Activity-dependent myelination: A glial mechanism of oscillatory self-organization in large-scale brain networks

Communication and oscillatory synchrony between distributed neural populations are believed to play a key role in multiple cognitive and neural functions. These interactions are mediated by long-range myelinated axonal fiber bundles, collectively termed as white matter. While traditionally considered to be static after development, white matter properties have been shown to change in an activity-dependent way through learning and behavior—a phenomenon known as white matter plasticity. In the central nervous system, this plasticity stems from oligodendroglia, which form myelin sheaths to regulate the conduction of nerve impulses across the brain, hence critically impacting neural communication. We here shift the focus from neural to glial contribution to brain synchronization and examine the impact of adaptive, activity-dependent changes in conduction velocity on the large-scale phase synchronization of neural oscillators. Using a network model based on primate large-scale white matter neuroanatomy, our computational and mathematical results show that such plasticity endows white matter with self-organizing properties, where conduction delay statistics are autonomously adjusted to ensure efficient neural communication. Our analysis shows that this mechanism stabilizes oscillatory neural activity across a wide range of connectivity gain and frequency bands, making phase-locked states more resilient to damage as reflected by diffuse decreases in connectivity. Critically, our work suggests that adaptive myelination may be a mechanism that enables brain networks with a means of temporal self-organization, resilience, and homeostasis.

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OncoThreads: Visualization of Large Scale Longitudinal Cancer Molecular Data

10.31219/osf.io/b3n4u ◽

2021 ◽

Author(s):

Theresa A Harbig ◽

Sabrina Nusrat ◽

Tali Mazor ◽

Qianwen Wang ◽

Alexander Thomson ◽

...

Keyword(s):

Longitudinal Data ◽

Large Scale ◽

Cancer Genomics ◽

Temporal Patterns ◽

Molecular Data ◽

Liquid Biopsies ◽

Sequencing Technologies ◽

Molecular Features ◽

Wide Range ◽

The Impact

Molecular profiling of patient tumors and liquid biopsies over time with next-generation sequencing technologies and new immuno-profile assays are becoming part of standard research and clinical practice. With the wealth of new longitudinal data, there is a critical need for visualizations for cancer researchers to explore and interpret temporal patterns not just in a single patient but across cohorts. To address this need we developed OncoThreads, a tool for the visualization of longitudinal clinical and cancer genomics and other molecular data in patient cohorts. The tool visualizes patient cohorts as temporal heatmaps and Sankey diagrams that support the interactive exploration and ranking of a wide range of clinical and molecular features. This allows analysts to discover temporal patterns in longitudinal data, such as the impact of mutations on response to a treatment, e.g. emergence of resistant clones. We demonstrate the functionality of OncoThreads using a cohort of 23 glioma patients sampled at 2-4 timepoints. OncoThreads is freely available at http://oncothreads.gehlenborglab.org and implemented in Javascript using the cBioPortal web API as a backend.

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Ivan Kavaleridze`s dramaturgy on the Sumy stage

SUMY HISTORICAL AND ARCHIVAL JOURNAL ◽

10.21272/shaj.2021.i36.p.37 ◽

2021 ◽

Author(s):

D.V. Budianskyi

Keyword(s):

