography and functional magnetic resonance imaging recording (EEG-fMRI) has been widely used in neuroscientific and clinical research. The artifacts in the recorded EEG resulting from rapidly switching magnetic field gradients are usually corrected by average-artifact subtraction (AAS) due to their repetitive nature. But the performance of AAS is often disrupted by altered artifact waveforms across epochs, notably due to head motion. 
 Approach. Here, a method is proposed ...

A microfabricated, 3D-sharpened silicon shuttle for insertion of flexible electrode arrays through dura mater into brain.

Electrode arrays for chronic implantation in the brain are a critical technology in both neuroscience and medicine. Recently, flexible, thin-film polymer electrode arrays have shown promise in facilitating stable, single-unit recordings spanning months in rats. While array flexibility enhances integration with neural tissue, it also requires removal of the dura mater, the tough membrane surrounding the brain, and temporary bracing to penetrate the brain parenchyma. Durotomy increases brain swelling, vascula...

Effect of electrode-electrolyte spatial mismatch on transcranial direct current stimulation: A finite element modeling study.

Despite the encouraging pilot results of transcranial direct current stimulation (tDCS) revealing its effectiveness in neuromodulation, there are also studies reporting inconsistent outcomes. Apart from previously studied factors, such as the differences in head model structures, anodal displacements, electrode shape and size, and connector position, the hypothesis that the inevitable spatial mismatch between the electrolyte buffer and electrode might shape current flow in the cerebral cortex was tested in ...

Higher Order Spectral Analysis of scalp EEG activity reveals non-linear behavior during rhythmic visual stimulation.

Flickering visual stimulation is known to evoke rhythmic oscillations in the Electroencephalographic (EEG) activity, called Steady-State Visually Evoked Potentials (SSVEP). The presence of harmonic components in the EEG signals during SSVEP suggests the non-linearity of the visual-system response to rhythmic stimulation, but the nature of this behavior has not been deeply understood. The aim of this study is the quantitative evaluation and characterization of this non-linear phenomenon and its interference ...

Guided growth with aligned neurites in adult spiral ganglion neurons cultured in-vitro on silicon micro-pillar substrates.

Assessment of the relationship between the topographical organization of silicon micro-pillar surfaces (MPS) on guidance and neural alignment of adult spiral ganglion neurons (SGN) and use of the otosurgical approach as an alternative for the extraction and isolation of SGNs from adult guinea pigs.
 Approach: SGNs from adult guinea pigs were isolated using conventional and otosurgical approach for in-vitro cell culturing on MPS of various micro-pillar widths (1-5.6 µm) and spacing (0.6-15 µm). Cel...

Accuracy of robotic coil positioning during transcranial magnetic stimulation.

Robotic positioning systems for transcranial magnetic stimulation (TMS) promise improved accuracy and stability of coil placement, but there is limited data on their performance. Investigate the usability, accuracy, and limitations of robotic coil placement with a commercial system, ANT Neuro, in a TMS study.
 Approach: 21 subjects underwent a total of 79 TMS sessions corresponding to 160 hours under robotic coil control. Coil position and orientation were monitored concurrently through an additiona...

Single-paradigm and hybrid Brain Computing Interfaces and their use by disabled patients.

Brain Computer Interfacing (BCI) has enjoyed increasing interest not only from research communities such as engineering and neuroscience but also from visionaries that predict it will change the way we will interact with technology. Since BCIs establish an alternative communication channel between the brain and the outside world, they have been hailed to provide solutions for patients suffering from severe motor- and/or communication disabilities such as fully paralyzed locked-in syndrome patients. However,...

The analytical subtraction approach for solving the forward problem in EEG.

The subtraction approach is known for being a theoretically-rigorous and accurate technique for solving the forward problem in electroencephalography by means of the finite element method. One key aspect of this approach consists of computing integrals of singular kernels over the discretised domain, usually referred to as potential integrals. Several techniques have been proposed for dealing with such integrals, all of them approximating the results at the expense of reducing the accuracy of the solution. ...

An iterative cross-subject negative-unlabeled learning algorithm for quantifying passive fatigue.

<i>Objective.</i> This paper proposes an iterative negative-unlabeled (NU) learning algorithm for cross-subject detection of passive fatigue from labelled alert (negative) and unlabeled driving EEG data. <i>Approach.</i> Unlike other studies which used manual labeling of the fatigue state, the proposed algorithm (PA) first iteratively uses 29 subjects' alert data and unlabeled driving data to identify the most fatigued block of EEG data in each subject...

Seizure tracking of epileptic EEG using a model-driven approach.

As a chronic neurological disorder, epilepsy is characterized by recurrent and unprovoked epileptic seizures which can disrupt the normal neuro-biologic, cognitive, psychological conditions of patients. Therefore, it is worthwhile to give a detailed account of how the epileptic EEG evolves during a period of seizure so that an effective control can be guided for epileptic patients in clinics.

Learning across multi-stimulus enhances target recognition methods in SSVEP-based BCIs.

<i>Objective</i>: Latest target recognition methods that are equipped with learning from subject's calibration data, represented by the extended canonical correlation analysis (eCCA) and the ensemble task-related component analysis (eTRCA), can achieve extra high performance in the steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs), however their performance deteriorate drastically if the calibration trials are insufficient. This paper develops a ...

Characterizing the fluctuations of dynamic resting-state electrophysiological functional connectivity: Reduced neuronal coupling variability in mild cognitive impairment and dementia due to Alzheimer's disease.

