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 used a famous algorithm "word2vec" from the field of natural language processing (NLP), to represent the vertexes of graph in the node embedding space, and transform the brain network into images, which can bridge the gap between brain network and CNN. Using this model, we analyze and classify the brain network from Magnetoencephalography (MEG) data into two categories: normal controls and patients with migraine. Results: In the experiments, we applied our method on the clinical MEG dataset, and got the mean classification accuracy rate 81.25%. Conclusions: These results indicate that our method can feasibly analyze and classify the brain network, and all the abundant resources of CNN can be used on the analysis of brain network.

journal_name

Front Comput Neurosci

authors

Meng L,Xiang J

doi

10.3389/fncom.2018.00095

subject

Has Abstract

pub_date

2018-12-10 00:00:00

pages

95

issn

1662-5188

journal_volume

12

pub_type

杂志文章
  • 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

  • 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

  • Combined Effects of Feedforward Inhibition and Excitation in Thalamocortical Circuit on the Transitions of Epileptic Seizures.

    abstract::The mechanisms underlying electrophysiologically observed two-way transitions between absence and tonic-clonic epileptic seizures in cerebral cortex remain unknown. The interplay within thalamocortical network is believed to give rise to these epileptic multiple modes of activity and transitions between them. In parti...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2017.00059

    authors: Fan D,Duan L,Wang Q,Luan G

    更新日期:2017-07-07 00:00:00

  • Anisotropic connectivity implements motion-based prediction in a spiking neural network.

    abstract::Predictive coding hypothesizes that the brain explicitly infers upcoming sensory input to establish a coherent representation of the world. Although it is becoming generally accepted, it is not clear on which level spiking neural networks may implement predictive coding and what function their connectivity may have. W...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2013.00112

    authors: Kaplan BA,Lansner A,Masson GS,Perrinet LU

    更新日期:2013-09-17 00:00:00

  • Density Visualization Pipeline: A Tool for Cellular and Network Density Visualization and Analysis.

    abstract::Neuron classification is an important component in analyzing network structure and quantifying the effect of neuron topology on signal processing. Current quantification and classification approaches rely on morphology projection onto lower-dimensional spaces. In this paper a 3D visualization and quantification tool i...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2020.00042

    authors: Grein S,Qi G,Queisser G

    更新日期:2020-06-26 00:00:00

  • The Effects of Capillary Transit Time Heterogeneity (CTH) on the Cerebral Uptake of Glucose and Glucose Analogs: Application to FDG and Comparison to Oxygen Uptake.

    abstract::Glucose is the brain's principal source of ATP, but the extent to which cerebral glucose consumption (CMRglc) is coupled with its oxygen consumption (CMRO2) remains unclear. Measurements of the brain's oxygen-glucose index OGI = CMRO2/CMRglc suggest that its oxygen uptake largely suffices for oxidative phosphorylation...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2016.00103

    authors: Angleys H,Jespersen SN,Østergaard L

    更新日期:2016-10-13 00:00:00

  • Anti-kindling Induced by Two-Stage Coordinated Reset Stimulation with Weak Onset Intensity.

    abstract::Abnormal neuronal synchrony plays an important role in a number of brain diseases. To specifically counteract abnormal neuronal synchrony by desynchronization, Coordinated Reset (CR) stimulation, a spatiotemporally patterned stimulation technique, was designed with computational means. In neuronal networks with spike ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2016.00044

    authors: Zeitler M,Tass PA

    更新日期:2016-05-17 00:00:00

  • Comparative Analysis of Behavioral Models for Adaptive Learning in Changing Environments.

    abstract::Probabilistic models of decision making under various forms of uncertainty have been applied in recent years to numerous behavioral and model-based fMRI studies. These studies were highly successful in enabling a better understanding of behavior and delineating the functional properties of brain areas involved in deci...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2016.00033

    authors: Marković D,Kiebel SJ

    更新日期:2016-04-20 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

  • A Computational Model of Interactions Between Neuronal and Astrocytic Networks: The Role of Astrocytes in the Stability of the Neuronal Firing Rate.

    abstract::Recent research in neuroscience indicates the importance of tripartite synapses and gliotransmission mediated by astrocytes in neuronal system modulation. Although the astrocyte and neuronal network functions are interrelated, they are fundamentally different in their signaling patterns and, possibly, the time scales ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2019.00092

    authors: Lenk K,Satuvuori E,Lallouette J,Ladrón-de-Guevara A,Berry H,Hyttinen JAK