Large Scale ◽

Musical Comedy ◽

Historical Figures ◽

Wide Range ◽

Socialist Realist ◽

History Of ◽

Characteristic Features ◽

Old Men ◽

The Impact ◽

First Time

The characteristic features of I. Kavaleridze’s drama is considered in the article. It is noted that there are signs of the artist’s individuality, attraction to expressionist forms, artistic techniques characteristic for the art of sculpture: symbolism, monumentality, hyperbole. I. Kavaleridze was well versed in the drama laws, understood the specifics of the stage events construction, had a large arsenal of literary means, thanks to which the characters’ monologues and dialogues were extremely expressive and colorful. In his work, he implemented original solutions that were ahead of time. Therefore, many of the artist’s ideas and achievements received due recognition only after his death. I. Kavaleridze’s creative heritage covers a wide range of both purely artistic and general philosophical problems. Among them the formation of the era of modernism and its features in the Ukrainian art of the early XX century, the impact of revolutionary ideas on the work of the 1920s, the role of spiritual leaders of the Ukrainian people T. Shevchenko and G. Skovoroda in the formation of national consciousness, political and ideological pressure on figurative art language and the formation of a socialist-realist canon, etc. The analysis of the productions of I. Kavalerizde’s plays “The First Furrow” and “Gregory and Paraskeva” on the stage of the Mykhailo Shchepkin Sumy Theater of Drama and Musical Comedy in 1970-1972. The article notes that these plays were staged in Sumy for the first time in the history of Ukrainian theater. The premiere of “The First Furrow” (the play was called “Old Men”) took place on March 19, 1970. The figure of the national genius Hryhoriy Skov oroda was als o embodied for the first time on t he stage in Sumy in th e play “Hryhoriy and Paraskeva”. It premiered on October 21, 1972. I. Rybchynsky, Honored Artist of the USSR, performed the production. Creating generalized historical outlines of people’s life, features of life at that time, depicting psychological portraits of people in various, sometimes-dramatic collisions, in the productions of I. Kavaleridze’s plays on the Sumy stage the emphasis was on universal values such as virtue, love. The main character was the Ukrainian people, who nurtured such large-scale historical figures, gave them strength and wisdom for great achievements. Based on publications in periodicals of that time, memoirs of Ukrainian directors, the peculiarities of the director’s interpretation, stenographic and musical design of these plays on the Sumy stage are considered. Considerable attention is paid to the analysis of acting works in I. Kavaleridze’s plays. In particular, the peculiarities of the actor’s embodiment of the image of the national genius Hryhoriy Skovoroda on the stage are presented. It is noted that I. Kavaleridze’s plays, created in a difficult political, social and ideological context, are rightly considered to be highly artistic works of Ukrainian drama. Their staging was carried out on various theatrical stages, including Mykhailo Shchepkin Sumy Theater of Drama and Musical Comedy is an important page of national theatrical art.

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Economics of the disintegration of the Greenland ice sheet

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1814990116 ◽

2019 ◽

Vol 116 (25) ◽

pp. 12261-12269 ◽

Cited By ~ 5

Author(s):

William Nordhaus

Keyword(s):

Climate Change ◽

Large Scale ◽

Social Cost ◽

Climate Models ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Reduced Form ◽

Small Contribution ◽

Wide Range ◽

The Impact

Concerns about the impact on large-scale earth systems have taken center stage in the scientific and economic analysis of climate change. The present study analyzes the economic impact of a potential disintegration of the Greenland ice sheet (GIS). The study introduces an approach that combines long-run economic growth models, climate models, and reduced-form GIS models. The study demonstrates that social cost–benefit analysis and damage-limiting strategies can be usefully extended to illuminate issues with major long-term consequences, as well as concerns such as potential tipping points, irreversibility, and hysteresis. A key finding is that, under a wide range of assumptions, the risk of GIS disintegration makes a small contribution to the optimal stringency of current policy or to the overall social cost of climate change. It finds that the cost of GIS disintegration adds less than 5% to the social cost of carbon (SCC) under alternative discount rates and estimates of the GIS dynamics.

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InSAR Greece with Parallelized Persistent Scatterer Interferometry: A National Ground Motion Service for Big Copernicus Sentinel-1 Data

Remote Sensing ◽

10.3390/rs12193207 ◽

2020 ◽

Vol 12 (19) ◽

pp. 3207

Author(s):

Ioannis Papoutsis ◽

Charalampos Kontoes ◽

Stavroula Alatza ◽

Alexis Apostolakis ◽

Constantinos Loupasakis

Keyword(s):

