Disinhibition-Induced Delayed Onset of Epileptic Spike-Wave Discharges in a Five Variable Model of Cortex and Thalamus.

Abstract:

:Based on a modified neural field network model composed of cortex and thalamus, we here propose a computational framework to investigate the onset control of absence seizure, which is characterized by the spike-wave discharges. Firstly, we briefly demonstrate the existence of various transition types in Taylor's model by increasing the thalamic input. Furthermore, after the disinhibitory function is reasonably introduced into the Taylor's model, we can observe the occurrence of various transition states of firing patterns with different dominant frequencies as the thalamic input is varied under different disinhibitory effects onto the pyramidal neural population. Interestingly, it is found that the onset of spike-wave discharges can be delayed as the disinhibitory input is considered. More importantly, we explore bifurcation mechanism of firing transitions as some key parameters are changed. And also, we observe other dynamical states, such as simple oscillations and saturated discharges with different spatial scales, which are consistent with previous theoretical or experimental findings.

journal_name

Front Comput Neurosci

authors

Liu S,Wang Q,Fan D

doi

10.3389/fncom.2016.00028

subject

Has Abstract

pub_date

2016-04-05 00:00:00

pages

28

issn

1662-5188

journal_volume

10

pub_type

杂志文章
  • A high-capacity model for one shot association learning in the brain.

    abstract::We present a high-capacity model for one-shot association learning (hetero-associative memory) in sparse networks. We assume that basic patterns are pre-learned in networks and associations between two patterns are presented only once and have to be learned immediately. The model is a combination of an Amit-Fusi like ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2014.00140

    authors: Einarsson H,Lengler J,Steger A

    更新日期:2014-11-07 00:00:00

  • Population coding of visual space: comparison of spatial representations in dorsal and ventral pathways.

    abstract::Although the representation of space is as fundamental to visual processing as the representation of shape, it has received relatively little attention from neurophysiological investigations. In this study we characterize representations of space within visual cortex, and examine how they differ in a first direct comp...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2010.00159

    authors: Sereno AB,Lehky SR

    更新日期:2011-02-01 00:00:00

  • Learning Generative State Space Models for Active Inference.

    abstract::In this paper we investigate the active inference framework as a means to enable autonomous behavior in artificial agents. Active inference is a theoretical framework underpinning the way organisms act and observe in the real world. In active inference, agents act in order to minimize their so called free energy, or p...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2020.574372

    authors: Çatal O,Wauthier S,De Boom C,Verbelen T,Dhoedt B

    更新日期:2020-11-16 00:00:00

  • Multiple Frequency Bands Analysis of Large Scale Intrinsic Brain Networks and Its Application in Schizotypal Personality Disorder.

    abstract::The human brain is a complex system composed by several large scale intrinsic networks with distinct functions. The low frequency oscillation (LFO) signal of blood oxygen level dependent (BOLD), measured through resting-state fMRI, reflects the spontaneous neural activity of these networks. We propose to characterize ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2018.00064

    authors: Qi S,Gao Q,Shen J,Teng Y,Xie X,Sun Y,Wu J

    更新日期:2018-08-03 00:00:00

  • Higher-order correlations in non-stationary parallel spike trains: statistical modeling and inference.

    abstract::The extent to which groups of neurons exhibit higher-order correlations in their spiking activity is a controversial issue in current brain research. A major difficulty is that currently available tools for the analysis of massively parallel spike trains (N >10) for higher-order correlations typically require vast sam...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2010.00016

    authors: Staude B,Grün S,Rotter S

    更新日期:2010-07-02 00:00:00

  • Invariant object recognition based on extended fragments.

    abstract::Visual appearance of natural objects is profoundly affected by viewing conditions such as viewpoint and illumination. Human subjects can nevertheless compensate well for variations in these viewing conditions. The strategies that the visual system uses to accomplish this are largely unclear. Previous computational stu...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2012.00056

    authors: Bart E,Hegdé J

    更新日期:2012-08-24 00:00:00

  • Quantized response times are a signature of a neuronal bottleneck in decision.

