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PubMed Journal Database | Journal of neural engineering - Page: 2 RSS

12:57 EDT 22nd July 2019 | BioPortfolio

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Showing PubMed Articles 26–50 of 190 from Journal of neural engineering

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...

Computationally inexpensive enhanced growing neural gas algorithm for real-time adaptive neural spike clustering.

Real-time closed-loop neural feedback control requires the analysis of action potential traces within several milliseconds after they have been recorded from the brain. The current generation of spike clustering algorithms were mostly designed for off-line use and also require a significant amount of computational resources. A new spike clustering algorithm, termed "Enhanced Growing Neural Gas (EGNG)", was therefore developed that is computationally lightweight and memory conserved. The EGNG algorithm can a...

Biometric identification of listener identity from frequency following responses to speech.

We investigated the biometric specificity of the frequency following response (FFR), an EEG marker of early auditory processing that reflects phase-locked activity from neural ensembles in the auditory cortex and subcortex (Bidelman, 2015a, 2018; Chandrasekaran & Kraus, 2010; Coffey et al., 2017). Our objective is two-fold: demonstrate that the FFR contains information beyond stimulus properties and broad group-level markers, and to assess the practical viability of the FFR as a biometric across differe...

Retinal supplementation augments optogenetic stimulation efficacy in vivo.

Over the last two decades, optical control of neuronal activity in the central nervous system has seen rapid growth, demonstrating the utility of optogenetics as both an experimental and therapeutic tool. Conversely, applications of optogenetics in the peripheral nervous system have been relatively constrained by the challenges of temporally variable opsin expression, light penetration and immune attack of non-native opsins. Whilst opsin expression can be increased significantly through high concentration v...

Miniature electroparticle-cuff for wireless peripheral neuromodulation.

Recent developments in peripheral nerve electrodes allow the efficient and selective neuromodulation of somatic and autonomic nerves, which has proven beneficial in specific bioelectronic medical applications. However, current most clinical devices are wired and powered by implantable batteries which suffer from several limitations. We recently developed a sub-millimeter inductively powered neural stimulator (electroparticle; EP), and in this study, we report the integration of the EP onto commercial cuff e...

Chronic recording and electrochemical performance of amorphous silicon carbide-coated Utah electrode arrays implanted in rat motor cortex.

Clinical applications of implantable microelectrode arrays are currently limited by device failure due to, in part, mechanical and electrochemical failure modes. To overcome this challenge, there is significant research interest in the exploration of novel array architectures and encapsulation materials. Amorphous silicon carbide (a-SiC) is biocompatible and corrosion resistant, and has recently been employed as a coating on biomedical devices including planar microelectrode arrays. However, to date, the th...

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

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 na...

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

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.

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

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. The inhibition appears to take effect via spinal interneuronal pathways. This study e...

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

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 dif...

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

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.

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

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. These scaffold-bas...

Deep-learning for seizure forecasting in canines with epilepsy.

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-p...

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

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. In the collected EEG, noise and SSVEP are usually coupled ...

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

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 perceiv...

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

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-specif...

Visuotactile synchrony of stimulation-induced sensation and natural somatosensation.

<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 perce...


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