Time Series ◽

Ground Motion ◽

Large Scale ◽

Persistent Scatterer Interferometry ◽

Persistent Scatterers ◽

Processing Chain ◽

Persistent Scatterer ◽

Basin Scale ◽

Wide Range ◽

The Impact

Advances in synthetic aperture radar (SAR) interferometry have enabled the seamless monitoring of the Earth’s crust deformation. The dense archive of the Sentinel-1 Copernicus mission provides unprecedented spatial and temporal coverage; however, time-series analysis of such big data volumes requires high computational efficiency. We present a parallelized-PSI (P-PSI), a novel, parallelized, and end-to-end processing chain for the fully automated assessment of line-of-sight ground velocities through persistent scatterer interferometry (PSI), tailored to scale to the vast multitemporal archive of Sentinel-1 data. P-PSI is designed to transparently access different and complementary Sentinel-1 repositories, and download the appropriate datasets for PSI. To make it efficient for large-scale applications, we re-engineered and parallelized interferogram creation and multitemporal interferometric processing, and introduced distributed implementations to best use computing cores and provide resourceful storage management. We propose a new algorithm to further enhance the processing efficiency, which establishes a non-uniform patch grid considering land use, based on the expected number of persistent scatterers. P-PSI achieves an overall speed-up by a factor of five for a full Sentinel-1 frame for processing in a 20-core server. The processing chain is tested on a large-scale project to calculate and monitor deformation patterns over the entire extent of the Greek territory—our own Interferometric SAR (InSAR) Greece project. Time-series InSAR analysis was performed on volumes of about 12 TB input data corresponding to more than 760 Single Look Complex Sentinel-1A and B images mostly covering mainland Greece in the period of 2015–2019. InSAR Greece provides detailed ground motion information on more than 12 million distinct locations, providing completely new insights into the impact of geophysical and anthropogenic activities at this geographic scale. This new information is critical to enhancing our understanding of the underlying mechanisms, providing valuable input into risk assessment models. We showcase this through the identification of various characteristic geohazard locations in Greece and discuss their criticality. The selected geohazard locations, among a thousand, cover a wide range of catastrophic events including landslides, land subsidence, and structural failures of various scales, ranging from a few hundredths of square meters up to the basin scale. The study enriches the large catalog of geophysical related phenomena maintained by the GeObservatory portal of the Center of Earth Observation Research and Satellite Remote Sensing BEYOND of the National Observatory of Athens for the opening of new knowledge to the wider scientific community.

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Altered topology of large-scale structural brain networks in chronic stroke

Brain Communications ◽

10.1093/braincomms/fcz020 ◽

2019 ◽

Vol 1 (1) ◽

Cited By ~ 1

Author(s):

Bastian Cheng ◽

Eckhard Schlemm ◽

Robert Schulz ◽

Marlene Boenstrup ◽

Arnaud Messé ◽

...

Keyword(s):

Information Transfer ◽

Large Scale ◽

Neuronal Degeneration ◽

Brain Networks ◽

Brain Regions ◽

Local Network ◽

Structural Connectome ◽

The Impact ◽

Structural Brain ◽

Topological Changes

Abstract Beyond disruption of neuronal pathways, focal stroke lesions induce structural disintegration of distant, yet connected brain regions via retrograde neuronal degeneration. Stroke lesions alter functional brain connectivity and topology in large-scale brain networks. These changes are associated with the degree of clinical impairment and recovery. In contrast, changes of large scale, structural brain networks after stroke are less well reported. We therefore aimed to analyse the impact of focal lesions on the structural connectome after stroke based on data from diffusion-weighted imaging and probabilistic fibre tracking. In total, 17 patients (mean age 64.5 ± 8.4 years) with upper limb motor deficits in the chronic stage after stroke and 21 healthy participants (mean age 64.9 ± 10.3 years) were included. Clinical deficits were evaluated by grip strength and the upper extremity Fugl-Meyer assessment. We calculated global and local graph theoretical measures to characterize topological changes in the structural connectome. Results from our analysis demonstrated significant alterations of network topology in both ipsi- and contralesional, primarily unaffected, hemispheres after stroke. Global efficiency was significantly lower in stroke connectomes as an indicator of overall reduced capacity for information transfer between distant brain areas. Furthermore, topology of structural connectomes was shifted toward a higher degree of segregation as indicated by significantly higher values of global clustering and modularity. On a level of local network parameters, these effects were most pronounced in a subnetwork of cortico-subcortical brain regions involved in motor control. Structural changes were not significantly associated with clinical measures. We propose that the observed network changes in our patients are best explained by the disruption of inter- and intrahemispheric, long white matter fibre tracts connecting distant brain regions. Our results add novel insights on topological changes of structural large-scale brain networks in the ipsi- and contralesional hemisphere after stroke.

