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International Journal of Neural Systems

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https://www.readbyqxmd.com/read/29297264/mirror-neurons-modeled-through-spike-timing-dependent-plasticity-are-affected-by-channelopathies-associated-with-autism-spectrum-disorder
#1
Gabriela Antunes, Samuel F Faria da Silva, Fabio M Simoes de Souza
Mirror neurons fire action potentials both when the agent performs a certain behavior and watches someone performing a similar action. Here, we present an original mirror neuron model based on the spike-timing-dependent plasticity (STDP) between two morpho-electrical models of neocortical pyramidal neurons. Both neurons fired spontaneously with basal firing rate that follows a Poisson distribution, and the STDP between them was modeled by the triplet algorithm. Our simulation results demonstrated that STDP is sufficient for the rise of mirror neuron function between the pairs of neocortical neurons...
November 28, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29298521/neural-correlates-of-phrase-quadrature-perception-in-harmonic-rhythm-an-eeg-study-using-a-brain-computer-interface
#2
Alicia Fernández-Sotos, Arturo Martínez-Rodrigo, José Moncho-Bogani, José Miguel Latorre, Antonio Fernández-Caballero
For the sake of establishing the neural correlates of phrase quadrature perception in harmonic rhythm, a musical experiment has been designed to induce music-evoked stimuli related to one important aspect of harmonic rhythm, namely the phrase quadrature. Brain activity is translated to action through electroencephalography (EEG) by using a brain-computer interface. The power spectral value of each EEG channel is estimated to obtain how power variance distributes as a function of frequency. The results of processing the acquired signals are in line with previous studies that use different musical parameters to induce emotions...
November 13, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29297265/short-term-effects-of-binaural-beats-on-eeg-power-functional-connectivity-cognition-gait-and-anxiety-in-parkinson-s-disease
#3
Gerardo Gálvez, Manuel Recuero, Leonides Canuet, Francisco Del-Pozo
We applied rhythmic binaural sound to Parkinson's Disease (PD) patients to investigate its influence on several symptoms of this disease and on Electrophysiology (Electrocardiography and Electroencephalography (EEG)). We conducted a double-blind, randomized controlled study in which rhythmic binaural beats and control were administered over two randomized and counterbalanced sessions (within-subjects repeated-measures design). Patients ([Formula: see text], age [Formula: see text], stage I-III Hoehn & Yahr scale) participated in two sessions of sound stimulation for 10[Formula: see text]min separated by a minimum of 7 days...
November 13, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29297263/foreground-detection-by-competitive-learning-for-varying-input-distributions
#4
Ezequiel López-Rubio, Miguel A Molina-Cabello, Rafael Marcos Luque-Baena, Enrique Domínguez
One of the most important challenges in computer vision applications is the background modeling, especially when the background is dynamic and the input distribution might not be stationary, i.e. the distribution of the input data could change with time (e.g. changing illuminations, waving trees, water, etc.). In this work, an unsupervised learning neural network is proposed which is able to cope with progressive changes in the input distribution. It is based on a dual learning mechanism which manages the changes of the input distribution separately from the cluster detection...
November 13, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29297261/multi-step-time-series-forecasting-with-an-ensemble-of-varied-length-mixture-models
#5
Yicun Ouyang, Hujun Yin
Many real-world problems require modeling and forecasting of time series, such as weather temperature, electricity demand, stock prices and foreign exchange (FX) rates. Often, the tasks involve predicting over a long-term period, e.g. several weeks or months. Most existing time series models are inheritably for one-step prediction, that is, predicting one time point ahead. Multi-step or long-term prediction is difficult and challenging due to the lack of information and uncertainty or error accumulation. The main existing approaches, iterative and independent, either use one-step model recursively or treat the multi-step task as an independent model...
November 13, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29281922/development-of-a-ternary-near-infrared-spectroscopy-brain-computer-interface-online-classification-of-verbal-fluency-task-stroop-task-and-rest
#6
Larissa C Schudlo, Tom Chau
The majority of proposed NIRS-BCIs has considered binary classification. Studies considering high-order classification problems have yielded average accuracies that are less than favorable for practical communication. Consequently, there is a paucity of evidence supporting online classification of more than two mental states using NIRS. We developed an online ternary NIRS-BCI that supports the verbal fluency task (VFT), Stroop task and rest. The system utilized two sessions dedicated solely to classifier training...
