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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 - January 25, 2018 Category: Neuroscience Source Type: research

Effects of channel blocking on information transmission and energy efficiency in squid giant axons
AbstractAction potentials are the information carriers of neural systems. The generation of action potentials involves the cooperative opening and closing of sodium and potassium channels. This process is metabolically expensive because the ions flowing through open channels need to be restored to maintain concentration gradients of these ions. Toxins like tetraethylammonium can block working ion channels, thus affecting the function and energy cost of neurons. In this paper, by computer simulation of the Hodgkin-Huxley neuron model, we studied the effects of channel blocking with toxins on the information transmission and...
Source: Journal of Computational Neuroscience - January 11, 2018 Category: Neuroscience Source Type: research

New class of reduced computationally efficient neuronal models for large-scale simulations of brain dynamics
AbstractDuring slow-wave sleep, brain electrical activity is dominated by the slow (< 1  Hz) electroencephalogram (EEG) oscillations characterized by the periodic transitions between active (or Up) and silent (or Down) states in the membrane voltage of the cortical and thalamic neurons. Sleep slow oscillation is believed to play critical role in consolidation of recent memories. Past computational studies, based on the Hodgkin-Huxley type neuronal models, revealed possible intracellular and network mechanisms of the neuronal activity during sleep, however, they failed to explore the large-scale cortical network dynamic...
Source: Journal of Computational Neuroscience - December 12, 2017 Category: Neuroscience Source Type: research

Coding of time-dependent stimuli in homogeneous and heterogeneous neural populations
AbstractWe compare the information transmission of a time-dependent signal by two types of uncoupled neuron populations that differ in their sources of variability: i) ahomogeneous population whose units receive independent noise and ii) a deterministicheterogeneous population, where each unit exhibits a different baseline firing rate ( ’disorder’). Our criterion for making both sources of variability quantitatively comparable is that the interspike-interval distributions are identical for both systems. Numerical simulations using leaky integrate-and-fire neurons unveil that a non-zero amount of both noise or disorder ...
Source: Journal of Computational Neuroscience - December 8, 2017 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 - December 5, 2017 Category: Neuroscience Source Type: research

How does transient signaling input affect the spike timing of postsynaptic neuron near the threshold regime: an analytical study
AbstractThe noisy threshold regime, where even a small set of presynaptic neurons can significantly affect postsynaptic spike-timing, is suggested as a key requisite for computation in neurons with high variability. It also has been proposed that signals under the noisy conditions are successfully transferred by a few strong synapses and/or by an assembly of nearly synchronous synaptic activities. We analytically investigate the impact of a transient signaling input on a leaky integrate-and-fire postsynaptic neuron that receives background noise near the threshold regime. The signaling input models a single strong synapse ...
Source: Journal of Computational Neuroscience - December 1, 2017 Category: Neuroscience Source Type: research

The role of astrocytic calcium and TRPV4 channels in neurovascular coupling
AbstractNeuronal activity evokes a localised change in cerebral blood flow in a response known as neurovascular coupling (NVC). Although NVC has been widely studied the exact mechanisms that mediate this response remain unclear; in particular the role of astrocytic calcium is controversial. Mathematical modelling can be a useful tool for investigating the contribution of various signalling pathways towards NVC and for analysing the underlying cellular mechanisms. The lumped parameter model of a neurovascular unit with both potassium and nitric oxide (NO) signalling pathways and comprised of neurons, astrocytes, and vascula...
Source: Journal of Computational Neuroscience - November 20, 2017 Category: Neuroscience Source Type: research

Cliques and cavities in the human connectome
AbstractEncoding brain regions and their connections as a network of nodes and edges captures many of the possible paths along which information can be transmitted as humans process and perform complex behaviors. Because cognitive processes involve large, distributed networks of brain areas, principled examinations of multi-node routes within larger connection patterns can offer fundamental insights into the complexities of brain function. Here, we investigate both densely connected groups of nodes that could perform local computations as well as larger patterns of interactions that would allow for parallel processing. Fin...
Source: Journal of Computational Neuroscience - November 16, 2017 Category: Neuroscience Source Type: research

