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Journal of Computational Neuroscience

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https://www.readbyqxmd.com/read/28434057/predictive-control-of-intersegmental-tarsal-movements-in-an-insect
#1
Alicia Costalago-Meruelo, David M Simpson, Sandor M Veres, Philip L Newland
In many animals intersegmental reflexes are important for postural and movement control but are still poorly undesrtood. Mathematical methods can be used to model the responses to stimulation, and thus go beyond a simple description of responses to specific inputs. Here we analyse an intersegmental reflex of the foot (tarsus) of the locust hind leg, which raises the tarsus when the tibia is flexed and depresses it when the tibia is extended. A novel method is described to measure and quantify the intersegmental responses of the tarsus to a stimulus to the femoro-tibial chordotonal organ...
April 22, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28393281/reaction-time-impairments-in-decision-making-networks-as-a-diagnostic-marker-for-traumatic-brain-injuries-and-neurological-diseases
#2
Pedro D Maia, J Nathan Kutz
The presence of diffuse Focal Axonal Swellings (FAS) is a hallmark cellular feature in many neurological diseases and traumatic brain injury. Among other things, the FAS have a significant impact on spike-train encodings that propagate through the affected neurons, leading to compromised signal processing on a neuronal network level. This work merges, for the first time, three fields of study: (i) signal processing in excitatory-inhibitory (EI) networks of neurons via population codes, (ii) decision-making theory driven by the production of evidence from stimulus, and (iii) compromised spike-train propagation through FAS...
April 10, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28389716/multirate-method-for-co-simulation-of-electrical-chemical-systems-in-multiscale-modeling
#3
Ekaterina Brocke, Mikael Djurfeldt, Upinder S Bhalla, Jeanette Hellgren Kotaleski, Michael Hanke
Multiscale modeling by means of co-simulation is a powerful tool to address many vital questions in neuroscience. It can for example be applied in the study of the process of learning and memory formation in the brain. At the same time the co-simulation technique makes it possible to take advantage of interoperability between existing tools and multi-physics models as well as distributed computing. However, the theoretical basis for multiscale modeling is not sufficiently understood. There is, for example, a need of efficient and accurate numerical methods for time integration...
April 7, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28389715/neural-field-model-of-seizure-like-activity-in-isolated-cortex
#4
X Zhao, P A Robinson
Epileptiform discharges on an isolated cortex are explored using neural field theory. A neural field model of the isolated cortex is used that consists of three neural populations, excitatory, inhibitory, and excitatory bursting. Mechanisms by which an isolated cortex gives rise to seizure-like waveforms thought to underly pathological EEG waveforms on the deafferented cortex are explored. It is shown that the model reproduces similar time series and oscillatory frequencies for paroxysmal discharges when compared with physiological recordings both during acute and chronic deafferentation states...
April 7, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28367595/ionic-currents-influencing-spontaneous-firing-and-pacemaker-frequency-in-dopamine-neurons-of-the-ventrolateral-periaqueductal-gray-and-dorsal-raphe-nucleus-vlpag-drn-a-voltage-clamp-and-computational-modelling-study
#5
Antonios G Dougalis, Gillian A C Matthews, Birgit Liss, Mark A Ungless
Dopamine (DA) neurons of the ventrolateral periaqueductal gray (vlPAG) and dorsal raphe nucleus (DRN) fire spontaneous action potentials (APs) at slow, regular patterns in vitro but a detailed account of their intrinsic membrane properties responsible for spontaneous firing is currently lacking. To resolve this, we performed a voltage-clamp electrophysiological study in brain slices to describe their major ionic currents and then constructed a computer model and used simulations to understand the mechanisms behind autorhythmicity in silico...
April 3, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28353176/mathematical-investigation-of-ip3-dependent-calcium-dynamics-in-astrocytes
#6
Gregory Handy, Marsa Taheri, John A White, Alla Borisyuk
We study evoked calcium dynamics in astrocytes, a major cell type in the mammalian brain. Experimental evidence has shown that such dynamics are highly variable between different trials, cells, and cell subcompartments. Here we present a qualitative analysis of a recent mathematical model of astrocyte calcium responses. We show how the major response types are generated in the model as a result of the underlying bifurcation structure. By varying key channel parameters, mimicking blockers used by experimentalists, we manipulate this underlying bifurcation structure and predict how the distributions of responses can change...