October 26, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29092679/author-index-volume-27-2017
#7
(no author information available yet)
No abstract text is available yet for this article.
December 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/28982286/spiking-neural-p-systems-with-communication-on-request
#8
Linqiang Pan, Gheorghe Păun, Gexiang Zhang, Ferrante Neri
Spiking Neural [Formula: see text] Systems are Neural System models characterized by the fact that each neuron mimics a biological cell and the communication between neurons is based on spikes. In the Spiking Neural [Formula: see text] systems investigated so far, the application of evolution rules depends on the contents of a neuron (checked by means of a regular expression). In these [Formula: see text] systems, a specified number of spikes are consumed and a specified number of spikes are produced, and then sent to each of the neurons linked by a synapse to the evolving neuron...
December 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/28774230/dynamics-of-epileptiform-discharges-induced-by-transcranial-magnetic-stimulation-in-genetic-generalized-epilepsy
#9
Dimitris Kugiumtzis, Christos Koutlis, Alkiviadis Tsimpiris, Vasilios K Kimiskidis
OBJECTIVE: In patients with Genetic Generalized Epilepsy (GGE), transcranial magnetic stimulation (TMS) can induce epileptiform discharges (EDs) of varying duration. We hypothesized that (a) the ED duration is determined by the dynamic states of critical network nodes (brain areas) at the early post-TMS period, and (b) brain connectivity changes before, during and after the ED, as well as within the ED. METHODS: EEG recordings from two GGE patients were analyzed...
November 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29297262/tracking-the-reorganization-of-module-structure-in-time-varying-weighted-brain-functional-connectivity-networks
#10
Christoph Schmidt, Diana Piper, Britta Pester, Andreas Mierau, Herbert Witte
Identification of module structure in brain functional networks is a promising way to obtain novel insights into neural information processing, as modules correspond to delineated brain regions in which interactions are strongly increased. Tracking of network modules in time-varying brain functional networks is not yet commonly considered in neuroscience despite its potential for gaining an understanding of the time evolution of functional interaction patterns and associated changing degrees of functional segregation and integration...
October 20, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29258366/dynamic-characteristics-of-a-new-three-dimensional-linear-homeomorphic-saccade-model
#11
Wei Zhou, Xiu Zhai, Alireza Ghahari, G Alex Korentis, David Kaputa, John D Enderle
A linear homeomorphic eye movement model that produces 3D saccadic eye movements consistent with anatomical and physiological evidence is introduced in this second part of a two-paper sequence. Central to the model is the implementation of a time-optimal neural control strategy involving six linear muscle models that faithfully represent the dynamic characteristics of 3D saccades. The muscle is modeled as a parallel combination of viscosity [Formula: see text] and series elasticity [Formula: see text], connected to the parallel combination of active-state tension generator [Formula: see text], viscosity element [Formula: see text], and length tension elastic element [Formula: see text]...
October 20, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29241397/static-characteristics-of-a-new-three-dimensional-linear-homeomorphic-saccade-model
#12
Wei Zhou, Xiu Zhai, Alireza Ghahari, G Alex Korentis, David Kaputa, John D Enderle
A linear homeomorphic saccade model that produces 3D saccadic eye movements consistent with physiological and anatomical evidence is introduced. Central to the model is the implementation of a time-optimal controller with six linear muscles and pulleys that represent the saccade oculomotor plant. Each muscle is modeled as a parallel combination of viscosity [Formula: see text] and series elasticity [Formula: see text] connected to the parallel combination of active-state tension generator [Formula: see text], viscosity element [Formula: see text], and length tension elastic element [Formula: see text]...
October 20, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29129128/convergent-time-varying-regression-models-for-data-streams-tracking-concept-drift-by-the-recursive-parzen-based-generalized-regression-neural-networks
#13
Piotr Duda, Maciej Jaworski, Leszek Rutkowski
One of the greatest challenges in data mining is related to processing and analysis of massive data streams. Contrary to traditional static data mining problems, data streams require that each element is processed only once, the amount of allocated memory is constant and the models incorporate changes of investigated streams. A vast majority of available methods have been developed for data stream classification and only a few of them attempted to solve regression problems, using various heuristic approaches...