    abstract::The histograms of response times of optimal YES/NO decisions that are computed from a single sensory Poisson neuron are highly structured. In particular, response times in NO decisions are quantized to a small set of times, while response times in YES decisions have a multimodal structure. Both the times of NO decisio...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2014.00042

    authors: Perona P

    更新日期:2014-04-11 00:00:00

  • Nine criteria for a measure of scientific output.

    abstract::Scientific research produces new knowledge, technologies, and clinical treatments that can lead to enormous returns. Often, the path from basic research to new paradigms and direct impact on society takes time. Precise quantification of scientific output in the short-term is not an easy task but is critical for evalua...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2011.00048

    authors: Kreiman G,Maunsell JH

    更新日期:2011-11-10 00:00:00

  • Alterations of Muscle Synergies During Voluntary Arm Reaching Movement in Subacute Stroke Survivors at Different Levels of Impairment.

    abstract::Motor system uses muscle synergies as a modular organization to simplify the control of movements. Motor cortical impairments, such as stroke and spinal cord injuries, disrupt the orchestration of the muscle synergies and result in abnormal movements. In this paper, the alterations of muscle synergies in subacute stro...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2018.00069

    authors: Pan B,Sun Y,Xie B,Huang Z,Wu J,Hou J,Liu Y,Huang Z,Zhang Z

    更新日期:2018-08-21 00:00:00

  • Structural Plasticity Denoises Responses and Improves Learning Speed.

    abstract::Despite an abundance of computational models for learning of synaptic weights, there has been relatively little research on structural plasticity, i.e., the creation and elimination of synapses. Especially, it is not clear how structural plasticity works in concert with spike-timing-dependent plasticity (STDP) and wha...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2016.00093

    authors: Spiess R,George R,Cook M,Diehl PU

    更新日期:2016-09-08 00:00:00

  • Examining Brain Morphometry Associated with Self-Esteem in Young Adults Using Multilevel-ROI-Features-Based Classification Method.

    abstract::Purpose: This study is to exam self-esteem related brain morphometry on brain magnetic resonance (MR) images using multilevel-features-based classification method. Method: The multilevel region of interest (ROI) features consist of two types of features: (i) ROI features, which include gray matter volume, white matter...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2017.00037

    authors: Peng B,Lu J,Saxena A,Zhou Z,Zhang T,Wang S,Dai Y

    更新日期:2017-05-22 00:00:00

  • Synaptic encoding of temporal contiguity.

    abstract::Often we need to perform tasks in an environment that changes stochastically. In these situations it is important to learn the statistics of sequences of events in order to predict the future and the outcome of our actions. The statistical description of many of these sequences can be reduced to the set of probabiliti...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2013.00032

    authors: Ostojic S,Fusi S

    更新日期:2013-04-12 00:00:00

  • Brain Network Analysis and Classification Based on Convolutional Neural Network.

    abstract::Background: Convolution neural networks (CNN) is increasingly used in computer science and finds more and more applications in different fields. However, analyzing brain network with CNN is not trivial, due to the non-Euclidean characteristics of brain network built by graph theory. Method: To address this problem, we...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2018.00095

    authors: Meng L,Xiang J

    更新日期:2018-12-10 00:00:00

  • Stability constraints on large-scale structural brain networks.

    abstract::Stability is an important dynamical property of complex systems and underpins a broad range of coherent self-organized behavior. Based on evidence that some neurological disorders correspond to linear instabilities, we hypothesize that stability constrains the brain's electrical activity and influences its structure a...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2013.00031

    authors: Gray RT,Robinson PA

    更新日期:2013-04-12 00:00:00

  • Classification of EEG Signals Based on Pattern Recognition Approach.

