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Spike timing precision of neuronal circuits
AbstractSpike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuron...
Source: Journal of Computational Neuroscience - June 1, 2018 Category: Neuroscience Source Type: research

The effect of inhibition on the existence of traveling wave solutions for a neural field model of human seizure termination
AbstractIn this paper we study the influence of inhibition on an activity-based neural field model consisting of an excitatory population with a linear adaptation term that directly regulates the activity of the excitatory population. Such a model has been used to replicate traveling wave data as observed in high density local field potential recordings (Gonz ález-Ramírez et al.PLoS Computational Biology,11(2), e1004065,2015). In this work, we show that by adding an inhibitory population to this model we can still replicate wave properties as observed in human clinical data preceding seizure termination, but the paramete...
Source: Journal of Computational Neuroscience - May 24, 2018 Category: Neuroscience Source Type: research

Linear feature projection-based real-time decoding of limb state from dorsal root ganglion recordings
AbstractProprioceptive afferent activities recorded by a multichannel microelectrode have been used to decode limb movements to provide sensory feedback signals for closed-loop control in a functional electrical stimulation (FES) system. However, analyzing the high dimensionality of neural activity is one of the major challenges in real-time applications. This paper proposes a linear feature projection method for the real-time decoding of ankle and knee joint angles. Single-unit activity was extracted as a feature vector from proprioceptive afferent signals that were recorded from the L7 dorsal root ganglion during passive...
Source: Journal of Computational Neuroscience - May 15, 2018 Category: Neuroscience Source Type: research

Analytical modelling of temperature effects on an AMPA-type synapse
AbstractIt was previously reported, that temperature may significantly influence neural dynamics on the different levels of brain function. Thus, in computational neuroscience, it would be useful to make models scalable for a wide range of various brain temperatures. However, lack of experimental data and an absence of temperature-dependent analytical models of synaptic conductance does not allow to include temperature effects at the multi-neuron modeling level. In this paper, we propose a first step to deal with this problem: A new analytical model of AMPA-type synaptic conductance, which is able to incorporate temperatur...
Source: Journal of Computational Neuroscience - May 11, 2018 Category: Neuroscience Source Type: research

Spike timing precision of neuronal circuits
AbstractSpike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuron...
Source: Journal of Computational Neuroscience - April 17, 2018 Category: Neuroscience Source Type: research

Phase model-based neuron stabilization into arbitrary clusters
AbstractDeep brain stimulation (DBS) is a common method of combating pathological conditions associated with Parkinson ’s disease, Tourette syndrome, essential tremor, and other disorders, but whose mechanisms are not fully understood. One hypothesis, supported experimentally, is that some symptoms of these disorders are associated with pathological synchronization of neurons in the basal ganglia and thalamus. For this reason, there has been interest in recent years in finding efficient ways to desynchronize neurons that are both fast-acting and low-power. Recent results on coordinated reset and periodically forced oscil...
Source: Journal of Computational Neuroscience - April 3, 2018 Category: Neuroscience Source Type: research

Linearization of excitatory synaptic integration at no extra cost
AbstractIn many theories of neural computation, linearly summed synaptic activation is a pervasive assumption for the computations performed by individual neurons. Indeed, for certain nominally optimal models, linear summation is required. However, the biophysical mechanisms needed to produce linear summation may add to the energy-cost of neural processing. Thus, the benefits provided by linear summation may be outweighed by the energy-costs. Using voltage-gated conductances in a relatively simple neuron model, this paper quantifies the cost of linearizing dendritically localized synaptic activation. Different combinations...
Source: Journal of Computational Neuroscience - April 1, 2018 Category: Neuroscience Source Type: research

Perceptual judgments via sensory-motor interaction assisted by cortical GABA
AbstractRecurrent input to sensory cortex, via long-range reciprocal projections between motor and sensory cortices, is essential for accurate perceptual judgments. GABA levels in sensory cortices correlate with perceptual performance. We simulated a neuron-astrocyte network model to investigate how top-down, feedback signaling from a motor network (Nmot) to a sensory network (Nsen) affects perceptual judgments in association with ambient (extracellular) GABA levels. In the Nsen, astrocytic transporters modulated ambient GABA levels around pyramidal cells. A simple perceptual task was implemented: detection of a feature st...
Source: Journal of Computational Neuroscience - April 1, 2018 Category: Neuroscience Source Type: research

