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Journal of Computational Neuroscience

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https://www.readbyqxmd.com/read/29327161/effects-of-channel-blocking-on-information-transmission-and-energy-efficiency-in-squid-giant-axons
#1
Yujiang Liu, Yuan Yue, Yuguo Yu, Liwei Liu, Lianchun Yu
Action 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 energy efficiency in squid giant axons...
January 11, 2018: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29230640/new-class-of-reduced-computationally-efficient-neuronal-models-for-large-scale-simulations-of-brain-dynamics
#2
Maxim Komarov, Giri Krishnan, Sylvain Chauvette, Nikolai Rulkov, Igor Timofeev, Maxim Bazhenov
During 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 dynamics depending on collective behavior in the large populations of neurons...
December 12, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29222729/coding-of-time-dependent-stimuli-in-homogeneous-and-heterogeneous-neural-populations
#3
Manuel Beiran, Alexandra Kruscha, Jan Benda, Benjamin Lindner
We compare the information transmission of a time-dependent signal by two types of uncoupled neuron populations that differ in their sources of variability: i) a homogeneous population whose units receive independent noise and ii) a deterministic heterogeneous 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 maximizes the encoding efficiency of the homogeneous and heterogeneous system, respectively, as a particular case of suprathreshold stochastic resonance...
December 8, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29210004/a-mathematical-model-of-recurrent-spreading-depolarizations
#4
Cameron Conte, Ray Lee, Monica Sarkar, David Terman
A 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...
December 5, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29192377/how-does-transient-signaling-input-affect-the-spike-timing-of-postsynaptic-neuron-near-the-threshold-regime-an-analytical-study
#5
Safura Rashid Shomali, Majid Nili Ahmadabadi, Hideaki Shimazaki, Seyyed Nader Rasuli
The 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...
December 1, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29152668/the-role-of-astrocytic-calcium-and-trpv4-channels-in-neurovascular-coupling
#6
Allanah Kenny, Michael J Plank, Tim David
Neuronal 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 vascular cells has been extended to include the glutamate induced astrocytic calcium pathway with epoxyeicosatrienoic acid (EET) signalling and the stretch dependent TRPV4 calcium channel on the astrocytic endfoot...
November 20, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29143250/cliques-and-cavities-in-the-human-connectome
#7
Ann E Sizemore, Chad Giusti, Ari Kahn, Jean M Vettel, Richard F Betzel, Danielle S Bassett
Encoding 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...
November 16, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29139050/modeling-mesoscopic-cortical-dynamics-using-a-mean-field-model-of-conductance-based-networks-of-adaptive-exponential-integrate-and-fire-neurons
#8
Yann Zerlaut, Sandrine Chemla, Frederic Chavane, Alain Destexhe
Voltage-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...
November 15, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29139049/feedforward-architectures-driven-by-inhibitory-interactions
#9
Yazan N Billeh, Michael T Schaub
Directed 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 networks even if the connectivity between the excitatory units in the system remains random...
November 14, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29124505/transitions-between-asynchronous-and-synchronous-states-a-theory-of-correlations-in-small-neural-circuits
#10
Diego Fasoli, Anna Cattani, Stefano Panzeri
The 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 of small size...
November 10, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29124504/variable-synaptic-strengths-controls-the-firing-rate-distribution-in-feedforward-neural-networks
#11
Cheng Ly, Gary Marsat
Heterogeneity 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 integrate-and-fire neurons with random recurrent coupling...
November 10, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29064059/spiking-resonances-in-models-with-the-same-slow-resonant-and-fast-amplifying-currents-but-different-subthreshold-dynamic-properties
#12
Horacio G Rotstein
The 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...
December 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29063491/a-possible-correlation-between-the-basal-ganglia-motor-function-and-the-inverse-kinematics-calculation
#13
Armin Salimi-Badr, Mohammad Mehdi Ebadzadeh, Christian Darlot
The 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...