    更新日期:2020-01-22 00:00:00

  • A Role for Electrotonic Coupling Between Cortical Pyramidal Cells.

    abstract::Many brain regions communicate information through synchronized network activity. Electrical coupling among the dendrites of interneurons in the cortex has been implicated in forming and sustaining such activity in the cortex. Evidence for the existence of electrical coupling among cortical pyramidal cells, however, h...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2019.00033

    authors: Crodelle J,Zhou D,Kovačič G,Cai D

    更新日期:2019-05-28 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

  • Model-Based Comparison of Deep Brain Stimulation Array Functionality with Varying Number of Radial Electrodes and Machine Learning Feature Sets.

    abstract::Deep brain stimulation (DBS) leads with radially distributed electrodes have potential to improve clinical outcomes through more selective targeting of pathways and networks within the brain. However, increasing the number of electrodes on clinical DBS leads by replacing conventional cylindrical shell electrodes with ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2016.00058

    authors: Teplitzky BA,Zitella LM,Xiao Y,Johnson MD

    更新日期:2016-06-10 00:00:00

  • Transition Dynamics of a Dentate Gyrus-CA3 Neuronal Network during Temporal Lobe Epilepsy.

    abstract::In temporal lobe epilepsy (TLE), the variation of chemical receptor expression underlies the basis of neural network activity shifts, resulting in neuronal hyperexcitability and epileptiform discharges. However, dynamical mechanisms involved in the transitions of TLE are not fully understood, because of the neuronal d...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2017.00061

    authors: Zhang L,Fan D,Wang Q

    更新日期:2017-07-11 00:00:00

  • Neural circuits for peristaltic wave propagation in crawling Drosophila larvae: analysis and modeling.

    abstract::Drosophila larvae crawl by peristaltic waves of muscle contractions, which propagate along the animal body and involve the simultaneous contraction of the left and right side of each segment. Coordinated propagation of contraction does not require sensory input, suggesting that movement is generated by a central patte...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2013.00024

    authors: Gjorgjieva J,Berni J,Evers JF,Eglen SJ

    更新日期:2013-04-04 00:00:00

  • Topological View of Flows Inside the BOLD Spontaneous Activity of the Human Brain.

    abstract::Spatio-temporal brain activities with variable delay detectable in resting-state functional magnetic resonance imaging (rs-fMRI) give rise to highly reproducible structures, termed cortical lag threads, that propagate from one brain region to another. Using a computational topology of data approach, we found that pers...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2020.00034

    authors: Don APH,Peters JF,Ramanna S,Tozzi A

    更新日期:2020-04-22 00:00:00

  • Segmental Bayesian estimation of gap-junctional and inhibitory conductance of inferior olive neurons from spike trains with complicated dynamics.

    abstract::The inverse problem for estimating model parameters from brain spike data is an ill-posed problem because of a huge mismatch in the system complexity between the model and the brain as well as its non-stationary dynamics, and needs a stochastic approach that finds the most likely solution among many possible solutions...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2015.00056

    authors: Hoang H,Yamashita O,Tokuda IT,Sato MA,Kawato M,Toyama K

    更新日期:2015-05-21 00:00:00

  • Cooperation and Competition with Hyperscanning Methods: Review and Future Application to Emotion Domain.

    abstract::Cooperation and competition, as two common and opposite examples of interpersonal dynamics, are thought to be reflected by different cognitive, neural, and behavioral patterns. According to the conventional approach, they have been explored by measuring subjects' reactions during individual performance or turn-based i...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章,评审

    doi:10.3389/fncom.2017.00086

    authors: Balconi M,Vanutelli ME

    更新日期:2017-09-29 00:00:00

  • Enabling functional neural circuit simulations with distributed computing of neuromodulated plasticity.

    abstract::A major puzzle in the field of computational neuroscience is how to relate system-level learning in higher organisms to synaptic plasticity. Recently, plasticity rules depending not only on pre- and post-synaptic activity but also on a third, non-local neuromodulatory signal have emerged as key candidates to bridge th...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2010.00141

    authors: Potjans W,Morrison A,Diesmann M

    更新日期:2010-11-23 00:00:00

  • Statistical physics of pairwise probability models.

