Journal of Computational Neuroscience This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Predictive control of intersegmental tarsal movements in an insect
AbstractIn 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. An Artificial Neural Networ...
Source: Journal of Computational Neuroscience - April 22, 2017 Category: Neuroscience Source Type: research

Reaction time impairments in decision-making networks as a diagnostic marker for traumatic brain injuries and neurological diseases
AbstractThe 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 throu...
Source: Journal of Computational Neuroscience - April 10, 2017 Category: Neuroscience Source Type: research

Multirate method for co-simulation of electrical-chemical systems in multiscale modeling
AbstractMultiscale 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. When time constants of model componen...
Source: Journal of Computational Neuroscience - April 7, 2017 Category: Neuroscience Source Type: research

Neural field model of seizure-like activity in isolated cortex
AbstractEpileptiform 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. Furthermore, within...
Source: Journal of Computational Neuroscience - April 7, 2017 Category: Neuroscience Source Type: research

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
AbstractDopamine (DA) neurons of the ventrolateral periaqueductal gray (vlPAG) and dorsal raphe nucleus (DRN) fire spontaneous action potentials (APs) at slow, regular patternsin 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 autorhythmicityin silico. We found that vlPAG/DRN DA neurons exhibit a number of voltage-dependent curr...
Source: Journal of Computational Neuroscience - April 3, 2017 Category: Neuroscience Source Type: research

Mathematical investigation of IP 3 -dependent calcium dynamics in astrocytes
AbstractWe 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 ...
Source: Journal of Computational Neuroscience - March 28, 2017 Category: Neuroscience Source Type: research

Mechanisms of circumferential gyral convolution in primate brains
AbstractMammalian 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 a...
Source: Journal of Computational Neuroscience - March 6, 2017 Category: Neuroscience Source Type: research

Deriving theoretical phase locking values of a coupled cortico-thalamic neural mass model using center manifold reduction
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. First, the model for generating neural signals is transformed into a normal form of the Hopf bifurcation using center manifold reduction. Second, the normal form is transformed into a phase model that is suitable for analyzing synchronization phenomena. Third, the Fokker –Planck equation of the phase model is derived and the phase difference distribution is obtained. Finally, the PLVs are calculated from the stationary distribution of the phase difference. The ...
Source: Journal of Computational Neuroscience - February 23, 2017 Category: Neuroscience Source Type: research

Neural mass models as a tool to investigate neural dynamics during seizures
AbstractEpilepsy 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 les...
Source: Journal of Computational Neuroscience - January 18, 2017 Category: Neuroscience Source Type: research

Multi-scale detection of rate changes in spike trains with weak dependencies
AbstractThe 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). As empirical spike trains often show weak dependencies in the correlation st...
Source: Journal of Computational Neuroscience - December 25, 2016 Category: Neuroscience Source Type: research

Propagation and synchronization of reverberatory bursts in developing cultured networks
AbstractDeveloping 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 act...
Source: Journal of Computational Neuroscience - December 8, 2016 Category: Neuroscience Source Type: research

The shaping of intrinsic membrane potential oscillations: positive/negative feedback, ionic resonance/amplification, nonlinearities and time scales
AbstractThe 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 qualitati...
Source: Journal of Computational Neuroscience - November 30, 2016 Category: Neuroscience Source Type: research

The relationship between nernst equilibrium variability and the multifractality of interspike intervals in the hippocampus
AbstractSpatiotemporal 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. Conventional methods limit their ability to account for cellular charge depletion by not including these ...
Source: Journal of Computational Neuroscience - November 30, 2016 Category: Neuroscience Source Type: research

A model of signal processing at the isolated hair cell of the frog semicircular canal
AbstractA computational model has been developed to simulate the electrical behavior of the type II hair cell dissected from thecrista ampullaris of frog semicircular canals. In its basolateral membrane, it hosts a system of four voltage-dependent conductances (gA,gKV,gKCa,gCa). The conductance behavior was mathematically described using original patch-clamp experimental data. The transient K current, IA, was isolated as the difference between the currents obtained before and after removing IA inactivation. The remaining current, IKD, results from the summation of a voltage-dependent K current, IKV, a voltage-calcium-depen...
Source: Journal of Computational Neuroscience - November 14, 2016 Category: Neuroscience Source Type: research

Anti-correlations in the degree distribution increase stimulus detection performance in noisy spiking neural networks
AbstractNeuronal 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. We found that anti-correlation between the number of afferent...
Source: Journal of Computational Neuroscience - November 3, 2016 Category: Neuroscience Source Type: research