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Journal of Computational Neuroscience

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https://www.readbyqxmd.com/read/28643213/the-difficult-legacy-of-turing-s-wager
#1
Andrew Thwaites, Andrew Soltan, Eric Wieser, Ian Nimmo-Smith
Describing the human brain in mathematical terms is an important ambition of neuroscience research, yet the challenges remain considerable. It was Alan Turing, writing in 1950, who first sought to demonstrate how time-consuming such an undertaking would be. Through analogy to the computer program, Turing argued that arriving at a complete mathematical description of the mind would take well over a thousand years. In this opinion piece, we argue that - despite seventy years of progress in the field - his arguments remain both prescient and persuasive...
June 22, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28616843/intermittency-in-the-hodgkin-huxley-model
#2
Gaspar Cano, Rui Dilão
We show that action potentials in the Hodgkin-Huxley neuron model result from a type I intermittency phenomenon that occurs in the proximity of a saddle-node bifurcation of limit cycles. For the Hodgkin-Huxley spatially extended model, describing propagation of action potential along axons, we show the existence of type I intermittency and a new type of chaotic intermittency, as well as space propagating regular and chaotic diffusion waves. Chaotic intermittency occurs in the transition from a turbulent regime to the resting regime of the transmembrane potential and is characterised by the existence of a sequence of action potential spikes occurring at irregular time intervals...
June 14, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28585050/exact-analytical-results-for-integrate-and-fire-neurons-driven-by-excitatory-shot-noise
#3
Felix Droste, Benjamin Lindner
A neuron receives input from other neurons via electrical pulses, so-called spikes. The pulse-like nature of the input is frequently neglected in analytical studies; instead, the input is usually approximated to be Gaussian. Recent experimental studies have shown, however, that an assumption underlying this approximation is often not met: Individual presynaptic spikes can have a significant effect on a neuron's dynamics. It is thus desirable to explicitly account for the pulse-like nature of neural input, i...
June 6, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28573354/optimal-feedback-control-to-describe-multiple-representations-of-primary-motor-cortex-neurons
#4
Yuki Ueyama
Primary motor cortex (M1) neurons are tuned in response to several parameters related to motor control, and it was recently reported that M1 is important in feedback control. However, it remains unclear how M1 neurons encode information to control the musculoskeletal system. In this study, we examined the underlying computational mechanisms of M1 based on optimal feedback control (OFC) theory, which is a plausible hypothesis for neuromotor control. We modelled an isometric torque production task that required joint torque to be regulated and maintained at desired levels in a musculoskeletal system physically constrained by muscles, which act by pulling rather than pushing...
June 1, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28569367/resonance-modulation-annihilation-and-generation-of-anti-resonance-and-anti-phasonance-in-3d-neuronal-systems-interplay-of-resonant-and-amplifying-currents-with-slow-dynamics
#5
Horacio G Rotstein
Subthreshold (membrane potential) resonance and phasonance (preferred amplitude and zero-phase responses to oscillatory inputs) in single neurons arise from the interaction between positive and negative feedback effects provided by relatively fast amplifying currents and slower resonant currents. In 2D neuronal systems, amplifying currents are required to be slave to voltage (instantaneously fast) for these phenomena to occur. In higher dimensional systems, additional currents operating at various effective time scales may modulate and annihilate existing resonances and generate antiresonance (minimum amplitude response) and antiphasonance (zero-phase response with phase monotonic properties opposite to phasonance)...
May 31, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28528529/the-influence-of-depolarization-block-on-seizure-like-activity-in-networks-of-excitatory-and-inhibitory-neurons
#6
Christopher M Kim, Duane Q Nykamp
The inhibitory restraint necessary to suppress aberrant activity can fail when inhibitory neurons cease to generate action potentials as they enter depolarization block. We investigate possible bifurcation structures that arise at the onset of seizure-like activity resulting from depolarization block in inhibitory neurons. Networks of conductance-based excitatory and inhibitory neurons are simulated to characterize different types of transitions to the seizure state, and a mean field model is developed to verify the generality of the observed phenomena of excitatory-inhibitory dynamics...
May 20, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28509116/tonic-regulation-of-stationary-asynchronous-firing-of-a-neural-network
#7
D A Adamchik, V B Kazantsev
The impact of tonic conductance upon population activity was investigated. An extra tonic transmembrane current through GABA-activated extrasynaptic GABA A -receptors was found to control stationary asynchronous firing both quantitatively and qualitatively. Quantitative regulation consisted in alterating a current level of stationary population activity while qualitative regulation manifested itself in appearance of resilient asynchronous spiking in case GABA reversal potential exceeded a certain threshold...
