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Journal of Neural Engineering

Kyle P Lillis, Kevin J Staley
For over a century, epileptic seizures have been characterized as a state of pathological, hypersynchronous brain activity. Anti-epileptic therapies have been developed largely based on the dogma that the altered brain rhythms result from an overabundance of glutamatergic activity or insufficient GABAergic inhibition. The most effective drugs in use today act to globally decrease excitation, increase inhibition, or decrease all activity. Unfortunately, such broad alterations to brain activity often lead to impactful side effects such as mood disordersdrowsiness, cognitive impairment, and sleep disruption...
March 14, 2018: Journal of Neural Engineering
Martin Lamos, Radek Marecek, Tomáš Slavíček, Michal Mikl, Ivan Rektor, Jiri Jan
Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during EEG data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity.
 Approach. The blind decomposition of EEG spectrogram by Parallel Factor Analysis has been shown to be a useful technique for uncovering patterns of neural activity...
March 14, 2018: Journal of Neural Engineering
Kensuke Sekihara, Yoshiaki Adachi, Hiroshi K Kubota, Chang Cai, Srikantan S Nagarajan
Magnetoencephalography (MEG)
 has a well-recognized weakness at detecting deeper brain activities. This paper proposes a novel algorithm for selective detection of deep sources by suppressing interference signals from superficial sources in magnetoencephalographic (MEG) measurements. 
 Approach: The proposed algorithm combines the beamspace preprocessing method with the dual signal space projection (DSSP) interference suppression method. A prerequisite of the proposed algorithm is prior knowledge of the location of the deep sources...
March 12, 2018: Journal of Neural Engineering
Zachariah J Sperry, Kyounghwan Na, Saman S Parizi, Hillel J Chiel, John Seymour, Euisik Yoon, Tim M Bruns
The dorsal root ganglia (DRG) are promising nerve structures for sensory neural interfaces because they provide centralized access to primary afferent cell bodies and spinal reflex circuitry. In order to harness this potential, new electrode technologies are needed which take advantage of the unique properties of DRG, specifically the high density of neural cell bodies at the dorsal surface. Here we report initial <i>in vivo</i> results from the development of a flexible non-penetrating polyimide electrode array interfacing with the surface of ganglia...
March 9, 2018: Journal of Neural Engineering
Steven T Walston, Robert H Chow, James D Weiland
This in vitro investigation examines the response of retinal bipolar cells to extracellular electrical stimulation. 
 Approach: In vitro investigations characterizing the response of retinal neurons to electrical stimulation have primarily focused on retinal ganglion cells because they are the output neurons of the retina and their superficial position in the retina makes them readily accessible to in vitro recording techniques. Thus, the majority of information regarding the response of inner retinal neurons has been inferred from ganglion cell activity...
March 7, 2018: Journal of Neural Engineering
Johannes Erhardt, Erwin Fuhrer, Oliver G Gruschke, Jochen Leupold, Matthias C Wapler, Jurgen Hennig, Thomas Stieglitz, Jan G Korvink
Patients suffering from neuronal degenerative diseases are increasingly being equipped with neural implants to treat symptoms or restore functions and increase their quality of life. Magnetic resonance imaging (MRI) would be the modality of choice for diagnosis and compulsory post-operative monitoring of such patients. However, interactions between the MR environment and implants pose severe health risks to the patient. Nevertheless, neural implant recipients regularly underwent MRI examinations, and adverse events were reported rarely...
March 7, 2018: Journal of Neural Engineering
Keum-Shik Hong, Nida Aziz, Usman Ghafoor
During the last few decades, substantial scientific and technological efforts have been focused on the development of neuroprostheses. The major emphasis has been on techniques for connecting the human nervous system with a robotic prosthesis via natural-feeling interfaces. The peripheral nerves provide access to highly processed and segregated neural command signals from the brain that can in principle be used to determine user intent and control muscles. If these signals could be used, they might allow near-natural and intuitive control of prosthetic limbs with multiple degrees of freedom...