December 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29047010/disrupted-cholinergic-modulation-can-underlie-abnormal-gamma-rhythms-in-schizophrenia-and-auditory-hallucination
#14
Jung Hoon Lee
The pathophysiology of auditory hallucination, a common symptom of schizophrenia, has yet been understood, but during auditory hallucination, primary auditory cortex (A1) shows paradoxical responses. When auditory stimuli are absent, A1 becomes hyperactive, while A1 responses to auditory stimuli are reduced. Such activation pattern of A1 responses during auditory hallucination is consistent with aberrant gamma rhythms in schizophrenia observed during auditory tasks, raising the possibility that the pathology underlying abnormal gamma rhythms can account for auditory hallucination...
December 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/29027605/short-term-depression-and-transient-memory-in-sensory-cortex
#15
Grant Gillary, Rüdiger von der Heydt, Ernst Niebur
Persistent neuronal activity is usually studied in the context of short-term memory localized in central cortical areas. Recent studies show that early sensory areas also can have persistent representations of stimuli which emerge quickly (over tens of milliseconds) and decay slowly (over seconds). Traditional positive feedback models cannot explain sensory persistence for at least two reasons: (i) They show attractor dynamics, with transient perturbations resulting in a quasi-permanent change of system state, whereas sensory systems return to the original state after a transient...
December 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28939929/stimulus-induced-transitions-between-spike-wave-discharges-and-spindles-with-the-modulation-of-thalamic-reticular-nucleus
#16
Denggui Fan, Qingyun Wang, Jianzhong Su, Hongguang Xi
It is believed that thalamic reticular nucleus (TRN) controls spindles and spike-wave discharges (SWD) in seizure or sleeping processes. The dynamical mechanisms of spatiotemporal evolutions between these two types of activity, however, are not well understood. In light of this, we first use a single-compartment thalamocortical neural field model to investigate the effects of TRN on occurrence of SWD and its transition. Results show that the increasing inhibition from TRN to specific relay nuclei (SRN) can lead to the transition of system from SWD to slow-wave oscillation...
December 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28924628/a-recurrent-neural-model-for-proto-object-based-contour-integration-and-figure-ground-segregation
#17
Brian Hu, Ernst Niebur
Visual processing of objects makes use of both feedforward and feedback streams of information. However, the nature of feedback signals is largely unknown, as is the identity of the neuronal populations in lower visual areas that receive them. Here, we develop a recurrent neural model to address these questions in the context of contour integration and figure-ground segregation. A key feature of our model is the use of grouping neurons whose activity represents tentative objects ("proto-objects") based on the integration of local feature information...
December 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28791522/pre-processing-and-transfer-entropy-measures-in-motor-neurons-controlling-limb-movements
#18
Fernando P Santos, Carlos D Maciel, Philip L Newland
Directed information transfer measures are increasingly being employed in modeling neural system behavior due to their model-free approach, applicability to nonlinear and stochastic signals, and the potential to integrate repetitions of an experiment. Intracellular physiological recordings of graded synaptic potentials provide a number of additional challenges compared to spike signals due to non-stationary behaviour generated through extrinsic processes. We therefore propose a method to overcome this difficulty by using a preprocessing step based on Singular Spectrum Analysis (SSA) to remove nonlinear trends and discontinuities...
October 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28748303/a-mean-field-model-for-movement-induced-changes-in-the-beta-rhythm
#19
Áine Byrne, Matthew J Brookes, Stephen Coombes
In electrophysiological recordings of the brain, the transition from high amplitude to low amplitude signals are most likely caused by a change in the synchrony of underlying neuronal population firing patterns. Classic examples of such modulations are the strong stimulus-related oscillatory phenomena known as the movement related beta decrease (MRBD) and post-movement beta rebound (PMBR). A sharp decrease in neural oscillatory power is observed during movement (MRBD) followed by an increase above baseline on movement cessation (PMBR)...
October 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28660531/decision-making-neural-circuits-mediating-social-behaviors-an-attractor-network-model
#20
Julián Hurtado-López, David F Ramirez-Moreno, Terrence J Sejnowski
We propose a mathematical model of a continuous attractor network that controls social behaviors. The model is examined with bifurcation analysis and computer simulations. The results show that the model exhibits stable steady states and thresholds for steady state transitions corresponding to some experimentally observed behaviors, such as aggression control. The performance of the model and the relation with experimental evidence are discussed.
October 2017: Journal of Computational Neuroscience
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