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.

Dynamics of a neuron –glia system: the occurrence of seizures and the influence of electroconvulsive stimuli
AbstractIn this paper, we investigate the dynamics of a neuron –glia cell system and the underlying mechanism for the occurrence of seizures. For our mathematical and numerical investigation of the cell model we will use bifurcation analysis and some computational methods. It turns out that an increase of the potassium concentration in the reservoir is one tr igger for seizures and is related to a torus bifurcation. In addition, we will study potassium dynamics of the model by considering a reduced version and we will show how both mechanisms are linked to each other. Moreover, the reduction of the potassium leak current...
Source: Journal of Computational Neuroscience - May 11, 2020 Category: Neuroscience Source Type: research

Short term depression, presynaptic inhibition and local neuron diversity play key functional roles in the insect antennal lobe
AbstractAs the oldest, but least understood sensory system in evolution, the olfactory system represents one of the most challenging research targets in sensory neurobiology. Although a large number of computational models of the olfactory system have been proposed, they do not account for the diversity in physiology, connectivity of local neurons, and several recent discoveries in the insect antennal lobe, a major olfactory organ in insects. Recent studies revealed that the response of some projection neurons were reduced by application of a GABA antagonist, and that insects are sensitive to odor pulse frequency. To accou...
Source: Journal of Computational Neuroscience - May 8, 2020 Category: Neuroscience Source Type: research

Ring models of binocular rivalry and fusion
AbstractWhen similar visual stimuli are presented binocularly to both eyes, one perceives a fused single image. However, when the two stimuli are distinct, one does not perceive a single image; instead, one perceives binocular rivalry. That is, one perceives one of the stimulated patterns for a few seconds, then the other for few seconds, and so on – with random transitions between the two percepts. Most theoretical studies focus on rivalry, with few considering the coexistence of fusion and rivalry. Here we develop three distinct computational neuronal network models which capture binocular rivalry with realistic stocha...
Source: Journal of Computational Neuroscience - May 2, 2020 Category: Neuroscience Source Type: research

A hierarchical model of perceptual multistability involving interocular grouping
AbstractAmbiguous visual images can generate dynamic and stochastic switches in perceptual interpretation known as perceptual rivalry. Such dynamics have primarily been studied in the context of rivalry between two percepts, but there is growing interest in the neural mechanisms that drive rivalry between more than two percepts. In recent experiments, we showed that split images presented to each eye lead to subjects perceiving four stochastically alternating percepts (Jacot-Guillarmod et al.Vision research, 133, 37 –46,2017): two single eye images and two interocularly grouped images. Here we propose a hierarchical neur...
Source: Journal of Computational Neuroscience - April 26, 2020 Category: Neuroscience Source Type: research

Modelling acute and lasting effects of tDCS on epileptic activity
AbstractTranscranial Direct brain stimulation (tDCS) is commonly used in order to modulate cortical networks activity during physiological processes through the application of weak electrical fields with scalp electrodes. Cathodal stimulation has been shown to decrease brain excitability in the context of epilepsy, with variable success. However, the cellular mechanisms responsible for the acute and the long-lasting effect of tDCS remain elusive. Using a novel approach of computational modeling that combines detailed but functionally integrated neurons we built a physiologically-based thalamocortical column. This model com...
Source: Journal of Computational Neuroscience - April 18, 2020 Category: Neuroscience Source Type: research

A computational model for grid maps in neural populations
AbstractGrid cells in the entorhinal cortex, together with head direction, place, speed and border cells, are major contributors to the organization of spatial representations in the brain. In this work we introduce a novel theoretical and algorithmic framework able to explain the optimality of hexagonal grid-like response patterns. We show that this pattern is a result of minimal variance encoding of neurons together with maximal robustness to neurons ’ noise and minimal number of encoding neurons. The novelty lies in the formulation of the encoding problem considering neurons as an overcomplete basis (a frame) where th...
Source: Journal of Computational Neuroscience - March 2, 2020 Category: Neuroscience Source Type: research

Inference of synaptic connectivity and external variability in neural microcircuits
AbstractA major goal in neuroscience is to estimate neural connectivity from large scale extracellular recordings of neural activityin vivo. This is challenging in part because any such activity is modulated by the unmeasured external synaptic input to the network, known as the common input problem. Many different measures of functional connectivity have been proposed in the literature, but their direct relationship to synaptic connectivity is often assumed or ignored. Forin vivo data, measurements of this relationship would require a knowledge of ground truth connectivity, which is nearly always unavailable. Instead, many...
Source: Journal of Computational Neuroscience - February 20, 2020 Category: Neuroscience Source Type: research

Multiscale relevance and informative encoding in neuronal spike trains
AbstractNeuronal responses to complex stimuli and tasks can encompass a wide range of time scales. Understanding these responses requires measures that characterize how the information on these response patterns are represented across multiple temporal resolutions. In this paper we propose a metric – which we call multiscale relevance (MSR) – to capture the dynamical variability of the activity of single neurons across different time scales. The MSR is a non-parametric, fully featureless indicator in that it uses only the time stamps of the firing activity without resorting to anya priori covariate or invoking any spec...
Source: Journal of Computational Neuroscience - January 27, 2020 Category: Neuroscience Source Type: research

