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International Journal of Neural Systems

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https://www.readbyqxmd.com/read/27776439/introduction
#1
Levin Kuhlmann, David B Grayden, Mark J Cook
No abstract text is available yet for this article.
October 24, 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27873553/real-time-control-of-an-exoskeleton-hand-robot-with-myoelectric-pattern-recognition
#2
Zhiyuan Lu, Xiang Chen, Xu Zhang, Kay-Yu Tong, Ping Zhou
Robot-assisted training provides an effective approach to neurological injury rehabilitation. To meet the challenge of hand rehabilitation after neurological injuries, this study presents an advanced myoelectric pattern recognition scheme for real-time intention-driven control of a hand exoskeleton. The developed scheme detects and recognizes user's intention of six different hand motions using four channels of surface electromyography (EMG) signals acquired from the forearm and hand muscles, and then drives the exoskeleton to assist the user accomplish the intended motion...
October 6, 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27873552/correlated-eeg-signals-simulation-based-on-artificial-neural-networks
#3
Nikola M Tomasevic, Aleksandar M Neskovic, Natasa J Neskovic
In recent years, simulation of the human electroencephalogram (EEG) data found its important role in medical domain and neuropsychology. In this paper, a novel approach to simulation of two cross-correlated EEG signals is proposed. The proposed method is based on the principles of artificial neural networks (ANN). Contrary to the existing EEG data simulators, the ANN-based approach was leveraged solely on the experimentally acquired EEG data. More precisely, measured EEG data were utilized to optimize the simulator which consisted of two ANN models (each model responsible for generation of one EEG sequence)...
September 30, 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27873554/a-realistic-seizure-prediction-study-based-on-multiclass-svm
#4
Bruno Direito, César A Teixeira, Francisco Sales, Miguel Castelo-Branco, António Dourado
A patient-specific algorithm, for epileptic seizure prediction, based on multiclass support-vector machines (SVM) and using multi-channel high-dimensional feature sets, is presented. The feature sets, combined with multiclass classification and post-processing schemes aim at the generation of alarms and reduced influence of false positives. This study considers 216 patients from the European Epilepsy Database, and includes 185 patients with scalp EEG recordings and 31 with intracranial data. The strategy was tested over a total of 16,729...
September 23, 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27873551/on-the-methodological-implications-of-extracting-muscle-synergies-from-human-locomotion
#5
Alessandro Santuz, Antonis Ekizos, Lars Janshen, Vasilios Baltzopoulos, Adamantios Arampatzis
We investigated the influence of three different high-pass (HP) and low-pass (LP) filtering conditions and a Gaussian (GNMF) and inverse-Gaussian (IGNMF) non-negative matrix factorization algorithm on the extraction of muscle synergies from myoelectric signals during human walking and running. To evaluate the effects of signal recording and processing on the outcomes, we analyzed the intraday and interday computation reliability. Results show that the IGNMF achieved a significantly higher reconstruction quality and on average needs one less synergy to sufficiently reconstruct the original signals compared to the GNMF...
September 23, 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27832712/visibility-graph-from-adaptive-optimal-kernel-time-frequency-representation-for-classification-of-epileptiform-eeg
#6
Zhong-Ke Gao, Qing Cai, Yu-Xuan Yang, Na Dong, Shan-Shan Zhang
Detecting epileptic seizure from EEG signals constitutes a challenging problem of significant importance. Combining adaptive optimal kernel time-frequency representation and visibility graph, we develop a novel method for detecting epileptic seizure from EEG signals. We construct complex networks from EEG signals recorded from healthy subjects and epilepsy patients. Then we employ clustering coefficient, clustering coefficient entropy and average degree to characterize the topological structure of the networks generated from different brain states...