October 12, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29113518/functional-semi-blind-source-separation-identifies-primary-motor-area-without-active-motor-execution
#14
Camillo Porcaro, Carlo Cottone, Andrea Cancelli, Carlo Salustri, Franca Tecchio
High time resolution techniques are crucial for investigating the brain in action. Here, we propose a method to identify a section of the upper-limb motor area representation (FS_M1) by means of electroencephalographic (EEG) signals recorded during a completely passive condition (FS_M1bySS). We delivered a galvanic stimulation to the median nerve and we applied to EEG the semi-Blind Source Separation (s-BSS) algorithm named Functional Source Separation (FSS). In order to prove that FS_M1bySS is part of FS_M1, we also collected EEG in a motor condition, i...
September 11, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/28982281/nonlinear-semi-supervised-metric-learning-via-multiple-kernels-and-local-topology
#15
Xin Li, Yanqin Bai, Yaxin Peng, Shaoyi Du, Shihui Ying
Changing the metric on the data may change the data distribution, hence a good distance metric can promote the performance of learning algorithm. In this paper, we address the semi-supervised distance metric learning (ML) problem to obtain the best nonlinear metric for the data. First, we describe the nonlinear metric by the multiple kernel representation. By this approach, we project the data into a high dimensional space, where the data can be well represented by linear ML. Then, we reformulate the linear ML by a minimization problem on the positive definite matrix group...
September 11, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29046111/eeg-classification-with-a-sequential-decision-making-method-in-motor-imagery-bci
#16
Rong Liu, Yongxuan Wang, Geoffrey I Newman, Nitish V Thakor, Sarah Ying
To develop subject-specific classifier to recognize mental states fast and reliably is an important issue in brain-computer interfaces (BCI), particularly in practical real-time applications such as wheelchair or neuroprosthetic control. In this paper, a sequential decision-making strategy is explored in conjunction with an optimal wavelet analysis for EEG classification. The subject-specific wavelet parameters based on a grid-search method were first developed to determine evidence accumulative curve for the sequential classifier...
September 7, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29046110/image-sharpness-and-contrast-tuning-in-the-early-visual-pathway
#17
Eduardo Sánchez, Rubén Ferreiroa, Adrián Arias, Luis M Martínez
The center-surround organization of the receptive fields (RFs) of retinal ganglion cells highlights the presence of local contrast in visual stimuli. As RF of thalamic relay cells follow the same basic functional organization, it is often assumed that they contribute very little to alter the retinal output. However, in many species, thalamic relay cells largely outnumber their retinal inputs, which diverge to contact simultaneously several units at thalamic level. This gain in cell population as well as retinothalamic convergence opens the door to question how information about contrast is transformed at the thalamic stage...
September 7, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/28982282/long-synfire-chains-emerge-by-spike-timing-dependent-plasticity-modulated-by-population-activity
#18
Felix Weissenberger, Florian Meier, Johannes Lengler, Hafsteinn Einarsson, Angelika Steger
Sequences of precisely timed neuronal activity are observed in many brain areas in various species. Synfire chains are a well-established model that can explain such sequences. However, it is unknown under which conditions synfire chains can develop in initially unstructured networks by self-organization. This work shows that with spike-timing dependent plasticity (STDP), modulated by global population activity, long synfire chains emerge in sparse random networks. The learning rule fosters neurons to participate multiple times in the chain or in multiple chains...
September 7, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/28659042/announcement-the-2017-hojjat-adeli-award-for-outstanding-contributions-in-neural-systems
#19
(no author information available yet)
No abstract text is available yet for this article.
September 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/28587498/surface-eeg-transcranial-direct-current-stimulation-tdcs-closed-loop-system
#20
Jorge Leite, Leon Morales-Quezada, Sandra Carvalho, Aurore Thibaut, Deniz Doruk, Chiun-Fan Chen, Steven C Schachter, Alexander Rotenberg, Felipe Fregni
Conventional transcranial direct current stimulation (tDCS) protocols rely on applying electrical current at a fixed intensity and duration without using surrogate markers to direct the interventions. This has led to some mixed results; especially because tDCS induced effects may vary depending on the ongoing level of brain activity. Therefore, the objective of this preliminary study was to assess the feasibility of an EEG-triggered tDCS system based on EEG online analysis of its frequency bands. Six healthy volunteers were randomized to participate in a double-blind sham-controlled crossover design to receive a single session of 10[Formula: see text]min 2[Formula: see text]mA cathodal and sham tDCS...
September 2017: International Journal of Neural Systems
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