Organization of signal flow in directed networks

Bányai, Mihály; Négyessy, László; Bazsó, Fülöp

doi:10.1088/1742-5468/2011/06/p06001

Cited by 3 publications

(11 citation statements)

References 18 publications

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“…The degree of convergence and divergence was quantified by the analysis of all shortest paths using the notion of CD (Négyessy et al, 2008;Bányai et al, 2011b). CD is defined as the normalized difference between the number of input and target areas connected via a particular link of a directed graph, specifically…”

Section: Convergence Degree (Cd)mentioning

confidence: 99%

“…To further characterize each area with a single value, the CDflow was defined as the difference in the means of incoming and outgoing edge CD-s (Bányai et al, 2011b).…”

Section: Node-centric CD Representationmentioning

confidence: 99%

“…For the complete understanding of CD characteristics of the weighted network, the node-centric convergence degree measures (nrCD and CD-flow) were also computed. Figure 5B shows the nrCDw representation of the graph, which presents the characteristic shape shown by Négyessy et al (2008) and Bányai et al (2011b). Every node is present in all four quadrants, quantifying different aspects of the CD-based signalcoordinating capacity of the area the given node represents in the network.…”

Section: Analysis Of the Weighted CDmentioning

confidence: 99%

“…Only the anatomical network constructed by way of tract-tracing can represent the direction of neural connections, which provide further opportunities to identify functionally relevant topological features (Passingham et al, 2002 ; Kaiser, 2007 ; Markov et al, 2013a , 2014 ). Exploiting information in the distribution of directed edges and using edge betweenness centrality as a measure of connectedness (proportional to the number of shortest paths traversing an edge), an edge-based index called convergence degree (CD) was formulated, which uniquely characterizes the flow properties of networks (Négyessy et al, 2008 ; Bányai et al, 2011b ). Considering all directed shortest paths traversing a given edge, the CD determines convergence or divergence by the difference in the number of source and target nodes, i.e., convergent edges convey information from a larger number of nodes to a smaller set, while divergent edges from a smaller to a larger set.…”

Section: Introductionmentioning

confidence: 99%

“…Large-scale hierarchical network dynamics were simulated by a bilaminar Wilson–Cowan model, suitable for studying the oscillatory characteristics of feedforward and feedback interactions (Mejias et al, 2016 ). First of all, we aimed to extend the use of CD to weighted networks, as this index has been defined and applied only for binary graphs before (Négyessy et al, 2008 , 2012 ; Bányai et al, 2011b ). To this end, a refined combination of existing methods was developed for finding shortest paths in weighted graphs, which favors robustness at the expense of a winner-take-all approach (Newman, 2001 , 2005 ; Opsahl et al, 2010 ; Avena-Koenigsberger et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

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Network Path Convergence Shapes Low-Level Processing in the Visual Cortex

Varga

Soós

Jákli

et al. 2021

Front. Syst. Neurosci.

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Hierarchical counterstream via feedforward and feedback interactions is a major organizing principle of the cerebral cortex. The counterstream, as a topological feature of the network of cortical areas, is captured by the convergence and divergence of paths through directed links. So defined, the convergence degree (CD) reveals the reciprocal nature of forward and backward connections, and also hierarchically relevant integrative properties of areas through their inward and outward connections. We asked if topology shapes large-scale cortical functioning by studying the role of CD in network resilience and Granger causal coupling in a model of hierarchical network dynamics. Our results indicate that topological synchronizability is highly vulnerable to attacking edges based on CD, while global network efficiency depends mostly on edge betweenness, a measure of the connectedness of a link. Furthermore, similar to anatomical hierarchy determined by the laminar distribution of connections, CD highly correlated with causal coupling in feedforward gamma, and feedback alpha-beta band synchronizations in a well-studied subnetwork, including low-level visual cortical areas. In contrast, causal coupling did not correlate with edge betweenness. Considering the entire network, the CD-based hierarchy correlated well with both the anatomical and functional hierarchy for low-level areas that are far apart in the hierarchy. Conversely, in a large part of the anatomical network where hierarchical distances are small between the areas, the correlations were not significant. These findings suggest that CD-based and functional hierarchies are interrelated in low-level processing in the visual cortex. Our results are consistent with the idea that the interplay of multiple hierarchical features forms the basis of flexible functional cortical interactions.

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Section: Convergence Degree (Cd)mentioning

confidence: 99%

“…To further characterize each area with a single value, the CDflow was defined as the difference in the means of incoming and outgoing edge CD-s (Bányai et al, 2011b).…”

Section: Node-centric CD Representationmentioning

confidence: 99%

Section: Analysis Of the Weighted CDmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Network Path Convergence Shapes Low-Level Processing in the Visual Cortex

Varga

Soós

Jákli

et al. 2021

Front. Syst. Neurosci.

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Signal Transduction Pathways of TNAP: Molecular Network Analyses

Négyessy

Győrffy

Hanics

et al. 2015

Subcellular Biochemistry

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Despite the growing body of evidence pointing on the involvement of tissue non-specific alkaline phosphatase (TNAP) in brain function and diseases like epilepsy and Alzheimer's disease, our understanding about the role of TNAP in the regulation of neurotransmission is severely limited. The aim of our study was to integrate the fragmented knowledge into a comprehensive view regarding neuronal functions of TNAP using objective tools. As a model we used the signal transduction molecular network of a pyramidal neuron after complementing with TNAP related data and performed the analysis using graph theoretic tools. The analyses show that TNAP is in the crossroad of numerous pathways and therefore is one of the key players of the neuronal signal transduction network. Through many of its connections, most notably with molecules of the purinergic system, TNAP serves as a controller by funnelling signal flow towards a subset of molecules. TNAP also appears as the source of signal to be spread via interactions with molecules involved among others in neurodegeneration. Cluster analyses identified TNAP as part of the second messenger signalling cascade. However, TNAP also forms connections with other functional groups involved in neuronal signal transduction. The results indicate the distinct ways of involvement of TNAP in multiple neuronal functions and diseases.

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What makes the prefrontal cortex so appealing in the era of brain imaging? A network analytical perspective

Négyessy¹,

Bányai²,

Nepusz³

et al. 2012

Acta Biologica Hungarica

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It is thought that the prefrontal cortex (PFC) subserves cognitive control processes by coordinating the flow of information in the cerebral cortex. In the network of cortical areas the central position of the PFC makes difficult to dissociate processing and the cognitive function mapped to this region, especially when using whole brain imaging techniques, which can detect frequently activated regions. Accordingly, the present study showed particularly high rate of increase of published studies citing the PFC and imaging as compared to other fields of the neurosciences on the PubMed. Network measures used to characterize the role of the areas in signal flow indicated specialization of the different regions of the PFC in cortical processing. Notably, areas of the dorsolateral PFC and the anterior cingulate cortex, which received the highest number of citations, were identified as global convergence points in the network. These prefrontal regions also had central position in the dominant cluster consisted exclusively by the associational areas of the cortex. We also present findings relevant to models suggesting that control processes of the PFC are depended on serial processing, which results in bottleneck effects. The findings suggest that PFC is best understood via its role in cortical information processing.

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Organization of signal flow in directed networks

Cited by 3 publications

References 18 publications

Network Path Convergence Shapes Low-Level Processing in the Visual Cortex

Network Path Convergence Shapes Low-Level Processing in the Visual Cortex

Signal Transduction Pathways of TNAP: Molecular Network Analyses

What makes the prefrontal cortex so appealing in the era of brain imaging? A network analytical perspective

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