September 13, 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27712456/emergence-of-narrowband-high-frequency-oscillations-from-asynchronous-uncoupled-neural-firing
#7
Stephen V Gliske, William C Stacey, Eugene Lim, Katherine A Holman, Christian G Fink
Previous experimental studies have demonstrated the emergence of narrowband local field potential oscillations during epileptic seizures in which the underlying neural activity appears to be completely asynchronous. We derive a mathematical model explaining how this counterintuitive phenomenon may occur, showing that a population of independent, completely asynchronous neurons may produce narrowband oscillations if each neuron fires quasi-periodically, without requiring any intrinsic oscillatory cells or feedback inhibition...
February 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27701932/introduction
#8
Sharon Shmuely, Roland D Thijs, Stiliyan N Kalitzin, Josemir W Sander
No abstract text is available yet for this article.
December 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27701931/author-index-volume-26-2016
#9
(no author information available yet)
No abstract text is available yet for this article.
December 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27633895/seizures-start-without-common-signatures-of-critical-transition
#10
Piotr Milanowski, Piotr Suffczynski
Complex dynamical systems may exhibit sudden autonomous changes from one state to another. Such changes that occur rapidly in comparison to the regular dynamics have been termed critical transitions. Examples of such phenomena can be found in many complex systems: changes in climate and ocean circulation, changes in wildlife populations, financial crashes, as well as in medical conditions like asthma attacks and depression. It has been recognized that critical transitions, even if they arise in completely different contexts and situations, share several common attributes and also generic early-warning signals that indicate that a critical transition is approaching...
December 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27464853/extracellular-potassium-and-seizures-excitation-inhibition-and-the-role-of-ih
#11
Lihua Wang, Suzie Dufour, Taufik A Valiante, Peter L Carlen
Seizure activity leads to increases in extracellular potassium concentration ([K[Formula: see text]]o), which can result in changes in neuronal passive and active membrane properties as well as in population activities. In this study, we examined how extracellular potassium modulates seizure activities using an acute 4-AP induced seizure model in the neocortex, both in vivo and in vitro. Moderately elevated [K[Formula: see text]]o up to 9[Formula: see text]mM prolonged seizure durations and shortened interictal intervals as well as depolarized the neuronal resting membrane potential (RMP)...
December 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27440467/nonlinear-connectivity-in-the-human-stretch-reflex-assessed-by-cross-frequency-phase-coupling
#12
Yuan Yang, Teodoro Solis-Escalante, Jun Yao, Frans C T van der Helm, Julius P A Dewald, Alfred C Schouten
Communication between neuronal populations is facilitated by synchronization of their oscillatory activity. Although nonlinearity has been observed in the sensorimotor system, its nonlinear connectivity has not been widely investigated yet. This study investigates nonlinear connectivity during the human stretch reflex based on neuronal synchronization. Healthy participants generated isotonic wrist flexion while receiving a periodic mechanical perturbation to the wrist. Using a novel cross-frequency phase coupling metric, we estimate directional nonlinear connectivity, including time delay, from the perturbation to brain and to muscle, as well as from brain to muscle...
December 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27478060/ensembles-of-deep-learning-architectures-for-the-early-diagnosis-of-the-alzheimer-s-disease
#13
Andrés Ortiz, Jorge Munilla, Juan M Górriz, Javier Ramírez
Computer Aided Diagnosis (CAD) constitutes an important tool for the early diagnosis of Alzheimer's Disease (AD), which, in turn, allows the application of treatments that can be simpler and more likely to be effective. This paper explores the construction of classification methods based on deep learning architectures applied on brain regions defined by the Automated Anatomical Labeling (AAL). Gray Matter (GM) images from each brain area have been split into 3D patches according to the regions defined by the AAL atlas and these patches are used to train different deep belief networks...
November 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27478059/introduction
#14
José Manuel Ferrández, Diego Andina, Eduardo Fernández
No abstract text is available yet for this article.