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Experience and activity-dependent control of glucocorticoid receptors during the stress response in large-scale brain networks

Stress ◽

10.1080/10253890.2020.1806226 ◽

2020 ◽

pp. 1-24 ◽

Cited By ~ 1

Author(s):

Damien Huzard ◽

Virginie Rappeneau ◽

Onno C. Meijer ◽

Chadi Touma ◽

Margarita Arango-Lievano ◽

...

Keyword(s):

Stress Response ◽

Large Scale ◽

Glucocorticoid Receptors ◽

Brain Networks ◽

Activity Dependent

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Motion Simulation Experiments for Driver Behavior and Road Vehicle Dynamics

Journal of Computing and Information Science in Engineering ◽

10.1115/1.3617437 ◽

2011 ◽

Vol 11 (4) ◽

Author(s):

Kemper Lewis ◽

Kevin Hulme ◽

Edward Kasprzak ◽

Deborah Moore-Russo ◽

Gregory Fabiano

Keyword(s):

Vehicle Dynamics ◽

Large Scale ◽

Driving Simulation ◽

Vehicle Design ◽

Simulation Environment ◽

Learning Mechanisms ◽

Road Vehicle ◽

Wide Range ◽

Traffic Systems ◽

The Impact

This paper discusses the design and development of a motion-based driving simulation and its integration into driving simulation research. The integration of the simulation environment into a road vehicle dynamics curriculum is also presented. The simulation environment provides an immersive experience to conduct a wide range of research on driving behavior, vehicle design and intelligent traffic systems. From an education perspective, the environment is designed to promote hands-on student participation in real-world engineering experiences that enhance conventional learning mechanisms for road vehicle dynamics and engineering systems analysis. The paper assesses the impact of the environment on student learning objectives in an upper level vehicle dynamics course and presents results from research involving teenage drivers. The paper presents an integrated framework for the use of real-time simulation and large-scale visualization to both study driving behaviors and to discover the impact that design decisions have on vehicle design using a realistic simulated driving interface.

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Phase Synchronization Stability of Non-Homogeneous Low-Voltage Distribution Networks with Large-Scale Distributed Generations

Energies ◽

10.3390/en13051257 ◽

2020 ◽

Vol 13 (5) ◽

pp. 1257 ◽

Cited By ~ 1

Author(s):

Shi Chen ◽

Hong Zhou ◽

Jingang Lai ◽

Yiwei Zhou ◽

Chang Yu

Keyword(s):

Power Law ◽

Coupling Strength ◽

Large Scale ◽

Phase Synchronization ◽

Distribution Networks ◽

Critical Coupling ◽

Power Law Distribution ◽

Distributed Generations ◽

Strength Formula ◽

The Impact

The ideal distributed network composed of distributed generations (DGs) has unweighted and undirected interactions which omit the impact of the power grid structure and actual demand. Apparently, the coupling relationship between DGs, which is determined by line impedance, node voltage, and droop coefficient, is generally non-homogeneous. Motivated by this, this paper investigates the phase synchronization of an islanded network with large-scale DGs in a non-homogeneous condition. Furthermore, we explicitly deduce the critical coupling strength formula for different weighting cases via the synchronization condition. On this basis, three cases of Gaussian distribution, power-law distribution, and frequency-weighted distribution are analyzed. A synthetical analysis is also presented, which helps to identify the order parameter. Finally, this paper employs the numerical simulation methods to test the effectiveness of the critical coupling strength formula and the superiority over the power-law distribution.

