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.

Ion channel noise can explain firing correlation in auditory nerves
AbstractNeural spike trains are commonly characterized as a Poisson point process. However, the Poisson assumption is a poor model for spiking in auditory nerve fibres because it is known that interspike intervals display positive correlation over long time scales and negative correlation over shorter time scales. We have therefore developed a biophysical model based on the well-known Meddis model of the peripheral auditory system, to produce simulated auditory nerve fibre spiking statistics that more closely match the firing correlations observed in empirical data. We achieve this by introducing biophysically realistic io...
Source: Journal of Computational Neuroscience - August 1, 2016 Category: Neuroscience Source Type: research

Neural assemblies revealed by inferred connectivity-based models of prefrontal cortex recordings
We present two graphical model-based approaches to analyse the distribution of neural activities in the prefrontal cortex of behaving rats. The first method aims at identifying cell assemblies, groups of synchronously activating neurons possibly representing the units of neural coding and memory. A graphical (Ising) model distribution of snapshots of the neural activities, with an effective connectivity matrix reproducing the correlation statistics, is inferred from multi-electrode recordings, and then simulated in the presence of a virtual external drive, favoring high activity (multi-neuron) configurations. As the drive ...
Source: Journal of Computational Neuroscience - July 27, 2016 Category: Neuroscience Source Type: research

Two ’s company, three (or more) is a simplex
< h3 class= " a-plus-plus " > Abstract < /h3 > < p class= " a-plus-plus " > The language of graph theory, or network science, has proven to be an exceptional tool for addressing myriad problems in neuroscience. Yet, the use of networks is predicated on a critical simplifying assumption: that the quintessential unit of interest in a brain is a dyad – two nodes (neurons or brain regions) connected by an edge. While rarely mentioned, this fundamental assumption inherently limits the types of neural structure and function that graphs can be used to model. Here, we describe a generalization of graphs that overcomes these limi...
Source: Journal of Computational Neuroscience - July 21, 2016 Category: Neuroscience Source Type: research

Computational modeling of epileptiform activities in medial temporal lobe epilepsy combined with in vitro experiments
Abstract In this paper, we propose a comprehensive computational model that is able to reproduce three epileptiform activities. The model targets a hippocampal formation that is known to be an important lesion in medial temporal lobe epilepsy. It consists of four sub-networks consisting of excitatory and inhibitory neurons and well-known signal pathways, with consideration of propagation delay. The three epileptiform activities involve fast and slow interictal discharge and ictal discharge, and those activities can be induced in vitro by application of 4-Aminopyridine in entorhinal cortex combined hippoca...
Source: Journal of Computational Neuroscience - July 13, 2016 Category: Neuroscience Source Type: research

Axonal model for temperature stimulation
Abstract Recent studies indicate that a rapid increase in local temperature plays an important role in nerve stimulation by laser. To analyze the temperature effect, our study modified the classical HH axonal model by incorporating a membrane capacitance-temperature relationship. The modified model successfully simulated the generation and propagation of action potentials induced by a rapid increase in local temperature when the Curie temperature of membrane capacitance is below 40 °C, while the classical model failed to simulate the axonal excitation by temperature stimulation. The new model predicts t...
Source: Journal of Computational Neuroscience - June 23, 2016 Category: Neuroscience Source Type: research

AMPA/NMDA cooperativity and integration during a single synaptic event
Abstract Coexistence of AMPA and NMDA receptors in glutamatergic synapses leads to a cooperative effect that can be very complex. This effect is dependent on many parameters including the relative and absolute number of the two types of receptors and biophysical parameters that can vary among synapses of the same cell. Herein we simulate the AMPA/NMDA cooperativity by using different number of the two types of receptors and considering the effect of the spine resistance on the EPSC production. Our results show that the relative number of NMDA with respect to AMPA produces a different degree of cooperation...
Source: Journal of Computational Neuroscience - June 13, 2016 Category: Neuroscience Source Type: research

Two’s company, three (or more) is a simplex
Abstract The language of graph theory, or network science, has proven to be an exceptional tool for addressing myriad problems in neuroscience. Yet, the use of networks is predicated on a critical simplifying assumption: that the quintessential unit of interest in a brain is a dyad – two nodes (neurons or brain regions) connected by an edge. While rarely mentioned, this fundamental assumption inherently limits the types of neural structure and function that graphs can be used to model. Here, we describe a generalization of graphs that overcomes these limitations, thereby offering a broad range of new po...
Source: Journal of Computational Neuroscience - June 10, 2016 Category: Neuroscience Source Type: research

Parallel linear dynamic models can mimic the McGurk effect in clinical populations
This report hypothesizes reasons why certain clinical and listeners who are hard of hearing might be more susceptible to visual influence. Conversely, we also examine why other listeners appear less susceptible to the McGurk effect (i.e., they report hearing just the auditory stimulus without being influenced by the visual). Such explanations are accompanied by a mechanistic explanation of integration phenomena including visual inhibition of auditory information, or slower rate of accumulation of inputs. First, simulations of a linear dynamic parallel interactive model were instantiated using inhibition and facilitation to...
Source: Journal of Computational Neuroscience - June 6, 2016 Category: Neuroscience Source Type: research