November 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27377663/asynchronous-detection-of-trials-onset-from-raw-eeg-signals
#15
M A Lopez-Gordo, M D Grima Murcia, Pablo Padilla, F Pelayo, E Fernandez
Clinical processing of event-related potentials (ERPs) requires a precise synchrony between the stimulation and the acquisition units that are guaranteed by means of a physical link between them. This precise synchrony is needed since temporal misalignments during trial averaging can lead to high deviations of peak times, thus causing error in diagnosis or inefficiency in classification in brain-computer interfaces (BCIs). Out of the laboratory, mobile EEG systems and BCI headsets are not provided with the physical link, thus being inadequate for acquisition of ERPs...
November 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27354192/a-computational-framework-for-realistic-retina-modeling
#16
Pablo Martínez-Cañada, Christian Morillas, Begoña Pino, Eduardo Ros, Francisco Pelayo
Computational simulations of the retina have led to valuable insights about the biophysics of its neuronal activity and processing principles. A great number of retina models have been proposed to reproduce the behavioral diversity of the different visual processing pathways. While many of these models share common computational stages, previous efforts have been more focused on fitting specific retina functions rather than generalizing them beyond a particular model. Here, we define a set of computational retinal microcircuits that can be used as basic building blocks for the modeling of different retina mechanisms...
November 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27354191/eeg-based-detection-of-starting-and-stopping-during-gait-cycle
#17
Enrique Hortal, Andrés Úbeda, Eduardo Iáñez, José M Azorín, Eduardo Fernández
Walking is for humans an essential task in our daily life. However, there is a huge (and growing) number of people who have this ability diminished or are not able to walk due to motor disabilities. In this paper, a system to detect the start and the stop of the gait through electroencephalographic signals has been developed. The system has been designed in order to be applied in the future to control a lower limb exoskeleton to help stroke or spinal cord injured patients during the gait. The brain-machine interface (BMI) training has been optimized through a preliminary analysis using the brain information recorded during the experiments performed by three healthy subjects...
November 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27354190/reconstruction-of-neural-activity-from-eeg-data-using-dynamic-spatiotemporal-constraints
#18
E Giraldo-Suarez, J D Martinez-Vargas, G Castellanos-Dominguez
We present a novel iterative regularized algorithm (IRA) for neural activity reconstruction that explicitly includes spatiotemporal constraints, performing a trade-off between space and time resolutions. For improving the spatial accuracy provided by electroencephalography (EEG) signals, we explore a basis set that describes the smooth, localized areas of potentially active brain regions. In turn, we enhance the time resolution by adding the Markovian assumption for brain activity estimation at each time period...
November 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27354189/a-structural-parametrization-of-the-brain-using-hidden-markov-models-based-paths-in-alzheimer-s-disease
#19
Francisco J Martinez-Murcia, Juan M Górriz, Javier Ramírez, Andres Ortiz
The usage of biomedical imaging in the diagnosis of dementia is increasingly widespread. A number of works explore the possibilities of computational techniques and algorithms in what is called computed aided diagnosis. Our work presents an automatic parametrization of the brain structure by means of a path generation algorithm based on hidden Markov models (HMMs). The path is traced using information of intensity and spatial orientation in each node, adapting to the structure of the brain. Each path is itself a useful way to characterize the distribution of the tissue inside the magnetic resonance imaging (MRI) image by, for example, extracting the intensity levels at each node or generating statistical information of the tissue distribution...
November 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27354187/automatic-tuning-of-a-retina-model-for-a-cortical-visual-neuroprosthesis-using-a-multi-objective-optimization-genetic-algorithm
#20
Antonio Martínez-Álvarez, Rubén Crespo-Cano, Ariadna Díaz-Tahoces, Sergio Cuenca-Asensi, José Manuel Ferrández Vicente, Eduardo Fernández
The retina is a very complex neural structure, which contains many different types of neurons interconnected with great precision, enabling sophisticated conditioning and coding of the visual information before it is passed via the optic nerve to higher visual centers. The encoding of visual information is one of the basic questions in visual and computational neuroscience and is also of seminal importance in the field of visual prostheses. In this framework, it is essential to have artificial retina systems to be able to function in a way as similar as possible to the biological retinas...
November 2016: International Journal of Neural Systems
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