March 28, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28271301/mechanisms-of-circumferential-gyral-convolution-in-primate-brains
#7
Tuo Zhang, Mir Jalil Razavi, Hanbo Chen, Yujie Li, Xiao Li, Longchuan Li, Lei Guo, Xiaoping Hu, Tianming Liu, Xianqiao Wang
Mammalian cerebral cortices are characterized by elaborate convolutions. Radial convolutions exhibit homology across primate species and generally are easily identified in individuals of the same species. In contrast, circumferential convolutions vary across species as well as individuals of the same species. However, systematic study of circumferential convolution patterns is lacking. To address this issue, we utilized structural MRI (sMRI) and diffusion MRI (dMRI) data from primate brains. We quantified cortical thickness and circumferential convolutions on gyral banks in relation to axonal pathways and density along the gray matter/white matter boundaries...
March 7, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28236135/deriving-theoretical-phase-locking-values-of-a-coupled-cortico-thalamic-neural-mass-model-using-center-manifold-reduction
#8
Yutaro Ogawa, Ikuhiro Yamaguchi, Kiyoshi Kotani, Yasuhiko Jimbo
Cognitive functions such as sensory processing and memory processes lead to phase synchronization in the electroencephalogram or local field potential between different brain regions. There are a lot of computational researches deriving phase locking values (PLVs), which are an index of phase synchronization intensity, from neural models. However, these researches derive PLVs numerically. To the best of our knowledge, there have been no reports on the derivation of a theoretical PLV. In this study, we propose an analytical method for deriving theoretical PLVs from a cortico-thalamic neural mass model described by a delay differential equation...
February 24, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/27778248/analysis-of-the-dynamics-of-temporal-relationships-of-neural-activities-using-optical-imaging-data
#9
Jannetta S Steyn, Peter Andras
The temporal relationship between the activities of neurons in biological neural systems is critically important for the correct delivery of the functionality of these systems. Fine measurement of temporal relationships of neural activities using micro-electrodes is possible but this approach is very limited due to spatial constraints in the context of physiologically valid settings of neural systems. Optical imaging with voltage-sensitive dyes or calcium dyes can provide data about the activity patterns of many neurons in physiologically valid settings, but the data is relatively noisy...
April 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/27812835/anti-correlations-in-the-degree-distribution-increase-stimulus-detection-performance-in-noisy-spiking-neural-networks
#10
Marijn B Martens, Arthur R Houweling, Paul H E Tiesinga
Neuronal circuits in the rodent barrel cortex are characterized by stable low firing rates. However, recent experiments show that short spike trains elicited by electrical stimulation in single neurons can induce behavioral responses. Hence, the underlying neural networks provide stability against internal fluctuations in the firing rate, while simultaneously making the circuits sensitive to small external perturbations. Here we studied whether stability and sensitivity are affected by the connectivity structure in recurrently connected spiking networks...
February 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/27726048/hierarchical-winner-take-all-particle-swarm-optimization-social-network-for-neural-model-fitting
#11
Brandon S Coventry, Aravindakshan Parthasarathy, Alexandra L Sommer, Edward L Bartlett
Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons...
February 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/27714569/optimal-nonlinear-cue-integration-for-sound-localization
#12
Brian J Fischer, Jose Luis Peña
Integration of multiple sensory cues can improve performance in detection and estimation tasks. There is an open theoretical question of the conditions under which linear or nonlinear cue combination is Bayes-optimal. We demonstrate that a neural population decoded by a population vector requires nonlinear cue combination to approximate Bayesian inference. Specifically, if cues are conditionally independent, multiplicative cue combination is optimal for the population vector. The model was tested on neural and behavioral responses in the barn owl's sound localization system where space-specific neurons owe their selectivity to multiplicative tuning to sound localization cues interaural phase (IPD) and level (ILD) differences...
February 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/27704337/modeling-the-differentiation-of-a-and-c-type-baroreceptor-firing-patterns
#13
Jacob Sturdy, Johnny T Ottesen, Mette S Olufsen
The baroreceptor neurons serve as the primary transducers of blood pressure for the autonomic nervous system and are thus critical in enabling the body to respond effectively to changes in blood pressure. These neurons can be separated into two types (A and C) based on the myelination of their axons and their distinct firing patterns elicited in response to specific pressure stimuli. This study has developed a comprehensive model of the afferent baroreceptor discharge built on physiological knowledge of arterial wall mechanics, firing rate responses to controlled pressure stimuli, and ion channel dynamics within the baroreceptor neurons...
