scholarly journals Rare long-range cortical connections enhance information processing

2021 ◽  
Author(s):  
Gustavo Deco ◽  
Yonathan Sanz Perl ◽  
Peter Vuust ◽  
Enzo Tagliazucchi ◽  
Henry Kennedy ◽  
...  
Keyword(s):  
Information Processing ◽  
Long Range ◽  
Small Proportion ◽  
Large Scale ◽  
Brain Dynamics ◽  
Turbulent Regime ◽  
Cortical Function ◽  
Information Cascade ◽  
Causal Function ◽  
Topological Features

SummaryA fundamental and unanswered question concerns the key topological features of connectivity that are critically relevant for generating the dynamics underlying efficient cortical function. A candidate feature that has recently emerged is that the connectivity of the mammalian cortex follows an exponential distance rule, which uniquely includes a small proportion of long-range high-weight anatomical connections. We investigate how these long-range connections influence whole-brain dynamics with coupled oscillators. To understand the causal function of long-range connections, we first studied these connections in simple ring structures and then in complex empirical brain architectures. A small proportion of long-range connections are sufficient for significantly improving information transmission, i.e. information cascade. Large-scale empirical neuroimaging modelling point to the immense functional benefits for information processing of a brain architecture with long-range coupling that improves the information cascade thanks to the underlying turbulent regime of brain dynamics.

scholarly journals Synchronous brain dynamics establish brief states of communality in distant neuronal populations

2021 ◽  
Author(s):  
Martin Seeber ◽  
Christoph M. Michel
Keyword(s):  
Long Range ◽  
Large Scale ◽  
Temporal Stability ◽  
Brain Dynamics ◽  
Brain Areas ◽  
Neuronal Populations ◽  
Scalp Eeg ◽  
Eyes Closed ◽  
Dynamic Coordination ◽  
Functional Brain Networks

Intrinsic brain dynamics co-fluctuate between distant regions in an organized manner during rest, establishing large-scale functional networks. We investigate these brain dynamics on a millisecond time scale by focusing on Electroencephalographic (EEG) source analyses. While synchrony is thought of as a neuronal mechanism grouping distant neuronal populations into assemblies, the relevance of simultaneous zero-lag synchronization between brain areas in humans remains largely unexplored. This negligence is due to the confound of volume conduction, leading inherently to temporal dependencies of source estimates derived from scalp EEG (and Magnetoencephalography, MEG), referred to as spatial leakage. Here, we focus on the analyses of simultaneous, i.e., quasi zero-lag related, synchronization that cannot be explained by spatial leakage phenomenon. In eighteen subjects during rest with eyes closed, we provide evidence that first, simultaneous synchronization is present between distant brain areas and second, that this long-range synchronization is occurring in brief epochs, i.e., 54-80 milliseconds. Simultaneous synchronization might signify the functional convergence of remote neuronal populations. Given the simultaneity of distant regions, these synchronization patterns might relate to the representation and maintenance, rather than processing of information. This long-range synchronization is briefly stable, not persistently, indicating flexible spatial reconfiguration pertaining to the establishment of particular, re-occurring states. Taken together, we suggest that the balance between temporal stability and spatial flexibility of long-range, simultaneous synchronization patterns is characteristic of the dynamic coordination of large-scale functional brain networks. As such, quasi zero-phase related EEG source fluctuations are physiologically meaningful if spatial leakage is considered appropriately.

scholarly journals TransMed: Transformers Advance Multi-Modal Medical Image Classification

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1384
Author(s):  
Yin Dai ◽  
Yifan Gao ◽  
Fayu Liu
Keyword(s):  
Image Analysis ◽  
Image Classification ◽  
Long Range ◽  
Medical Image ◽  
Large Scale ◽  
Medical Images ◽  
Medical Image Analysis ◽  
Lesion Detection ◽  
Tumor Segmentation ◽  
Medical Image Classification

Over the past decade, convolutional neural networks (CNN) have shown very competitive performance in medical image analysis tasks, such as disease classification, tumor segmentation, and lesion detection. CNN has great advantages in extracting local features of images. However, due to the locality of convolution operation, it cannot deal with long-range relationships well. Recently, transformers have been applied to computer vision and achieved remarkable success in large-scale datasets. Compared with natural images, multi-modal medical images have explicit and important long-range dependencies, and effective multi-modal fusion strategies can greatly improve the performance of deep models. This prompts us to study transformer-based structures and apply them to multi-modal medical images. Existing transformer-based network architectures require large-scale datasets to achieve better performance. However, medical imaging datasets are relatively small, which makes it difficult to apply pure transformers to medical image analysis. Therefore, we propose TransMed for multi-modal medical image classification. TransMed combines the advantages of CNN and transformer to efficiently extract low-level features of images and establish long-range dependencies between modalities. We evaluated our model on two datasets, parotid gland tumors classification and knee injury classification. Combining our contributions, we achieve an improvement of 10.1% and 1.9% in average accuracy, respectively, outperforming other state-of-the-art CNN-based models. The results of the proposed method are promising and have tremendous potential to be applied to a large number of medical image analysis tasks. To our best knowledge, this is the first work to apply transformers to multi-modal medical image classification.

scholarly journals On the dynamical interaction between overshooting convection and an underlying dipole magnetic field – I. The non-dynamo regime

2021 ◽  
Vol 503 (1) ◽  
pp. 362-375
Author(s):  
L Korre ◽  
NH Brummell ◽  
P Garaud ◽  
C Guervilly
Keyword(s):  
Magnetic Field ◽  
Turbulent Diffusion ◽  
Large Scale ◽  
Molecular Diffusion ◽  
Mean Field ◽  
Stable Region ◽  
Turbulent Regime ◽  
Poloidal Magnetic Field ◽  
Dynamical Interaction ◽  
Large Scale Field