Modeling mesoscopic cortical dynamics using a mean-field model of conductance-based networks of adaptive exponential integrate-and-fire neurons
AbstractVoltage-sensitive dye imaging (VSDi) has revealed fundamental properties of neocortical processing at macroscopic scales. Since for each pixel VSDi signals report the average membrane potential over hundreds of neurons, it seems natural to use a mean-field formalism to model such signals. Here, we present a mean-field model of networks of Adaptive Exponential (AdEx) integrate-and-fire neurons, with conductance-based synaptic interactions. We study a network of regular-spiking (RS) excitatory neurons and fast-spiking (FS) inhibitory neurons. We use a Master Equation formalism, together with a semi-analytic approach ...
Source: Journal of Computational Neuroscience - November 15, 2017 Category: Neuroscience Source Type: research

Feedforward architectures driven by inhibitory interactions
AbstractDirected information transmission is paramount for many social, physical, and biological systems. For neural systems, scientists have studied this problem under the paradigm of feedforward networks for decades. In most models of feedforward networks, activity is exclusively driven by excitatory neurons and the wiring patterns between them, while inhibitory neurons play only a stabilizing role for the network dynamics. Motivated by recent experimental discoveries of hippocampal circuitry, cortical circuitry, and the diversity of inhibitory neurons throughout the brain, here we illustrate that one can construct such ...
Source: Journal of Computational Neuroscience - November 14, 2017 Category: Neuroscience Source Type: research

Transitions between asynchronous and synchronous states: a theory of correlations in small neural circuits
AbstractThe study of correlations in neural circuits of different size, from the small size of cortical microcolumns to the large-scale organization of distributed networks studied with functional imaging, is a topic of central importance to systems neuroscience. However, a theory that explains how the parameters of mesoscopic networks composed of a few tens of neurons affect the underlying correlation structure is still missing. Here we consider a theory that can be applied to networks of arbitrary size with multiple populations of homogeneous fully-connected neurons, and we focus its analysis to a case of two populations...
Source: Journal of Computational Neuroscience - November 10, 2017 Category: Neuroscience Source Type: research

Variable synaptic strengths controls the firing rate distribution in feedforward neural networks
AbstractHeterogeneity of firing rate statistics is known to have severe consequences on neural coding. Recent experimental recordings in weakly electric fish indicate that the distribution-width of superficial pyramidal cell firing rates (trial- and time-averaged) in the electrosensory lateral line lobe (ELL) depends on the stimulus, and also that network inputs can mediate changes in the firing rate distribution across the population. We previously developed theoretical methods to understand how two attributes (synaptic and intrinsic heterogeneity) interact and alter the firing rate distribution in a population of integra...
Source: Journal of Computational Neuroscience - November 10, 2017 Category: Neuroscience Source Type: research

Spiking resonances in models with the same slow resonant and fast amplifying currents but different subthreshold dynamic properties
AbstractThe generation of spiking resonances in neurons (preferred spiking responses to oscillatory inputs) requires the interplay of the intrinsic ionic currents that operate at the subthreshold voltage level and the spiking mechanisms. Combinations of the same types of ionic currents in different parameter regimes may give rise to different types of nonlinearities in the voltage equation (e.g., parabolic- and cubic-like), generating subthreshold (membrane potential) oscillations patterns with different properties. These nonlinearities are not apparent in the model equations, but can be uncovered by plotting the voltage n...
Source: Journal of Computational Neuroscience - October 24, 2017 Category: Neuroscience Source Type: research

A possible correlation between the basal ganglia motor function and the inverse kinematics calculation
AbstractThe main hypothesis of this study, based on experimental data showing the relations between the BG activities and kinematic variables, is that BG are involved in computing inverse kinematics (IK) as a part of planning and decision-making. Indeed, it is assumed that based on the desired kinematic variables (such as velocity) of a limb in the workspace, angular kinematic variables in the joint configuration space are calculated. Therefore, in this paper, a system-level computational model of BG is proposed based on geometrical rules, which is able to compute IK. Next, the functionality of each part in the presented m...
Source: Journal of Computational Neuroscience - October 23, 2017 Category: Neuroscience Source Type: research

Disrupted cholinergic modulation can underlie abnormal gamma rhythms in schizophrenia and auditory hallucination
In this study, we utilized a computational model of A1 to ask if disrupted cholinergic modulation could underlie abnormal gamma rhythms in schizophrenia. Furthermore, based on our simulation results, we propose potential pathology by which A1 can directly contribute to auditory hallucination. (Source: Journal of Computational Neuroscience)
Source: Journal of Computational Neuroscience - October 18, 2017 Category: Neuroscience Source Type: research