March 2, 2018: Journal of Neural Engineering
James Zhang, Thanh Nguyen, Steven Cogill, Asim Bhatti, Lingkun Luo, Samuel Yang, Saeid Nahavandi
The extracellular action potentials recorded on an electrode result from the collective simultaneous electrophysiological activity of an unknown number of neurons. Identifying and assigning these action potentials to their firing neurons, "spike sorting", is an indispensable step in studying the function and the response of an individual or ensemble of neurons to certain stimuli. With the task of neural spike sorting, the determination of the number of clusters (neurons) is arguably the most difficult and the most challenging part due to the existence of background noise and the overlap and interactions among neurons in the neighbouring regions...
March 2, 2018: Journal of Neural Engineering
Akito Kosugi, Mitsuaki Takemi, Banty Tia, Elisa Castagnola, Alberto Ansaldo, Kenta Sato, Friedemann Awiszus, Kazuhiko Seki, Davide Ricci, Luciano Fadiga, Atsushi Iriki, Junichi Ushiba
Motor map has been widely used as an indicator of motor skills and learning, cortical injury, plasticity, and functional recovery. Cortical stimulation mapping using epidural electrodes is recently adopted for animal studies. However, several technical limitations still remain. Test-retest reliability of epidural cortical stimulation (ECS) mapping has not been examined in detail. Many previous studies defined evoked movements and motor thresholds by visual inspection, and thus, lacked quantitative measurements...
March 1, 2018: Journal of Neural Engineering
Fabien Lotte, Laurent Bougrain, Andrzej Cichocki, Maureen Clerc, Marco Congedo, Alain Rakotomamonjy, Florian Yger

 Most current Electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) are based on machine learning algorithms. There is a large diversity of classifier types that are used in this field, as described in our 2007 review paper. Now, approximately 10 years after this review publication, many new algorithms have been developed and tested to classify EEG signals in BCIs. The time is therefore ripe for an updated review of EEG classification algorithms for BCIs.
 We surveyed the BCI and machine learning literature from 2007 to 2017 to identify the new classification approaches that have been investigated to design BCIs...
February 28, 2018: Journal of Neural Engineering
Behraz Farrokhi, Abbas Erfanian
OBJECTIVE: The primary concern of this study is to develop a probabilistic regression method that would improve the decoding of the hand movement trajectories from epidural ECoG as well as from subdural ECoG signals. APPROACH: The model is characterized by the conditional expectation of the hand position given the ECoG signals. The conditional expectation of the hand position is then modeled by a linear combination of the conditional probability density functions defined for each segment of the movement...
February 27, 2018: Journal of Neural Engineering
Meng-Chen Lo, Shuwu Wang, Sagar Singh, Vinod B Damodaran, Ijaz Ahmed, Kevin Coffey, David Barker, Kshitij Saste, Karanvir Kals, Hilton M Kaplan, Joachim Kohn, David I Shreiber, Jeffrey D Zahn
OBJECTIVE: Despite the feasibility of short-term neural recordings using implantable microelectrodes, attaining reliable, chronic recordings remains a challenge. Most neural recording devices suffer from a long-term tissue response, including gliosis, at the device-tissue interface. It was hypothesized that smaller, more flexible intracortical probes would limit gliosis by providing a better mechanical match with surrounding tissue. APPROACH: This paper describes the in vivo evaluation of flexible parylene microprobes designed to improve the interface with the adjacent neural tissue to limit gliosis and thereby allow for improved recording longevity...
February 27, 2018: Journal of Neural Engineering
Thomas C Spencer, James B Fallon, Mohit N Shivdasani
Current steering techniques have shown promise in retinal prostheses as a way to increase the number of distinct percepts elicitable without increasing the number of implanted electrodes. Previously, it has been shown that 'virtual' electrodes can be created between simultaneously stimulated electrode pairs, producing unique cortical response patterns. This study investigated whether virtual electrodes could be created using two-dimensional current steering, and whether these virtual electrodes can produce cortical responses with predictable spatial characteristics...