Transient neocortical gamma oscillations induced by neuronal response modulation
AbstractIn this paper a mean field model of spatio-temporal electroencephalographic activity in the neocortex is used to computationally study the emergence of neocortical gamma oscillations as a result of neuronal response modulation. It is shown using a numerical bifurcation analysis that gamma oscillations emerge robustly in the solutions of the model and transition to beta oscillations through coordinated modulation of the responsiveness of inhibitory and excitatory neuronal populations. The spatio-temporal pattern of the propagation of these oscillations across the neocortex is illustrated by solving the equations of ...
Source: Journal of Computational Neuroscience - January 27, 2020 Category: Neuroscience Source Type: research

A calcium-influx-dependent plasticity model exhibiting multiple STDP curves
AbstractHebbian plasticity means that if the firing of two neurons is correlated, then their connection is strengthened. Conversely, uncorrelated firing causes a decrease in synaptic strength. Spike-timing-dependent plasticity (STDP) represents one instantiation of Hebbian plasticity. Under STDP, synaptic changes depend on the relative timing of the pre- and post-synaptic firing. By inducing pre- and post-synaptic firing at different relative times the STDP curves of many neurons have been determined, and it has been found that there are different curves for different neuron types or synaptic sites. Biophysically, strength...
Source: Journal of Computational Neuroscience - January 23, 2020 Category: Neuroscience Source Type: research

A general method to generate artificial spike train populations matching recorded neurons
AbstractWe developed a general method to generate populations of artificial spike trains (ASTs) that match the statistics of recorded neurons. The method is based on computing a Gaussian local rate function of the recorded spike trains, which results in rate templates from which ASTs are drawn as gamma distributed processes with a refractory period. Multiple instances of spike trains can be sampled from the same rate templates. Importantly, we can manipulate rate-covariances between spike trains by performing simple algorithmic transformations on the rate templates, such as filtering or amplifying specific frequency bands,...
Source: Journal of Computational Neuroscience - January 22, 2020 Category: Neuroscience Source Type: research

Fast simulation of extracellular action potential signatures based on a morphological filtering approximation
AbstractSimulating extracellular recordings of neuronal populations is an important and challenging task both for understanding the nature and relationships between extracellular field potentials at different scales, and for the validation of methodological tools for signal analysis such as spike detection and sorting algorithms. Detailed neuronal multicompartmental models with active or passive compartments are commonly used in this objective. Although using such realistic NEURON models could lead to realistic extracellular potentials, it may require a high computational burden making the simulation of large populations d...
Source: Journal of Computational Neuroscience - January 16, 2020 Category: Neuroscience Source Type: research

Oscillations and concentration dynamics of brain tissue oxygen in neonates and adults
AbstractThe brain is a metabolically demanding organ and its health directly depends on brain oxygen dynamics to prevent hypoxia and ischemia. Localized brain tissue oxygen is characterized by a baseline level combined with spontaneous oscillations. These oscillations are attributed to spontaneous changes of vascular tone at the level of arterioles and their frequencies depend on age. Specifically, lower frequencies are more typical for neonates than for adults. We have built a mathematical model which analyses the diffusion abilities of oxygen based on the frequency of source brain oxygen oscillations and neuronal demand....
Source: Journal of Computational Neuroscience - January 7, 2020 Category: Neuroscience Source Type: research

Spatiotemporal model of tripartite synapse with perinodal astrocytic process
AbstractInformation transfer may not be limited only to synapses. Therefore, the processes and dynamics of biological neuron-astrocyte coupling and intercellular interaction within this domain are worth investigating. Existing models of tripartite synapse consider an astrocyte as a point process. Here, we extended the tripartite synapse model by considering the astrocytic processes (synaptic and perinodal) as compartments. The scattered extrinsic signals in the extracellular space and the presence of calcium stores in different astrocytic sites create local transient [Ca2+]. We investigated the Ca2+ dynamics and found that...
Source: Journal of Computational Neuroscience - December 2, 2019 Category: Neuroscience Source Type: research

Analyzing dynamic decision-making models using Chapman-Kolmogorov equations
AbstractDecision-making in dynamic environments typically requires adaptive evidence accumulation that weights new evidence more heavily than old observations. Recent experimental studies of dynamic decision tasks require subjects to make decisions for which the correct choice switches stochastically throughout a single trial. In such cases, an ideal observer ’s belief is described by an evolution equation that is doubly stochastic, reflecting stochasticity in the both observations and environmental changes. In these contexts, we show that the probability density of the belief can be represented using differential Chapma...
Source: Journal of Computational Neuroscience - November 15, 2019 Category: Neuroscience Source Type: research