scholarly journals Functional Roles of Alpha-Band Phase Synchronization in Local and Large-Scale Cortical Networks

2011 ◽  
Vol 2 ◽  
Author(s):  
Satu Palva ◽  
J. Matias Palva
Keyword(s):  
Large Scale ◽  
Phase Synchronization ◽  
Alpha Band ◽  
Cortical Networks ◽  
Functional Roles

scholarly journals The frustrated brain: from dynamics on motifs to communities and networks

2014 ◽  
Vol 369 (1653) ◽  
pp. 20130532 ◽  
Author(s):  
Leonardo L. Gollo ◽  
Michael Breakspear
Keyword(s):  
Cognitive Processes ◽  
Large Scale ◽  
Phase Synchronization ◽  
Metastable Phase ◽  
Network Size ◽  
Stable States ◽  
Adaptive Function ◽  
Cortical Networks ◽  
Broad Variety ◽  
Coupling Strengths

Cognitive function depends on an adaptive balance between flexible dynamics and integrative processes in distributed cortical networks. Patterns of zero-lag synchrony likely underpin numerous perceptual and cognitive functions. Synchronization fulfils integration by reducing entropy, while adaptive function mandates that a broad variety of stable states be readily accessible. Here, we elucidate two complementary influences on patterns of zero-lag synchrony that derive from basic properties of brain networks. First, mutually coupled pairs of neuronal subsystems—resonance pairs—promote stable zero-lag synchrony among the small motifs in which they are embedded, and whose effects can propagate along connected chains. Second, frustrated closed-loop motifs disrupt synchronous dynamics, enabling metastable configurations of zero-lag synchrony to coexist. We document these two complementary influences in small motifs and illustrate how these effects underpin stable versus metastable phase-synchronization patterns in prototypical modular networks and in large-scale cortical networks of the macaque (CoCoMac). We find that the variability of synchronization patterns depends on the inter-node time delay, increases with the network size and is maximized for intermediate coupling strengths. We hypothesize that the dialectic influences of resonance versus frustration may form a dynamic substrate for flexible neuronal integration, an essential platform across diverse cognitive processes.

scholarly journals Cortical traveling waves reflect state-dependent hierarchical sequencing of local regions in the human connectome network

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Naoyuki Sato
Keyword(s):  
Traveling Waves ◽  
Large Scale ◽  
Phase Synchronization ◽  
Hierarchical Organization ◽  
Cortical Surface ◽  
Intrinsic Frequency ◽  
Cortical Networks ◽  
State Dependent ◽  
Cortical Regions ◽  
Empirical Networks

AbstractRecent human studies using electrocorticography have demonstrated that alpha and theta band oscillations form traveling waves on the cortical surface. According to neural synchronization theories, the cortical traveling waves may group local cortical regions and sequence them by phase synchronization; however these contributions have not yet been assessed. This study aimed to evaluate the functional contributions of traveling waves using connectome-based network modeling. In the simulation, we observed stable traveling waves on the entire cortical surface wherein the topographical pattern of these phases was substantially correlated with the empirically obtained resting-state networks, and local radial waves also appeared within the size of the empirical networks (< 50 mm). Importantly, individual regions in the entire network were instantaneously sequenced by their internal frequencies, and regions with higher intrinsic frequency were seen in the earlier phases of the traveling waves. Based on the communication-through-coherence theory, this phase configuration produced a hierarchical organization of each region by unidirectional communication between the arbitrarily paired regions. In conclusion, cortical traveling waves reflect the intrinsic frequency-dependent hierarchical sequencing of local regions, global traveling waves sequence the set of large-scale cortical networks, and local traveling waves sequence local regions within individual cortical networks.

scholarly journals High-alpha band synchronization across frontal, parietal and visual cortex mediates behavioral and neuronal effects of visuospatial attention

2017 ◽  
Author(s):  
Muriel Lobier ◽  
J. Matias Palva ◽  
Satu Palva
Keyword(s):  
Visual Cortex ◽  
Large Scale ◽  
Phase Synchronization ◽  
Reaction Times ◽  
Alpha Phase ◽  
Visuospatial Attention ◽  
Alpha Band ◽  
Attention Task ◽  
Neuronal Communication ◽  
Frontoparietal Network

Visuospatial attention prioritizes processing of attended visual stimuli. It is characterized by lateralized alpha-band (8-14 Hz) amplitude suppression in visual cortex and increased neuronal activity in a network of frontal and parietal areas. It has remained unknown what mechanisms coordinate neuronal processing among frontoparietal network and visual cortices and implement the attention-related modulations of alpha-band amplitudes and behavior. We investigated whether large-scale network synchronization could be such a mechanism. We recorded human cortical activity with magnetoencephalography (MEG) during a visuospatial attention task. We then identified the frequencies and anatomical networks of inter-areal phase synchronization from source localized MEG data. We found that visuospatial attention is associated with robust and sustained long-range synchronization of cortical oscillations exclusively in the high-alpha (10-14 Hz) frequency band. This synchronization connected frontal, parietal and visual regions and was observed concurrently with amplitude suppression of low-alpha (6-9 Hz) band oscillations in visual cortex. Furthermore, stronger high-alpha phase synchronization was associated with decreased reaction times to attended stimuli and larger suppression of alpha-band amplitudes. These results thus show that high-alpha band phase synchronization is functionally significant and could coordinate the neuronal communication underlying the implementation of visuospatial attention.

scholarly journals A novel dynamic network imaging analysis method reveals aging-related fragmentation of cortical networks in mouse

