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https://www.readbyqxmd.com/read/28821650/feedback-signal-from-motoneurons-influences-a-rhythmic-pattern-generator
#1
Horacio G Rotstein, Elisa Schneider, Lidia Szczupak
Motoneurons are not mere output units of neuronal circuits that control motor behavior, but participate in pattern generation. Research on the circuit that controls the crawling motor behavior in leeches indicated that motoneurons participate as modulators of this rhythmic motor pattern. Crawling results from successive bouts of elongation and contraction of the whole leech body. In the isolated segmental ganglia dopamine can induce a rhythmic antiphasic activity of the motoneurons that control contraction (DE-3 motoneurons) and elongation (CV motoneurons)...
August 16, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28820744/simulation-of-morphologically-structured-photo-thermal-neural-stimulation
#2
Y Weissler, N Farah, S Shoham
OBJECTIVE: Rational design of next-generation techniques for photo-thermal excitation requires the development of tools capable of modeling the effects of spatially- and temporally-dependent temperature distribution on cellular neuronal structures. APPROACH: We present a new computer simulation tool for predicting the effects of arbitrary spatiotemporally-structured photo-thermal stimulation on 3D, morphologically realistic neurons. The new simulation tool is based on interfacing two generic platforms, NEURON and MATLAB and is therefore suited for capturing different kinds of stimuli and neural models...
August 18, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28819690/conductance-based-refractory-density-approach-comparison-with-experimental-data-and-generalization-to-lognormal-distribution-of-input-current
#3
Anton V Chizhov
The conductance-based refractory density (CBRD) approach is an efficient tool for modeling interacting neuronal populations. The model describes the firing activity of a statistical ensemble of uncoupled Hodgkin-Huxley-like neurons, each receiving individual Gaussian noise and a common time-varying deterministic input. However, the approach requires experimental validation and extension to cases of distributed input signals (or input weights) among different neurons of such an ensemble. Here the CBRD model is verified by comparing with experimental data and then generalized for a lognormal (LN) distribution of the input weights...
August 17, 2017: Biological Cybernetics
https://www.readbyqxmd.com/read/28819547/continuous-force-decoding-from-deep-brain-local-field-potentials-for-brain-computer-interfacing
#4
Syed A Shah, Huiling Tan, Peter Brown
Current Brain Computer Interface (BCI) systems are limited by relying on neuronal spikes and decoding limited to kinematics only. For a BCI system to be practically useful, it should be able to decode brain information on a continuous basis with low latency. This study investigates if force can be decoded from local field potentials (LFP) recorded with deep brain electrodes located at the Subthalamic nucleus (STN) using data from 5 patients with Parkinson's disease, on a continuous basis with low latency. A Wiener-Cascade (WC) model based decoder was proposed using both time-domain and frequency-domain features...
2017: International IEEE/EMBS Conference on Neural Engineering: [proceedings]
https://www.readbyqxmd.com/read/28818579/developing-integrated-pbpk-pd-coupled-mechanistic-pathway-model-mirna-bdnf-an-approach-towards-system-toxicology
#5
Raju Prasad Sharma, Marta Schuhmacher, Vikas Kumar
Integration of a dynamic signal transduction pathway into the tissue dosimetry model is a major advancement in the area of computational toxicology. This paper illustrates the ways to incorporate the use of existing system biological model in the field of toxicology via its coupling to the Physiological based Pharmacokinetics and Pharmacodynamics (PBPK/PD) model.This expansion framework of integrated PBPK/PD coupled mechanistic system pathway model can be called as system toxicology that describes the kinetics of both -the chemicals and -biomolecules, help us to understand the dynamic and steady-state behaviors of molecular pathways under perturbed condition...
August 14, 2017: Toxicology Letters
https://www.readbyqxmd.com/read/28817580/criticality-predicts-maximum-irregularity-in-recurrent-networks-of-excitatory-nodes
#6
Yahya Karimipanah, Zhengyu Ma, Ralf Wessel
A rigorous understanding of brain dynamics and function requires a conceptual bridge between multiple levels of organization, including neural spiking and network-level population activity. Mounting evidence suggests that neural networks of cerebral cortex operate at a critical regime, which is defined as a transition point between two phases of short lasting and chaotic activity. However, despite the fact that criticality brings about certain functional advantages for information processing, its supporting evidence is still far from conclusive, as it has been mostly based on power law scaling of size and durations of cascades of activity...
2017: PloS One
https://www.readbyqxmd.com/read/28816177/electrical-stimulation-of-gut-motility-guided-by-an-in-silico-model
#7
Bradley Brigham Barth, Craig S Henriquez, Warren M Grill, Xiling Shen
OBJECTIVE: Neuromodulation of the central and peripheral nervous systems is becoming increasingly important for treating a diverse set of diseases-ranging from Parkinson's Disease and epilepsy to chronic pain. However, neuromodulation of the gastrointestinal (GI) tract has achieved relatively limited success in treating functional GI disorders, which affect a significant population, because the effects of stimulation on the enteric nervous system (ENS) and gut motility are not well understood...