May 16, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28484899/functional-connectivity-models-for-decoding-of-spatial-representations-from-hippocampal-ca1-recordings
#8
Lorenzo Posani, Simona Cocco, Karel Ježek, Rémi Monasson
Hippocampus stores spatial representations, or maps, which are recalled each time a subject is placed in the corresponding environment. Across different environments of similar geometry, these representations show strong orthogonality in CA3 of hippocampus, whereas in the CA1 subfield a considerable overlap between the maps can be seen. The lower orthogonality decreases reliability of various decoders developed in an attempt to identify which of the stored maps is active at the moment. Especially, the problem with decoding emerges with a need to analyze data at high temporal resolution...
May 8, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28434057/predictive-control-of-intersegmental-tarsal-movements-in-an-insect
#9
Alicia Costalago-Meruelo, David M Simpson, Sandor M Veres, Philip L Newland
In many animals intersegmental reflexes are important for postural and movement control but are still poorly undesrtood. Mathematical methods can be used to model the responses to stimulation, and thus go beyond a simple description of responses to specific inputs. Here we analyse an intersegmental reflex of the foot (tarsus) of the locust hind leg, which raises the tarsus when the tibia is flexed and depresses it when the tibia is extended. A novel method is described to measure and quantify the intersegmental responses of the tarsus to a stimulus to the femoro-tibial chordotonal organ...
April 22, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28389715/neural-field-model-of-seizure-like-activity-in-isolated-cortex
#10
X Zhao, P A Robinson
Epileptiform discharges on an isolated cortex are explored using neural field theory. A neural field model of the isolated cortex is used that consists of three neural populations, excitatory, inhibitory, and excitatory bursting. Mechanisms by which an isolated cortex gives rise to seizure-like waveforms thought to underly pathological EEG waveforms on the deafferented cortex are explored. It is shown that the model reproduces similar time series and oscillatory frequencies for paroxysmal discharges when compared with physiological recordings both during acute and chronic deafferentation states...
April 7, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28393281/reaction-time-impairments-in-decision-making-networks-as-a-diagnostic-marker-for-traumatic-brain-injuries-and-neurological-diseases
#11
Pedro D Maia, J Nathan Kutz
The presence of diffuse Focal Axonal Swellings (FAS) is a hallmark cellular feature in many neurological diseases and traumatic brain injury. Among other things, the FAS have a significant impact on spike-train encodings that propagate through the affected neurons, leading to compromised signal processing on a neuronal network level. This work merges, for the first time, three fields of study: (i) signal processing in excitatory-inhibitory (EI) networks of neurons via population codes, (ii) decision-making theory driven by the production of evidence from stimulus, and (iii) compromised spike-train propagation through FAS...
June 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28389716/multirate-method-for-co-simulation-of-electrical-chemical-systems-in-multiscale-modeling
#12
Ekaterina Brocke, Mikael Djurfeldt, Upinder S Bhalla, Jeanette Hellgren Kotaleski, Michael Hanke
Multiscale modeling by means of co-simulation is a powerful tool to address many vital questions in neuroscience. It can for example be applied in the study of the process of learning and memory formation in the brain. At the same time the co-simulation technique makes it possible to take advantage of interoperability between existing tools and multi-physics models as well as distributed computing. However, the theoretical basis for multiscale modeling is not sufficiently understood. There is, for example, a need of efficient and accurate numerical methods for time integration...
June 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28367595/ionic-currents-influencing-spontaneous-firing-and-pacemaker-frequency-in-dopamine-neurons-of-the-ventrolateral-periaqueductal-gray-and-dorsal-raphe-nucleus-vlpag-drn-a-voltage-clamp-and-computational-modelling-study
#13
Antonios G Dougalis, Gillian A C Matthews, Birgit Liss, Mark A Ungless
Dopamine (DA) neurons of the ventrolateral periaqueductal gray (vlPAG) and dorsal raphe nucleus (DRN) fire spontaneous action potentials (APs) at slow, regular patterns in vitro but a detailed account of their intrinsic membrane properties responsible for spontaneous firing is currently lacking. To resolve this, we performed a voltage-clamp electrophysiological study in brain slices to describe their major ionic currents and then constructed a computer model and used simulations to understand the mechanisms behind autorhythmicity in silico...