A mathematical model of recurrent spreading depolarizations
AbstractA detailed biophysical model for a neuron/astrocyte network is developed in order to explore mechanisms responsible for the initiation and propagation of recurrent cortical spreading depolarizations. The model incorporates biophysical processes not considered in the earlier models. This includes a model for the Na+-glutamate transporter, which allows for a detailed description of reverse glutamate uptake. In particular, we consider the specific roles of elevated extracellular glutamate and K+ in the initiation, propagation and recurrence of spreading depolarizations. (Source: Journal of Computational Neuroscience)
Source: Journal of Computational Neuroscience - April 1, 2018 Category: Neuroscience Source Type: research

The role of phase shifts of sensory inputs in walking revealed by means of phase reduction
In this study, we employed phase reduction and averaging theory to this large network model in order to reduce it to a system of coupled phase oscillators. This enabled us to analyze the complex behavior of the system in a reduced parameter space. In this paper, we show that the reduced model reproduces the results of the original model. By analyzing the interaction of just two coupled phase oscillators, we found that the neighboring CPGs could operate within distinct regimes, depending on the phase shift between the sensory inputs from the extremities and the phases of the individual CPGs. We demonstrate that this depende...
Source: Journal of Computational Neuroscience - March 27, 2018 Category: Neuroscience Source Type: research

An integrate-and-fire model to generate spike trains with long-range dependence
AbstractLong-range dependence (LRD) has been observed in a variety of phenomena in nature, and for several years also in the spiking activity of neurons. Often, this is interpreted as originating from a non-Markovian system. Here we show that a purely Markovian integrate-and-fire (IF) model, with a noisy slow adaptation term, can generate interspike intervals (ISIs) that appear as having LRD. However a proper analysis shows that this is not the case asymptotically. For comparison, we also consider a new model of individual IF neuron with fractional (non-Markovian) noise. The correlations of its spike trains are studied and...
Source: Journal of Computational Neuroscience - March 24, 2018 Category: Neuroscience Source Type: research

Synaptic efficacy shapes resource limitations in working memory
AbstractWorking memory (WM) is limited in its temporal length and capacity. Classic conceptions of WM capacity assume the system possesses a finite number of slots, but recent evidence suggests WM may be a continuous resource. Resource models typically assume there is no hard upper bound on the number of items that can be stored, but WM fidelity decreases with the number of items. We analyze a neural field model of multi-item WM that associates each item with the location of a bump in a finite spatial domain, considering items that span a one-dimensional continuous feature space. Our analysis relates the neural architectur...
Source: Journal of Computational Neuroscience - March 15, 2018 Category: Neuroscience Source Type: research

Learning neural connectivity from firing activity: efficient algorithms with provable guarantees on topology
AbstractThe connectivity of a neuronal network has a major effect on its functionality and role. It is generally believed that the complex network structure of the brain provides a physiological basis for information processing. Therefore, identifying the network ’s topology has received a lot of attentions in neuroscience and has been the center of many research initiatives such as Human Connectome Project. Nevertheless,direct and invasive approaches that slice and observe the neural tissue have proven to be time consuming, complex and costly. As a result, theinverse methods that utilize firing activity of neurons in or...
Source: Journal of Computational Neuroscience - February 20, 2018 Category: Neuroscience Source Type: research

Perceptual judgments via sensory-motor interaction assisted by cortical GABA
AbstractRecurrent input to sensory cortex, via long-range reciprocal projections between motor and sensory cortices, is essential for accurate perceptual judgments. GABA levels in sensory cortices correlate with perceptual performance. We simulated a neuron-astrocyte network model to investigate how top-down, feedback signaling from a motor network (Nmot) to a sensory network (Nsen) affects perceptual judgments in association with ambient (extracellular) GABA levels. In the Nsen, astrocytic transporters modulated ambient GABA levels around pyramidal cells. A simple perceptual task was implemented: detection of a feature st...
Source: Journal of Computational Neuroscience - January 31, 2018 Category: Neuroscience Source Type: research