    abstract::Statistical models for describing the probability distribution over the states of biological systems are commonly used for dimensional reduction. Among these models, pairwise models are very attractive in part because they can be fit using a reasonable amount of data: knowledge of the mean values and correlations betw...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/neuro.10.022.2009

    authors: Roudi Y,Aurell E,Hertz JA

    更新日期:2009-11-17 00:00:00

  • Analog Signaling With the "Digital" Molecular Switch CaMKII.

    abstract::Molecular switches, such as the protein kinase CaMKII, play a fundamental role in cell signaling by decoding inputs into either high or low states of activity; because the high activation state can be turned on and persist after the input ceases, these switches have earned a reputation as "digital." Although this on/o...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2018.00092

    authors: Clarke SE

    更新日期:2018-11-22 00:00:00

  • Visual Cortex Inspired CNN Model for Feature Construction in Text Analysis.

    abstract::Recently, biologically inspired models are gradually proposed to solve the problem in text analysis. Convolutional neural networks (CNN) are hierarchical artificial neural networks, which include a various of multilayer perceptrons. According to biological research, CNN can be improved by bringing in the attention mod...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2016.00064

    authors: Fu H,Niu Z,Zhang C,Ma J,Chen J

    更新日期:2016-07-14 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

  • Computational models of neuron-astrocyte interaction in epilepsy.

    abstract::Astrocytes actively shape the dynamics of neurons and neuronal ensembles by affecting several aspects critical to neuronal function, such as regulating synaptic plasticity, modulating neuronal excitability, and maintaining extracellular ion balance. These pathways for astrocyte-neuron interaction can also enhance the ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2012.00058

    authors: Volman V,Bazhenov M,Sejnowski TJ

    更新日期:2012-08-13 00:00:00

  • A micro-pool model for decision-related signals in visual cortical areas.

    abstract::The study of sensory signaling in the visual cortex has been greatly advanced by the recording of neural activity simultaneously with the performance of a specific psychophysical task. Individual nerve cells may also increase their firing leading up to the particular choice or decision made on a single psychophysical ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2013.00115

    authors: Parker AJ

    更新日期:2013-08-13 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

  • Neural Coding With Bursts-Current State and Future Perspectives.

    abstract::Neuronal action potentials or spikes provide a long-range, noise-resistant means of communication between neurons. As point processes single spikes contain little information in themselves, i.e., outside the context of spikes from other neurons. Moreover, they may fail to cross a synapse. A burst, which consists of a ...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章,评审

    doi:10.3389/fncom.2018.00048

    authors: Zeldenrust F,Wadman WJ,Englitz B

    更新日期:2018-07-06 00:00:00

  • A model-based approach to predict muscle synergies using optimization: application to feedback control.

    abstract::This paper presents a new model-based method to define muscle synergies. Unlike the conventional factorization approach, which extracts synergies from electromyographic data, the proposed method employs a biomechanical model and formally defines the synergies as the solution of an optimal control problem. As a result,...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2015.00121

    authors: Sharif Razavian R,Mehrabi N,McPhee J

    更新日期:2015-10-06 00:00:00

  • A Neuronal Network Model for Pitch Selectivity and Representation.

    abstract::Pitch is a perceptual correlate of periodicity. Sounds with distinct spectra can elicit the same pitch. Despite the importance of pitch perception, understanding the cellular mechanism of pitch perception is still a major challenge and a mechanistic model of pitch is lacking. A multi-stage neuronal network model is de...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2016.00057

    authors: Huang C,Rinzel J

    更新日期:2016-06-16 00:00:00

  • Stochastic Resonance Based Visual Perception Using Spiking Neural Networks.

    abstract::Our aim is to propose an efficient algorithm for enhancing the contrast of dark images based on the principle of stochastic resonance in a global feedback spiking network of integrate-and-fire neurons. By linear approximation and direct simulation, we disclose the dependence of the peak signal-to-noise ratio on the sp...

    journal_title:Frontiers in computational neuroscience

    pub_type: 杂志文章

    doi:10.3389/fncom.2020.00024

    authors: Fu Y,Kang Y,Chen G

    更新日期:2020-05-15 00:00:00