June 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28353176/mathematical-investigation-of-ip3-dependent-calcium-dynamics-in-astrocytes
#14
Gregory Handy, Marsa Taheri, John A White, Alla Borisyuk
We study evoked calcium dynamics in astrocytes, a major cell type in the mammalian brain. Experimental evidence has shown that such dynamics are highly variable between different trials, cells, and cell subcompartments. Here we present a qualitative analysis of a recent mathematical model of astrocyte calcium responses. We show how the major response types are generated in the model as a result of the underlying bifurcation structure. By varying key channel parameters, mimicking blockers used by experimentalists, we manipulate this underlying bifurcation structure and predict how the distributions of responses can change...
June 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/27778248/analysis-of-the-dynamics-of-temporal-relationships-of-neural-activities-using-optical-imaging-data
#15
Jannetta S Steyn, Peter Andras
The temporal relationship between the activities of neurons in biological neural systems is critically important for the correct delivery of the functionality of these systems. Fine measurement of temporal relationships of neural activities using micro-electrodes is possible but this approach is very limited due to spatial constraints in the context of physiologically valid settings of neural systems. Optical imaging with voltage-sensitive dyes or calcium dyes can provide data about the activity patterns of many neurons in physiologically valid settings, but the data is relatively noisy...
April 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28271301/mechanisms-of-circumferential-gyral-convolution-in-primate-brains
#16
Tuo Zhang, Mir Jalil Razavi, Hanbo Chen, Yujie Li, Xiao Li, Longchuan Li, Lei Guo, Xiaoping Hu, Tianming Liu, Xianqiao Wang
Mammalian cerebral cortices are characterized by elaborate convolutions. Radial convolutions exhibit homology across primate species and generally are easily identified in individuals of the same species. In contrast, circumferential convolutions vary across species as well as individuals of the same species. However, systematic study of circumferential convolution patterns is lacking. To address this issue, we utilized structural MRI (sMRI) and diffusion MRI (dMRI) data from primate brains. We quantified cortical thickness and circumferential convolutions on gyral banks in relation to axonal pathways and density along the gray matter/white matter boundaries...
March 7, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/28236135/deriving-theoretical-phase-locking-values-of-a-coupled-cortico-thalamic-neural-mass-model-using-center-manifold-reduction
#17
Yutaro Ogawa, Ikuhiro Yamaguchi, Kiyoshi Kotani, Yasuhiko Jimbo
Cognitive functions such as sensory processing and memory processes lead to phase synchronization in the electroencephalogram or local field potential between different brain regions. There are a lot of computational researches deriving phase locking values (PLVs), which are an index of phase synchronization intensity, from neural models. However, these researches derive PLVs numerically. To the best of our knowledge, there have been no reports on the derivation of a theoretical PLV. In this study, we propose an analytical method for deriving theoretical PLVs from a cortico-thalamic neural mass model described by a delay differential equation...
February 24, 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/27812835/anti-correlations-in-the-degree-distribution-increase-stimulus-detection-performance-in-noisy-spiking-neural-networks
#18
Marijn B Martens, Arthur R Houweling, Paul H E Tiesinga
Neuronal circuits in the rodent barrel cortex are characterized by stable low firing rates. However, recent experiments show that short spike trains elicited by electrical stimulation in single neurons can induce behavioral responses. Hence, the underlying neural networks provide stability against internal fluctuations in the firing rate, while simultaneously making the circuits sensitive to small external perturbations. Here we studied whether stability and sensitivity are affected by the connectivity structure in recurrently connected spiking networks...
February 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/27726048/hierarchical-winner-take-all-particle-swarm-optimization-social-network-for-neural-model-fitting
#19
Brandon S Coventry, Aravindakshan Parthasarathy, Alexandra L Sommer, Edward L Bartlett
Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons...
February 2017: Journal of Computational Neuroscience
https://www.readbyqxmd.com/read/27714569/optimal-nonlinear-cue-integration-for-sound-localization
#20
Brian J Fischer, Jose Luis Peña
Integration of multiple sensory cues can improve performance in detection and estimation tasks. There is an open theoretical question of the conditions under which linear or nonlinear cue combination is Bayes-optimal. We demonstrate that a neural population decoded by a population vector requires nonlinear cue combination to approximate Bayesian inference. Specifically, if cues are conditionally independent, multiplicative cue combination is optimal for the population vector. The model was tested on neural and behavioral responses in the barn owl's sound localization system where space-specific neurons owe their selectivity to multiplicative tuning to sound localization cues interaural phase (IPD) and level (ILD) differences...
February 2017: Journal of Computational Neuroscience
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