The characterization of brain functional connectivity is a helpful tool in the study of the neuronal substrates and mechanisms that are altered in Azheimer's Disease (AD) and mild cognitive impairment (MCI). Recently, there has been a shift towards the characterization of dynamic functional connectivity (dFC), discarding the assumption of connectivity stationarity during the resting-state. The majority of these studies have been performed with functional magnetic resonance imaging (fMRI) recordings, with on...

An exploration of BCI performance variations in people with amyotrophic lateral sclerosis using longitudinal EEG data.

Brain-computer interface (BCI) technology enables people to use direct measures of brain activity for communication and control. The National Center for Adaptive Neurotechnologies (NCAN) and Helen Hayes Hospital are studying long-term independent home use of P300-based BCIs by people with amyotrophic lateral sclerosis (ALS). This BCI use takes place without technical oversight, and users can encounter substantial variation in their day-to-day BCI performance. The purpose of this study is to identify and eva...

Rogue bioelectrical waves in the brain: the Hurst exponent as a potential measure for presurgical mapping in epilepsy.

Brain electromagnetic activity in patients with epilepsy is characterized by abnormal high-amplitude transient events (spikes) and abnormal patterns of synchronization of brain rhythms that accompany epileptic seizures. With the aim of improving methods for identifying epileptogenic sources in magnetoencephalographic (MEG) recordings of brain data, we applied methods previously used in the study of oceanic 'rogue waves' and other freak events in complex systems 
 Approach. For data from 3 patients w...

Sparse model-based estimation of functional dependence in high-dimensional field and spike multiscale networks.

Behavior is encoded across multiple scales of brain activity, from binary neuronal spikes to continuous fields including local field potentials (LFP). Multiscale models need to describe both the encoding of behavior and the conditional dependencies in simultaneously recorded spike and field signals, which form a high-dimensional multiscale network. However, learning spike-field dependencies in high-dimensional recordings is challenging due to the prohibitively large number of spike-field signal pairs, which...

Two-stage regression of high-density scalp electroencephalograms visualizes force regulation signaling during muscle contraction.

A critical feature for the maintenance of precise skeletal muscle force production by the human brain is its ability to configure motor function activity dynamically and adaptively in response to visual and somatosensory information. Existing studies have concluded that not only the sensorimotor area but also distributed cortical areas act cooperatively in the generation of motor commands for voluntary force production to the desired level. However, less attention has been paid to such physiological mechani...

A comparative evaluation of signal quality between research-grade and wireless dry-electrode mobile EEG systems.

Electroencephalography (EEG) is widely used by clinicians, scientists, engineers and other professionals worldwide, with an increasing number of low-cost, commercially-oriented EEG systems that have become available in recent years. One such system is the Cognionics Quick-20 (Cognionics Inc., San Diego, USA), which uses dry electrodes and offers the convenience of portability thanks to its built-in amplifier and wireless connection. Because of such characteristics, this system has been used in several appli...

Connectivity steered graph Fourier transform for motor imagery BCI decoding.

Graph signal processing concepts are exploited for brain activity decoding and particularly the detection and recognition of a Motor Imagery (MI) movement. A novel signal analytic technique that combines Graph Fourier Transform (GFT) with estimates of cross-frequency coupling and discriminative learning is introduced as a means to recover the subject's intention from the multichannel signal.
 Approach. Adopting a multi-view perspective, based on the popular concept of co-existing and interacting bra...

Dynamic network modeling and dimensionality reduction for human ECoG activity.

Developing dynamic network models for multisite electrocorticogram (ECoG) activity can help study neural representations and design neurotechnologies in humans given the clinical promise of ECoG. However, dynamic network models have so far largely focused on spike recordings rather than ECoG. A dynamic network model for ECoG recordings, which constitute a network, should describe their temporal dynamics while also achieving dimensionality reduction given the inherent spatial and temporal correlations.

Continuous 2-D control via state-machine triggered by endogenous sensory discrimination and a fast brain switch.

Brain computer interfacing (BCI) is a promising method to control assistive systems for patients with severe disabilities. However, only a small number of commands (2 to 3) can be discriminated from EEG signals. Recently, we have presented a novel BCI approach that combines an electrotactile menu and a brain switch, which allows the user to trigger many commands robustly and efficiently. However, the commands are timed to periodic tactile cues and this may challenge online control. In the present study, the...

Realistic vOlumetric-Approach to Simulate Transcranial Electric Stimulation -- ROAST -- a fully automated open-source pipeline.

Research in the area of transcranial electrical stimulation (TES) often relies on computational models of current flow in the brain. Models are built based on magnetic resonance images (MRI) of the human head to capture detailed individual anatomy. To simulate current flow on an individual, the subject's MRI is segmented, virtual electrodes are placed on this anatomical model, the volume is tessellated into a mesh, and a finite element model (FEM) is solved numerically to estimate the current flow. Various ...

Maximal flexibility in dynamic functional connectivity with critical dynamics revealed by fMRI data analysis and brain network modelling.

The exploration of time-varying functional connectivity (FC) through human neuroimaging techniques provides important new insights on the spatio-temporal organization of functional communication in the brain's networks and its alterations in diseased brains. However, little is known about the underlying dynamic mechanism with which such a dynamic FC is flexibly organized under the constraint of structural connections. In this work, we explore the relationship between critical dynamics and FC flexibility bas...


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