    abstract::Feature extraction is an important step in the process of electroencephalogram (EEG) signal classification. The authors propose a "pattern recognition" approach that discriminates EEG signals recorded during different cognitive conditions. Wavelet based feature extraction such as, multi-resolution decompositions into ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2017.00103

    authors: Amin HU,Mumtaz W,Subhani AR,Saad MNM,Malik AS

    更新日期:2017-11-21 00:00:00

  • Deep networks for motor control functions.

    abstract::The motor system generates time-varying commands to move our limbs and body. Conventional descriptions of motor control and learning rely on dynamical representations of our body's state (forward and inverse models), and control policies that must be integrated forward to generate feedforward time-varying commands; th...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2015.00032

    authors: Berniker M,Kording KP

    更新日期:2015-03-19 00:00:00

  • Synaptic bouton properties are tuned to best fit the prevailing firing pattern.

    abstract::The morphology of presynaptic specializations can vary greatly ranging from classical single-release-site boutons in the central nervous system to boutons of various sizes harboring multiple vesicle release sites. Multi-release-site boutons can be found in several neural contexts, for example at the neuromuscular junc...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2014.00101

    authors: Knodel MM,Geiger R,Ge L,Bucher D,Grillo A,Wittum G,Schuster CM,Queisser G

    更新日期:2014-09-09 00:00:00

  • Probabilistic inference of short-term synaptic plasticity in neocortical microcircuits.

    abstract::Short-term synaptic plasticity is highly diverse across brain area, cortical layer, cell type, and developmental stage. Since short-term plasticity (STP) strongly shapes neural dynamics, this diversity suggests a specific and essential role in neural information processing. Therefore, a correct characterization of sho...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2013.00075

    authors: Costa RP,Sjöström PJ,van Rossum MC

    更新日期:2013-06-06 00:00:00

  • A network that performs brute-force conversion of a temporal sequence to a spatial pattern: relevance to odor recognition.

    abstract::A classic problem in neuroscience is how temporal sequences (TSs) can be recognized. This problem is exemplified in the olfactory system, where an odor is defined by the TS of olfactory bulb (OB) output that occurs during a sniff. This sequence is discrete because the output is subdivided by gamma frequency oscillatio...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2014.00108

    authors: Sanders H,Kolterman BE,Shusterman R,Rinberg D,Koulakov A,Lisman J

    更新日期:2014-09-17 00:00:00

  • Information diversity in structure and dynamics of simulated neuronal networks.

    abstract::Neuronal networks exhibit a wide diversity of structures, which contributes to the diversity of the dynamics therein. The presented work applies an information theoretic framework to simultaneously analyze structure and dynamics in neuronal networks. Information diversity within the structure and dynamics of a neurona...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2011.00026

    authors: Mäki-Marttunen T,Aćimović J,Nykter M,Kesseli J,Ruohonen K,Yli-Harja O,Linne ML

    更新日期:2011-06-01 00:00:00

  • On the dynamics of cortical development: synchrony and synaptic self-organization.

    abstract::We describe a model for cortical development that resolves long-standing difficulties of earlier models. It is proposed that, during embryonic development, synchronous firing of neurons and their competition for limited metabolic resources leads to selection of an array of neurons with ultra-small-world characteristic...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2013.00004

    authors: Wright JJ,Bourke PD

    更新日期:2013-02-15 00:00:00

  • Causal Role of Thalamic Interneurons in Brain State Transitions: A Study Using a Neural Mass Model Implementing Synaptic Kinetics.

    abstract::Experimental studies on the Lateral Geniculate Nucleus (LGN) of mammals and rodents show that the inhibitory interneurons (IN) receive around 47.1% of their afferents from the retinal spiking neurons, and constitute around 20-25% of the LGN cell population. However, there is a definite gap in knowledge about the role ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2016.00115

    authors: Bhattacharya BS,Bond TP,O'Hare L,Turner D,Durrant SJ

    更新日期:2016-11-16 00:00:00

  • An Approximation to the Adaptive Exponential Integrate-and-Fire Neuron Model Allows Fast and Predictive Fitting to Physiological Data.