Calcium dependent plasticity applied to repetitive transcranial magnetic stimulation with a neural field model
Abstract The calcium dependent plasticity (CaDP) approach to the modeling of synaptic weight change is applied using a neural field approach to realistic repetitive transcranial magnetic stimulation (rTMS) protocols. A spatially-symmetric nonlinear neural field model consisting of populations of excitatory and inhibitory neurons is used. The plasticity between excitatory cell populations is then evaluated using a CaDP approach that incorporates metaplasticity. The direction and size of the plasticity (potentiation or depression) depends on both the amplitude of stimulation and duration of the protocol. Th...
Source: Journal of Computational Neuroscience - June 3, 2016 Category: Neuroscience Source Type: research

Bifurcation analysis of a two-compartment hippocampal pyramidal cell model
Abstract The Pinsky-Rinzel model is a non-smooth 2-compartmental CA3 pyramidal cell model that has been used widely within the field of neuroscience. Here we propose a modified (smooth) system that captures the qualitative behaviour of the original model, while allowing the use of available, numerical continuation methods to perform full-system bifurcation and fast-slow analysis. We study the bifurcation structure of the full system as a function of the applied current and the maximal calcium conductance. We identify the bifurcations that shape the transitions between resting, bursting and spiking behavio...
Source: Journal of Computational Neuroscience - May 24, 2016 Category: Neuroscience Source Type: research

Efficient simulations of tubulin-driven axonal growth
Abstract This work concerns efficient and reliable numerical simulations of the dynamic behaviour of a moving-boundary model for tubulin-driven axonal growth. The model is nonlinear and consists of a coupled set of a partial differential equation (PDE) and two ordinary differential equations. The PDE is defined on a computational domain with a moving boundary, which is part of the solution. Numerical simulations based on standard explicit time-stepping methods are too time consuming due to the small time steps required for numerical stability. On the other hand standard implicit schemes are too complex du...
Source: Journal of Computational Neuroscience - April 27, 2016 Category: Neuroscience Source Type: research

Automated evolutionary optimization of ion channel conductances and kinetics in models of young and aged rhesus monkey pyramidal neurons
We present a three-stage EA optimization protocol for tuning ion channel conductances and kinetics in a generic neuron model with minimal manual intervention. We use the technique of Latin hypercube sampling in a new way, to choose weights for error functions automatically so that each function influences the parameter search to a similar degree. This protocol requires no specialized physiological data collection and is applicable to commonly-collected current clamp data and either single- or multi-objective optimization. We applied the protocol to two representative pyramidal neurons from layer 3 of the prefrontal cortex ...
Source: Journal of Computational Neuroscience - April 21, 2016 Category: Neuroscience Source Type: research

Impact of slow K + currents on spike generation can be described by an adaptive threshold model
In this study, we investigated the impact of slow K+ currents on spike generation mechanism by reducing a detailed conductance-based neuron model. We showed that the detailed model can be reduced to a multi-timescale adaptive threshold model, and derived the formulae that describe the relationship between slow K+ current parameters and reduced model parameters. Our analysis of the reduced model suggests that slow K+ currents have a differential effect on the noise tolerance in neural coding. (Source: Journal of Computational Neuroscience)
Source: Journal of Computational Neuroscience - April 15, 2016 Category: Neuroscience Source Type: research

Slow feature analysis with spiking neurons and its application to audio stimuli
Abstract Extracting invariant features in an unsupervised manner is crucial to perform complex computation such as object recognition, analyzing music or understanding speech. While various algorithms have been proposed to perform such a task, Slow Feature Analysis (SFA) uses time as a means of detecting those invariants, extracting the slowly time-varying components in the input signals. In this work, we address the question of how such an algorithm can be implemented by neurons, and apply it in the context of audio stimuli. We propose a projected gradient implementation of SFA that can be adapted to a H...
Source: Journal of Computational Neuroscience - April 13, 2016 Category: Neuroscience Source Type: research

Modeling the effect of sleep regulation on a neural mass model
Abstract In mammals, sleep is categorized by two main sleep stages, rapid eye movement (REM) and non-REM (NREM) sleep that are known to fulfill different functional roles, the most notable being the consolidation of memory. While REM sleep is characterized by brain activity similar to wakefulness, the EEG activity changes drastically with the emergence of K-complexes, sleep spindles and slow oscillations during NREM sleep. These changes are regulated by circadian and ultradian rhythms, which emerge from an intricate interplay between multiple neuronal populations in the brainstem, forebrain and hypothalam...
Source: Journal of Computational Neuroscience - April 10, 2016 Category: Neuroscience Source Type: research