February 23, 2018: Journal of Neural Engineering
Sreekanth Kura, Hongyu Xie, Buyin Fu, Cenk Ayata, David A Boas, Sava Sakadzic
OBJECTIVE: Resting state functional connectivity (RSFC) allows the study of functional organization in normal and diseased brain by measuring the spontaneous brain activity generated under resting conditions. Intrinsic optical signal imaging (IOSI) based on multiple illumination wavelengths has been used successfully to compute RSFC maps in animal studies. The IOSI setup complexity would be greatly reduced if only a single wavelength can be used to obtain comparable RSFC maps. APPROACH: We used anesthetized mice and performed various comparisons between the RSFC maps based on single wavelength as well as oxy-, deoxy- and total hemoglobin concentration changes...
February 16, 2018: Journal of Neural Engineering
A Kabbara, H Eid, W El Falou, M Khalil, F Wendling, M Hassan
OBJECTIVE: Emerging evidence shows that cognitive deficits in Alzheimer's disease (AD) are associated with disruptions in brain functional connectivity. Thus, the identification of alterations in AD functional networks has become a topic of increasing interest. However, to what extent AD induces disruption of the balance of local and global information processing in the human brain remains elusive. The main objective of this study is to explore the dynamic topological changes of AD networks in terms of brain network segregation and integration...
February 16, 2018: Journal of Neural Engineering
Antonio Maria Chiarelli, Pierpaolo Croce, Arcangelo Merla, Filippo Zappasodi
OBJECTIVE: Brain-Computer Interface (BCI) refers to procedures that
 link the central nervous system to a device. BCI was historically performed using
 Electroencephalography (EEG). In the last years, encouraging results were obtained
 by combining EEG with other neuroimaging technologies, such as functional Near
 Infrared Spectroscopy (fNIRS). A crucial step of BCI is brain state classication
 from recorded signal features. Deep Articial Neural Networks (DNNs) recently
 reached unprecedented complex classication outcomes...
February 15, 2018: Journal of Neural Engineering
Ian Daly, Caroline Blanchard, Nicholas P Holmes
OBJECTIVE: Brain-computer interfaces (BCIs) based on motor control have been suggested as tools for stroke rehabilitation. Some initial successes have been achieved with this approach, however the mechanism by which they work is not yet fully understood. One possible part of this mechanism is a, previously suggested, relationship between the strength of the event-related desynchronization (ERD), a neural correlate of motor imagination and execution, and corticospinal excitability. Additionally, a key component of BCIs used in neurorehabilitation is the provision of visual feedback to positively reinforce attempts at motor control...
February 14, 2018: Journal of Neural Engineering
Jonathan A N Fisher, Iryna Gumenchuk

 The use of transcranial, low intensity focused ultrasound (FUS) is an emerging neuromodulation technology that shows promise for both therapeutic and research applications. Among many, one of the most exciting applications is the use of FUS to rehabilitate or augment human sensory capabilities. While there is compelling empirical evidence demonstrating this capability, basic questions regarding the spatiotemporal extent of the modulatory effects remain. Our objective was to assess the basic, yet often overlooked hypothesis that FUS in fact alters sensory-evoked neural activity within the region of the cerebral cortex at the beam's focus...
February 13, 2018: Journal of Neural Engineering
Brad Joseph Raos, Cather M Simpson, Colin S Doyle, Alan F Murray, Scott Graham, Charles P Unsworth
Recent literature suggests that astrocytes form organized functional networks and communicate through transient changes in cytosolic Ca2+. Traditional techniques to investigate network activity, such as pharmacological blocking or genetic knockout, are difficult to restrict to individual cells. The objective of this work is to develop cell-patterning techniques to physically manipulate astrocytic interactions to enable the study of Ca2+ in astrocytic networks. Approach. We investigate how an in vitro cell-patterning platform that utilizes geometric patterns of parylene-C on SiO2 can be used to physically isolate single astrocytes and small astrocytic networks...
February 9, 2018: Journal of Neural Engineering
Francesc Miralles
Objetive. MUNIX is a technique based on surface electromyogram (sEMG) that is gaining acceptance as a method to monitoring motor neuron loss because is reliable and produces less discomfort than other electrodiagnostic techniques aimed to the same purpose. MUNIX assumes that the relationship between the area of sEMG obtained at increasing levels of muscle activation and the values of a variable called "Ideal case motor unit count" (ICMUC), defined as the product of the ratio between area and power of the M-wave by that of the sEMG, is described by a decreasing power function...
February 9, 2018: Journal of Neural Engineering
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