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Approximate weighted matching on emerging manycore and multithreaded architectures

The International Journal of High Performance Computing Applications ◽

10.1177/1094342012452893 ◽

2012 ◽

Vol 26 (4) ◽

pp. 413-430 ◽

Cited By ~ 20

Author(s):

Mahantesh Halappanavar ◽

John Feo ◽

Oreste Villa ◽

Antonino Tumeo ◽

Alex Pothen

Keyword(s):

Approximation Algorithms ◽

Large Scale ◽

Scientific Computing ◽

Graph Matching ◽

Combinatorial Problem ◽

Fine Tuning ◽

Matching Problem ◽

Weighted Matching ◽

Wide Range ◽

The Impact

Graph matching is a prototypical combinatorial problem with many applications in high-performance scientific computing. Optimal algorithms for computing matchings are challenging to parallelize. Approximation algorithms are amenable to parallelization and are therefore important to compute matchings for large-scale problems. Approximation algorithms also generate nearly optimal solutions that are sufficient for many applications. In this paper we present multithreaded algorithms for computing half-approximate weighted matching on state-of-the-art multicore (Intel Nehalem and AMD Magny-Cours), manycore (Nvidia Tesla and Nvidia Fermi), and massively multithreaded (Cray XMT) platforms. We provide two implementations: the first uses shared work queues and is suited for all platforms; and the second implementation, based on dataflow principles, exploits special features available on the Cray XMT. Using a carefully chosen dataset that exhibits characteristics from a wide range of applications, we show scalable performance across different platforms. In particular, for one instance of the input, an R-MAT graph (RMAT-G), we show speedups of about [Formula: see text] on [Formula: see text] cores of an AMD Magny-Cours, [Formula: see text] on [Formula: see text] cores of Intel Nehalem, [Formula: see text] on Nvidia Tesla and [Formula: see text] on Nvidia Fermi relative to one core of Intel Nehalem, and [Formula: see text] on [Formula: see text] processors of Cray XMT. We demonstrate strong as well as weak scaling for graphs with up to a billion edges using up to 12,800 threads. We avoid excessive fine-tuning for each platform and retain the basic structure of the algorithm uniformly across platforms. An exception is the dataflow algorithm designed specifically for the Cray XMT. To the best of the authors' knowledge, this is the first such large-scale study of the half-approximate weighted matching problem on multithreaded platforms. Driven by the critical enabling role of combinatorial algorithms such as matching in scientific computing and the emergence of informatics applications, there is a growing demand to support irregular computations on current and future computing platforms. In this context, we evaluate the capability of emerging multithreaded platforms to tolerate latency induced by irregular memory access patterns, and to support fine-grained parallelism via light-weight synchronization mechanisms. By contrasting the architectural features of these platforms against the Cray XMT, which is specifically designed to support irregular memory-intensive applications, we delineate the impact of these choices on performance.

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Vagal nerve stimulation triggers widespread responses and alters large-scale functional connectivity in the rat brain

10.1101/200220 ◽

2017 ◽

Cited By ~ 1

Author(s):

Jiayue Cao ◽

Kun-Han Lu ◽

Terry L. Powley ◽

Zhongming Liu

Keyword(s):

Vagus Nerve ◽

Nerve Stimulation ◽

Large Scale ◽

Time Course ◽

Brain Networks ◽

Blood Oxygenation ◽

7 Tesla ◽

Sprague Dawley ◽

Wide Range ◽

Oxygenation Level

AbstractVagus nerve stimulation (VNS) is a therapy for epilepsy and depression. However, its efficacy varies and its mechanism remains unclear. Prior studies have used functional magnetic resonance imaging (fMRI) to map brain activations with VNS in human brains, but have reported inconsistent findings. The source of inconsistency is likely attributable to the complex temporal characteristics of VNS-evoked fMRI responses that cannot be fully explained by simplified response models in the conventional model-based analysis for activation mapping. To address this issue, we acquired 7-Tesla blood oxygenation level dependent fMRI data from anesthetized Sprague–Dawley rats receiving electrical stimulation at the left cervical vagus nerve. Using spatially independent component analysis, we identified 20 functional brain networks and detected the network-wise activations with VNS in a data-driven manner. Our results showed that VNS activated 15 out of 20 brain networks, and the activated regions covered >76% of the brain volume. The time course of the evoked response was complex and distinct across regions and networks. In addition, VNS altered the strengths and patterns of correlations among brain networks relative to those in the resting state. The most notable changes in network-network interactions were related to the limbic system. Together, such profound and widespread effects of VNS may underlie its unique potential for a wide range of therapeutics to relieve central or peripheral conditions.

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