August 17, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28809709/a-new-method-for-automatic-sleep-stage-classification
#8
Junming Zhang, Yan Wu
Traditionally, automatic sleep stage classification is quite a challenging task because of the difficulty in translating open-textured standards to mathematical models and the limitations of handcrafted features. In this paper, a new system for automatic sleep stage classification is presented. Compared with existing sleep stage methods, our method can capture the sleep information hidden inside electroencephalography (EEG) signals and automatically extract features from raw data. To translate open sleep stage standards into machine rules recognized by computers, a new model named fast discriminative complex-valued convolutional neural network (FDCCNN) is proposed to extract features from raw EEG data and classify sleep stages...
August 14, 2017: IEEE Transactions on Biomedical Circuits and Systems
https://www.readbyqxmd.com/read/28792931/chaotic-dynamics-in-nanoscale-nbo2-mott-memristors-for-analogue-computing
#9
Suhas Kumar, John Paul Strachan, R Stanley Williams
At present, machine learning systems use simplified neuron models that lack the rich nonlinear phenomena observed in biological systems, which display spatio-temporal cooperative dynamics. There is evidence that neurons operate in a regime called the edge of chaos that may be central to complexity, learning efficiency, adaptability and analogue (non-Boolean) computation in brains. Neural networks have exhibited enhanced computational complexity when operated at the edge of chaos, and networks of chaotic elements have been proposed for solving combinatorial or global optimization problems...
August 9, 2017: Nature
https://www.readbyqxmd.com/read/28791515/a-multiscale-fluidic-device-for-the-study-of-dendrite-mediated-cell-to-cell-communication
#10
Sean McCutcheon, Robert Majeska, Mitchell Schaffler, Maribel Vazquez
Many cell types communicate by means of dendritic extensions via a multi-tiered set of geometric and chemical cues. Until recently, mimicking the compartmentalized in vivo cellular environment of dendrite-expressing cells such as osteocytes and motor neurons in a spatially and temporally controllable manner was limited by the challenges of in vitro device fabrication at submicron scales. Utilizing the improved resolution of current fabrication technology, we have designed a multiscale device, the Macro-micro-nano system, or Mμn, composed of two distinct cell-seeding and interrogation compartments separated by a nanochannel array...
August 8, 2017: Biomedical Microdevices
https://www.readbyqxmd.com/read/28791331/temporal-processing-in-the-visual-cortex-of-the-awake-and-anesthetized-rat
#11
Ida E J Aasebø, Mikkel E Lepperød, Maria Stavrinou, Sandra Nøkkevangen, Gaute Einevoll, Torkel Hafting, Marianne Fyhn
The activity pattern and temporal dynamics within and between neuron ensembles are essential features of information processing and believed to be profoundly affected by anesthesia. Much of our general understanding of sensory information processing, including computational models aimed at mathematically simulating sensory information processing, rely on parameters derived from recordings conducted on animals under anesthesia. Due to the high variety of neuronal subtypes in the brain, population-based estimates of the impact of anesthesia may conceal unit- or ensemble-specific effects of the transition between states...
July 2017: ENeuro
https://www.readbyqxmd.com/read/28783641/spiking-neural-p-systems-with-polarizations
#12
Tingfang Wu, Andrei Paun, Zhiqiang Zhang, Linqiang Pan
Spiking neural P (SN P) systems are a class of parallel computation models inspired by neurons, where the firing condition of a neuron is described by a regular expression associated with spiking rules. However, it is NP-complete to decide whether the number of spikes is in the length set of the language associated with the regular expression. In this paper, in order to avoid using regular expressions, two major and rather natural modifications in their form and functioning are proposed: the spiking rules no longer check the number of spikes in a neuron, but, in exchange, a polarization is associated with neurons and rules, one of the three electrical charges -, 0, +...
August 1, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28782235/detection-of-phasic-dopamine-by-d1-and-d2-striatal-medium-spiny-neurons
#13
Cedric Yapo, Anu G Nair, Lorna Clement, Liliana R Castro, Jeanette Hellgren Kotaleski, Pierre Vincent
The phasic release of dopamine in the striatum determines various aspects of reward and action selection, but the dynamics of dopamine effect on intracellular signalling remains poorly understood. We used genetically-encoded FRET biosensors in striatal brain slices to quantify the effect of transient dopamine on cAMP or PKA-dependent phosphorylation level, and computational modelling to further explore the dynamics of this signalling pathway. Medium-sized spiny neurons (MSNs), which express either D1 or D2 dopamine receptors, responded to dopamine by an increase or a decrease in cAMP, respectively...
August 7, 2017: Journal of Physiology
https://www.readbyqxmd.com/read/28777957/understanding-neural-circuit-development-through-theory-and-models
#14
REVIEW
Leonidas Ma Richter, Julijana Gjorgjieva
How are neural circuits organized and tuned to achieve stable function and produce robust behavior? The organization process begins early in development and involves a diversity of mechanisms unique to this period. We summarize recent progress in theoretical neuroscience that has substantially contributed to our understanding of development at the single neuron, synaptic and network level. We go beyond classical models of topographic map formation, and focus on the generation of complex spatiotemporal activity patterns, their role in refinements of particular circuit features, and the emergence of functional computations...