2019 ◽  
Author(s):  
Daniel A Llano ◽  
Chihua Ma ◽  
Umberto Di Fabrizio ◽  
Aynaz Taheri ◽  
Kevin A. Stebbings ◽  
...  
Keyword(s):  
Auditory Cortex ◽  
Large Scale ◽  
Brain Slices ◽  
Dynamic Network ◽  
Analytical Tool ◽  
Aging Brain ◽  
Autofluorescence Imaging ◽  
Imaging Data ◽  
Cortical Networks ◽  
Network Metrics

AbstractNetwork analysis of large-scale neuroimaging data has proven to be a particularly challenging computational problem. In this study, we adapt a novel analytical tool, known as the community dynamic inference method (CommDy), which was inspired by social network theory, for the study of brain imaging data from an aging mouse model. CommDy has been successfully used in other domains in biology; this report represents its first use in neuroscience. We used CommDy to investigate aging-related changes in network parameters in the auditory and motor cortices using flavoprotein autofluorescence imaging in brain slices and in vivo. Analysis of spontaneous activations in the auditory cortex of slices taken from young and aged animals demonstrated that cortical networks in aged brains were highly fragmented compared to networks observed in young animals. Specifically, the degree of connectivity of each activated node in the aged brains was significantly lower than those seen in the young brain, and multivariate analyses of all derived network metrics showed distinct clusters of these metrics in young vs. aged brains. CommDy network metrics were then used to build a random-forests classifier based on NMDA-receptor blockade data, which successfully recapitulated the aging findings, suggesting that the excitatory synaptic substructure of the auditory cortex may be altered during aging. A similar aging-related decline in network connectivity was also observed in spontaneous activity obtained from the awake motor cortex, suggesting that the findings in the auditory cortex are reflections of general mechanisms that occur during aging. Therefore, CommDy therefore provides a new dynamic network analytical tool to study the brain and provides links between network-level and synaptic-level dysfunction in the aging brain.

scholarly journals ANALYSIS OF THE FUCTIONAL ROLE OF RICE MILLING COMPANY ON THE WELFARE OF RICE FARMERS IN THE SUB-DISTRICT BUAY MADANG TIMUR DISTRICT OKU TIMUR

Jurnal AKTUAL ◽  
2019 ◽  
Vol 16 (1) ◽  
pp. 47
Author(s):  
Aisah Aisah
Keyword(s):  
Large Scale ◽  
Raw Materials ◽  
Small Scale ◽  
Functional Roles ◽  
Medium Scale ◽  
Rice Farmers ◽  
Result Show ◽  
Rice Milling ◽  
Processing And Storage

Rice Milling Company is rice industry’s oldest and largest classified in Indonesia, which is able to absorb more than 10 million workers, handles more than 40 million tons of grain.  Rice Milling Company agro-industy is the central point, because this is where the main product is obtained in the form of rice and raw materials for advanced processing of food and industrial products.  Rice Miling Unit in the district of OKU Timur there is some skala, ranging form small-scale, medium-scale to large-scale.  Fuctional benefits of each different scale milling is also different.  The average rice farmers often sell gabahnya to the rice milling unit closest to the place residence, whether it is large-scale, medium and small.  Rice produced by the milling-grinding different quality.  Usually when a large-scale millimg yield of rice is cleaner than the other scale.  But it does not become a reference for milling grain milling usually depends on consumer demand.  The purpose of the study are : 1.  To determine levels of volume (tonnage) and the retention time of each service fuctional rice storage (barns) wich carried a different scale rice milling unit.  2.  To determine differences in the bebefits of economic transactions received by farmers and rice millers of different scale of business, especially when seen from the level of the milling costs, the purchase price of rice by rice milling unit, and the quality of milling services and service scale.  The result show that : the fuctional role of each is different milling.  Large-scale milling has three fuctional roles are : Processing, storage and distribution.  Medium-scale miling functional has two roles, namely : processing and distribution.  While small-scale rice milling unit has only two functional roles are : processing and storage.

scholarly journals A Deep Boosting Based Approach for Capturing the Sequence Binding Preferences of RNA-Binding Proteins from High-Throughput CLIP-Seq Data

2016 ◽  
Author(s):  
Shuya Li ◽  
Fanghong Dong ◽  
Yuexin Wu ◽  
Sai Zhang ◽  
Chen Zhang ◽  
...  
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Binding Proteins ◽  
Rna Binding ◽  
Gene Expression Regulation ◽  
Rna Binding Proteins ◽  
False Negative ◽  
Functional Roles ◽  
Potential Applications ◽  
Validation Tests

AbstractCharacterizing the binding behaviors of RNA-binding proteins (RBPs) is important for understanding their functional roles in gene expression regulation. However, current high-throughput experimental methods for identifying RBP targets, such as CLIP-seq and RNAcompete, usually suffer from the false positive and false negative issues. Here, we develop a deep boosting based machine learning approach, called DeBooster, to accurately model the binding sequence preferences and identify the corresponding binding targets of RBPs from CLIP-seq data. Comprehensive validation tests have shown that DeBooster can outperform other state-of-the-art approaches in predicting RBP targets and recover false negatives that are common in current CLIP-seq data. In addition, we have demonstrated several new potential applications of DeBooster in understanding the regulatory functions of RBPs, including the binding effects of the RNA helicase MOV10 on mRNA degradation, the influence of different binding behaviors of the ADAR proteins on RNA editing, as well as the antagonizing effect of RBP binding on miRNA repression. Moreover, DeBooster may provide an effective index to investigate the effect of pathogenic mutations in RBP binding sites, especially those related to splicing events. We expect that DeBooster will be widely applied to analyze large-scale CLIP-seq experimental data and can provide a practically useful tool for novel biological discoveries in understanding the regulatory mechanisms of RBPs.

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