    abstract::For large-scale network simulations, it is often desirable to have computationally tractable, yet in a defined sense still physiologically valid neuron models. In particular, these models should be able to reproduce physiological measurements, ideally in a predictive sense, and under different input regimes in which n...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2012.00062

    authors: Hertäg L,Hass J,Golovko T,Durstewitz D

    更新日期:2012-09-06 00:00:00

  • Interareal coupling reduces encoding variability in multi-area models of spatial working memory.

    abstract::Persistent activity observed during delayed-response tasks for spatial working memory (Funahashi et al., 1989) has commonly been modeled by recurrent networks whose dynamics is described as a bump attractor (Compte et al., 2000). We examine the effects of interareal architecture on the dynamics of bump attractors in s...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2013.00082

    authors: Kilpatrick ZP

    更新日期:2013-07-01 00:00:00

  • Revealing the Computational Meaning of Neocortical Interarea Signals.

    abstract::To understand the function of the neocortex, which is a hierarchical distributed network, it is useful giving meaning to the signals transmitted between these areas from the computational viewpoint. The overall anatomical structure or organs related to this network, including the neocortex, thalamus, and basal ganglia...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2020.00074

    authors: Yamakawa H

    更新日期:2020-08-18 00:00:00

  • Differing effects of attention in single-units and populations are well predicted by heterogeneous tuning and the normalization model of attention.

    abstract::Single-unit measurements have reported many different effects of attention on contrast-response (e.g., contrast-gain, response-gain, additive-offset dependent on visibility), while functional imaging measurements have more uniformly reported increases in response across all contrasts (additive-offset). The normalizati...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2014.00012

    authors: Hara Y,Pestilli F,Gardner JL

    更新日期:2014-02-19 00:00:00

  • Deep Learning-Based Concurrent Brain Registration and Tumor Segmentation.

    abstract::Image registration and segmentation are the two most studied problems in medical image analysis. Deep learning algorithms have recently gained a lot of attention due to their success and state-of-the-art results in variety of problems and communities. In this paper, we propose a novel, efficient, and multi-task algori...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2020.00017

    authors: Estienne T,Lerousseau M,Vakalopoulou M,Alvarez Andres E,Battistella E,Carré A,Chandra S,Christodoulidis S,Sahasrabudhe M,Sun R,Robert C,Talbot H,Paragios N,Deutsch E

    更新日期:2020-03-20 00:00:00

  • Neuronal Degeneration Impairs Rhythms Between Connected Microcircuits.

    abstract::Synchronization of neural activity across brain regions is critical to processes that include perception, learning, and memory. After traumatic brain injury (TBI), neuronal degeneration is one possible effect and can alter communication between neural circuits. Consequently, synchronization between neurons may change ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2020.00018

    authors: Schumm SN,Gabrieli D,Meaney DF

    更新日期:2020-03-03 00:00:00

  • Short-Term Facilitation may Stabilize Parametric Working Memory Trace.

    abstract::Networks with continuous set of attractors are considered to be a paradigmatic model for parametric working memory (WM), but require fine tuning of connections and are thus structurally unstable. Here we analyzed the network with ring attractor, where connections are not perfectly tuned and the activity state therefor...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2011.00040

    authors: Itskov V,Hansel D,Tsodyks M

    更新日期:2011-10-24 00:00:00

  • Effects of Adaptation on Discrimination of Whisker Deflection Velocity and Angular Direction in a Model of the Barrel Cortex.

    abstract::Two important stimulus features represented within the rodent barrel cortex are velocity and angular direction of whisker deflection. Each cortical barrel receives information from thalamocortical (TC) cells that relay information from a single whisker, and TC input is decoded by barrel regular-spiking (RS) cells thro...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2018.00045

    authors: Patel MJ

    更新日期:2018-06-12 00:00:00