August 1, 2017: Current Opinion in Neurobiology
https://www.readbyqxmd.com/read/28761426/metabolite-changes-in-the-ipsilateral-and-contralateral-cerebral-hemispheres-in-rats-with-middle-cerebral-artery-occlusion
#15
Lei Ruan, Yan Wang, Shu-Chao Chen, Tian Zhao, Qun Huang, Zi-Long Hu, Neng-Zhi Xia, Jin-Jin Liu, Wei-Jian Chen, Yong Zhang, Jing-Liang Cheng, Hong-Chang Gao, Yun-Jun Yang, Hou-Zhang Sun
Cerebral ischemia not only causes pathological changes in the ischemic areas but also induces a series of secondary changes in more distal brain regions (such as the contralateral cerebral hemisphere). The impact of supratentorial lesions, which are the most common type of lesion, on the contralateral cerebellum has been studied in patients by positron emission tomography, single photon emission computed tomography, magnetic resonance imaging and diffusion tensor imaging. In the present study, we investigated metabolite changes in the contralateral cerebral hemisphere after supratentorial unilateral ischemia using nuclear magnetic resonance spectroscopy-based metabonomics...
June 2017: Neural Regeneration Research
https://www.readbyqxmd.com/read/28760861/feedback-inhibition-shapes-emergent-computational-properties-of-cortical-microcircuit-motifs
#16
Zeno Jonke, Robert Legenstein, Stefan Habenschuss, Wolfgang Maass
Cortical microcircuits are very complex networks, but they are composed of a relatively small number of stereotypical motifs. Hence one strategy for throwing light on the computational function of cortical microcircuits is to analyze emergent computational properties of these stereotypical microcircuit motifs. We are addressing here the question how spike-timing dependent plasticity (STDP) shapes the computational properties of one motif that has frequently been studied experimentally: interconnected populations of pyramidal cells and parvalbumin-positive inhibitory cells in layer 2/3...
July 31, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28759581/the-combination-of-circle-topology-and-leaky-integrator-neurons-remarkably-improves-the-performance-of-echo-state-network-on-time-series-prediction
#17
Fangzheng Xue, Qian Li, Xiumin Li
Recently, echo state network (ESN) has attracted a great deal of attention due to its high accuracy and efficient learning performance. Compared with the traditional random structure and classical sigmoid units, simple circle topology and leaky integrator neurons have more advantages on reservoir computing of ESN. In this paper, we propose a new model of ESN with both circle reservoir structure and leaky integrator units. By comparing the prediction capability on Mackey-Glass chaotic time series of four ESN models: classical ESN, circle ESN, traditional leaky integrator ESN, circle leaky integrator ESN, we find that our circle leaky integrator ESN shows significantly better performance than other ESNs with roughly 2 orders of magnitude reduction of the predictive error...
2017: PloS One
https://www.readbyqxmd.com/read/28758207/the-potential-of-computer-vision-optical-backscattering-parameters-and-artificial-neural-network-modelling-in-monitoring-the-shrinkage-of-sweet-potato-ipomoea-batatas-l-during-drying
#18
Daniel I Onwude, Norhashila Hashim, Khalina Abdan, Rimfiel Janius, Guangnan Chen
BACKGROUND: Drying is a method used to preserve agricultural crops. During the drying of products with high moisture content, structural changes in shape, volume, area, density and porosity occur. This changes could affect the final quality of dried product and also the effective design of drying equipment. Therefore, this study investigated a novel approach in monitoring and predicting the shrinkage of sweet potato during drying. Drying experiments were conducted at temperatures of 50-70 °C and samples thicknesses of 2 - 6 mm...
July 30, 2017: Journal of the Science of Food and Agriculture
https://www.readbyqxmd.com/read/28756163/information-reduction-in-a-reverberatory-neuronal-network-through-convergence-to-complex-oscillatory-firing-patterns
#19
A Vidybida, O Shchur
Dynamics of a reverberating neural net is studied by means of computer simulation. The net, which is composed of 9 leaky integrate-and-fire (LIF) neurons arranged in a square lattice, is fully connected with interneuronal communication delay proportional to the corresponding distance. The network is initially stimulated with different stimuli and then goes freely. For each stimulus, in the course of free evolution, activity either dies out completely or the network converges to a periodic trajectory, which may be different for different stimuli...
July 26, 2017: Bio Systems
https://www.readbyqxmd.com/read/28753456/synaptic-damage-underlies-eeg-abnormalities-in-postanoxic-encephalopathy-a-computational-study
#20
B J Ruijter, J Hofmeijer, H G E Meijer, M J A M van Putten
OBJECTIVE: In postanoxic coma, EEG patterns indicate the severity of encephalopathy and typically evolve in time. We aim to improve the understanding of pathophysiological mechanisms underlying these EEG abnormalities. METHODS: We used a mean field model comprising excitatory and inhibitory neurons, local synaptic connections, and input from thalamic afferents. Anoxic damage is modeled as aggravated short-term synaptic depression, with gradual recovery over many hours...
September 2017: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
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