ABSTRACT Motivated by the dynamics in the deep interiors of many stars, we study the interaction between overshooting convection and the large-scale poloidal fields residing in radiative zones. We have run a suite of 3D Boussinesq numerical calculations in a spherical shell that consists of a convection zone with an underlying stable region that initially compactly contains a dipole field. By varying the strength of the convective driving, we find that, in the less turbulent regime, convection acts as turbulent diffusion that removes the field faster than solely molecular diffusion would do. However, in the more turbulent regime, turbulent pumping becomes more efficient and partially counteracts turbulent diffusion, leading to a local accumulation of the field below the overshoot region. These simulations suggest that dipole fields might be confined in underlying stable regions by highly turbulent convective motions at stellar parameters. The confinement is of large-scale field in an average sense and we show that it is reasonably modelled by mean-field ideas. Our findings are particularly interesting for certain models of the Sun, which require a large-scale, poloidal magnetic field to be confined in the solar radiative zone in order to explain simultaneously the uniform rotation of the latter and the thinness of the solar tachocline.

Large-scale motion in the intermittent region of a turbulent boundary layer

1970 ◽  
Vol 41 (2) ◽  
pp. 283-325 ◽  
Author(s):  
Leslie S. G. Kovasznay ◽  
Valdis Kibens ◽  
Ron F. Blackwelder
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Large Scale ◽  
Cross Correlation ◽  
Turbulent Regime ◽  
Conditional Sampling ◽  
Correlation Data ◽  
Measuring Techniques ◽  
Conditional Averaging ◽  
Scale Motion

The outer intermittent region of a fully developed turbulent boundary layer with zero pressure gradient was extensively explored in the hope of shedding some light on the shape and motion of the interface separating the turbulent and non-turbulent regions as well as on the nature of the related large-scale eddies within the turbulent regime. Novel measuring techniques were devised, such as conditional sampling and conditional averaging, and others were turned to new uses, such as reorganizing in map form the space-time auto- and cross-correlation data involving both the U and V velocity components as well as I, the intermittency function. On the basis of the new experimental results, a conceptual model for the development of the interface and for the entrainment of new fluid is proposed.

TrafficBERT: Pre-trained model with large-scale data for long-range traffic flow forecasting

2021 ◽  
pp. 115738
Author(s):  
KyoHoon Jin ◽  
JeongA Wi ◽  
EunJu Lee ◽  
ShinJin Kang ◽  
SooKyun Kim ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Long Range ◽  
Large Scale ◽  
Traffic Flow Forecasting ◽  
Large Scale Data ◽  
Scale Data

The Finale of Mahler's Fifth Symphony: Long-Range Musical Thought

1987 ◽  
Vol 112 (2) ◽  
pp. 257-279
Author(s):  
Carolyn Baxendale
Keyword(s):  
Long Range ◽  
Large Scale ◽  
New Technique ◽  
Musical Thought ◽  
Musical Concepts ◽  
A New Technique

It is clear that all the experience I had gained in writing the first four symphonies completely let me down in this one- for a completely new style demanded a new technique.Twenty-Five years ago a prominent Mahler enthusiast could describe the finale of Mahler's Fifth Symphony as ‘a windy, uninspired stretch of note-spinning, literally scraping the barrel in search of music’. Few people nowadays would subscribe to this view: indeed the upsurge of interest in the work of other ‘late Romantic’ composers has perhaps served to sharpen our admiration for Mahler's exceptional powers of invention and his no less extraordinary mastery of large-scale form. Yet we are not really any closer to explaining just how such extended works are held together and given shape, particularly in the absence of specific extra-musical concepts such as those of the ‘Wunderhorn’ symphonies.

Waves, jets and vortices: Regime transitions in shallow water turbulence

2021 ◽  
Author(s):  
Nikos Bakas
Keyword(s):  
Shallow Water ◽  
Large Scale ◽  
Rossby Waves ◽  
Phase Speed ◽  
Critical Value ◽  
Turbulent Regime ◽  
Wave Regime ◽  
Frequency Spectra ◽  
Spectra Analysis ◽  
Zonal Jets

<p>Forced-dissipative beta-plane turbulence in a single-layer shallow-water fluid has been widely considered as a simplified model of planetary turbulence as it exhibits turbulence self-organization into large-scale structures such as robust zonal jets and strong vortices. In this study we perform a series of numerical simulations to analyze the characteristics of the emerging structures as a function of the planetary vorticity gradient and the deformation radius. We report four regimes that appear as the energy input rate ε of the random stirring that supports turbulence in the flow increases. A homogeneous turbulent regime for low values of ε, a regime in which large scale Rossby waves form abruptly when ε passes a critical value, a regime in which robust zonal jets coexist with weaker Rossby waves when ε passes a second critical value and a regime of strong materially coherent propagating vortices for large values of ε. The wave regime which is not predicted by standard cascade theories of turbulence anisotropization and the vortex regime are studied thoroughly. Wavenumber-frequency spectra analysis shows that the Rossby waves in the second regime remain phase coherent over long times. The coherent vortices are identified using the Lagrangian Averaged Deviation (LAVD) method. The statistics of the vortices (lifetime, radius, strength and speed) are reported as a function of the large scale parameters. We find that the strong vortices propagate zonally with a phase speed that is equal or larger than the long Rossby wave speed and advect the background turbulence leading to a non-dispersive line in the wavenumber-frequency spectra.</p>

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