February 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/27629590/twenty-years-of-modeldb-and-beyond-building-essential-modeling-tools-for-the-future-of-neuroscience
#14
REVIEW
Robert A McDougal, Thomas M Morse, Ted Carnevale, Luis Marenco, Rixin Wang, Michele Migliore, Perry L Miller, Gordon M Shepherd, Michael L Hines
Neuron modeling may be said to have originated with the Hodgkin and Huxley action potential model in 1952 and Rall's models of integrative activity of dendrites in 1964. Over the ensuing decades, these approaches have led to a massive development of increasingly accurate and complex data-based models of neurons and neuronal circuits. ModelDB was founded in 1996 to support this new field and enhance the scientific credibility and utility of computational neuroscience models by providing a convenient venue for sharing them...
February 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/27629491/artefactual-origin-of-biphasic-cortical-spike-lfp-correlation
#15
Michael Okun
Electrophysiological data acquisition systems introduce various distortions into the signals they record. While such distortions were discussed previously, their effects are often not appreciated. Here I show that the biphasic shape of cortical spike-triggered LFP average (stLFP), reported in multiple studies, is likely an artefact introduced by high-pass filter of the neural data acquisition system when the actual stLFP has a single trough around the zero lag.
February 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28102460/neural-mass-models-as-a-tool-to-investigate-neural-dynamics-during-seizures
#16
Tatiana Kameneva, Tianlin Ying, Ben Guo, Dean R Freestone
Epilepsy is one of the most common neurological disorders and is characterized by recurrent seizures. We use theoretical neuroscience tools to study brain dynamics during seizures. We derive and simulate a computational model of a network of hippocampal neuronal populations. Each population within the network is based on a model that has been shown to replicate the electrophysiological dynamics observed during seizures. The results provide insights into possible mechanisms for seizure spread. We observe that epileptiform activity remains localized to a pathological region when a global connectivity parameter is less than a critical value...
January 19, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28025784/multi-scale-detection-of-rate-changes-in-spike-trains-with-weak-dependencies
#17
Michael Messer, Kauê M Costa, Jochen Roeper, Gaby Schneider
The statistical analysis of neuronal spike trains by models of point processes often relies on the assumption of constant process parameters. However, it is a well-known problem that the parameters of empirical spike trains can be highly variable, such as for example the firing rate. In order to test the null hypothesis of a constant rate and to estimate the change points, a Multiple Filter Test (MFT) and a corresponding algorithm (MFA) have been proposed that can be applied under the assumption of independent inter spike intervals (ISIs)...
December 26, 2016: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/27942935/propagation-and-synchronization-of-reverberatory-bursts-in-developing-cultured-networks
#18
Chih-Hsu Huang, Yu-Ting Huang, Chun-Chung Chen, C K Chan
Developing networks of neural systems can exhibit spontaneous, synchronous activities called neural bursts, which can be important in the organization of functional neural circuits. Before the network matures, the activity level of a burst can reverberate in repeated rise-and-falls in periods of hundreds of milliseconds following an initial wave-like propagation of spiking activity, while the burst itself lasts for seconds. To investigate the spatiotemporal structure of the reverberatory bursts, we culture dissociated, rat cortical neurons on a high-density multi-electrode array to record the dynamics of neural activity over the growth and maturation of the network...
December 9, 2016: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/27909842/the-relationship-between-nernst-equilibrium-variability-and-the-multifractality-of-interspike-intervals-in-the-hippocampus
#19
Stephen R Meier, Jarrett L Lancaster, Dustin Fetterhoff, Robert A Kraft, Robert E Hampson, Joseph M Starobin
Spatiotemporal patterns of action potentials are considered to be closely related to information processing in the brain. Auto-generating neurons contributing to these processing tasks are known to cause multifractal behavior in the inter-spike intervals of the output action potentials. In this paper we define a novel relationship between this multifractality and the adaptive Nernst equilibrium in hippocampal neurons. Using this relationship we are able to differentiate between various drugs at varying dosages...
December 1, 2016: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/27909841/the-shaping-of-intrinsic-membrane-potential-oscillations-positive-negative-feedback-ionic-resonance-amplification-nonlinearities-and-time-scales
#20
Horacio G Rotstein
The generation of intrinsic subthreshold (membrane potential) oscillations (STOs) in neuronal models requires the interaction between two processes: a relatively fast positive feedback that favors changes in voltage and a slower negative feedback that opposes these changes. These are provided by the so-called resonant and amplifying gating variables associated to the participating ionic currents. We investigate both the biophysical and dynamic mechanisms of generation of STOs and how their attributes (frequency and amplitude) depend on the model parameters for biophysical (conductance-based) models having qualitatively different types of resonant currents (activating and inactivating) and an amplifying current...
December 1, 2016: Journal of Computational Neuroscience
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