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Causality, Influence, and Computation in Possibly Disconnected Synchronous Dynamic Networks [chapter]

Othon Michail, Ioannis Chatzigiannakis, Paul G. Spirakis
2012 Lecture Notes in Computer Science  
In this work, we study the propagation of influence and computation in dynamic networks that are possibly disconnected at every instant.  ...  We show that even in dynamic networks that are disconnected at every instant information may spread as fast as in networks that are connected at every instant.  ...  Spread of Influence in Dynamic Graphs (Causal Influence) Probably the most important notion associated with a dynamic network/graph is the causal influence, which formalizes the notion of one node "influencing  ... 
doi:10.1007/978-3-642-35476-2_19 fatcat:k5grs3mew5dgxbk4fmgozhsujq

Causality, influence, and computation in possibly disconnected synchronous dynamic networks

Othon Michail, Ioannis Chatzigiannakis, Paul G. Spirakis
2014 Journal of Parallel and Distributed Computing  
In this work, we study the propagation of influence and computation in dynamic networks that are possibly disconnected at every instant.  ...  We show that even in dynamic networks that are disconnected at every instant information may spread as fast as in networks that are connected at every instant.  ...  Spread of Influence in Dynamic Graphs (Causal Influence) Probably the most important notion associated with a dynamic network/graph is the causal influence, which formalizes the notion of one node "influencing  ... 
doi:10.1016/j.jpdc.2013.07.007 fatcat:4k6rqiyrorbwvnnnwggtk64klu

Causality, Influence, and Computation in Possibly Disconnected Dynamic Networks [article]

Othon Michail, Ioannis Chatzigiannakis, Paul G. Spirakis
2012 arXiv   pre-print
In this work, we study the propagation of influence and computation in dynamic distributed systems.  ...  We drop for the first time in worst-case dynamic networks the common instantaneous connectivity assumption and require a minimal temporal connectivity.  ...  We proved that fast dissemination and computation are possible even under continuous disconnectivity.  ... 
arXiv:1206.1290v1 fatcat:xqml74ltbzcq5j67ghaj2aozye

Blocking NMDAR Disrupts Spike Timing and Decouples Monkey Prefrontal Circuits: Implications for Activity-Dependent Disconnection in Schizophrenia

Jennifer L. Zick, Rachael K. Blackman, David A. Crowe, Bagrat Amirikian, Adele L. DeNicola, Theoden I. Netoff, Matthew V. Chafee
2018 Neuron  
of NMDA receptors (NMDAR) on spike-timing dynamics in prefrontal networks of monkeys as they performed a cognitive control task measuring specific deficits in schizophrenia.  ...  In this theory, disruption of NMDAR synaptic function leads to dys-regulated timing of action potentials in prefrontal networks, accelerating synaptic disconnection through a spike-timing-dependent mechanism  ...  rhythms in cortical networks or other aspects of neural system dynamics that influence spike timing.  ... 
doi:10.1016/j.neuron.2018.05.010 pmid:29861281 pmcid:PMC6085178 fatcat:jx7qwq7crvflpaixohokcqmtyi

Higher-order hub cells involved in feedforward motifs as critical factors in epileptic network instability [article]

Darian Hadjiabadi, Matthew Lovett-Barron, Ivan Raikov, Fraser Sparks, Zhenrui Liao, Scott C. Baraban, Jure Leskovec, Attila Losonczy, Karl Deisseroth, Ivan Soltesz
2020 bioRxiv   pre-print
neurons enhanced downstream excitation and were causally linked to network instabilityHigher-order hub cells were identified in the hippocampus of chronically epileptic mice, showing similar findings  ...  Simulated perturbation of single hub neurons in the preseizure state confirmed that such traditional hub cells can exert major influence over global dynamics.  ...  Models were built on the Texas Advanced Computing Center (TACC) Frontera system.  ... 
doi:10.1101/2020.10.20.340364 fatcat:hpikxt4sdvdm7lucpvnmdijdbu

Causation entropy identifies indirect influences, dominance of neighbors and anticipatory couplings

Jie Sun, Erik M. Bollt
2014 Physica D : Non-linear phenomena  
Inference of causality is central in nonlinear time series analysis and science in general.  ...  Using dynamics of coupled oscillator networks, we show that although transfer entropy can successfully detect information flow in two processes, it often results in erroneous identification of network  ...  Acknowledgments We thank Dr Samuel Stanton from the ARO Complex Dynamics and Systems Program for his ongoing and continuous support. This work was funded by ARO Grant No. 61386-EG.  ... 
doi:10.1016/j.physd.2013.07.001 fatcat:tebynlb2ora4zia5nm5y3sjgy4

The Brain-Mind-Computer Trichotomy [chapter]

Péter Érdi
2019 Artificial Intelligence in the Age of Neural Networks and Brain Computing  
We argue that brain is a hermeneutic device, and hermeneutics is also necessary to understand situations and other's minds. Intentional dynamics is a possible method to set this unifying framework.  ...  Specifically, computational studies suggest that schizophrenia, as a "disconnection syndrome" can be interpreted as a result of broken hermeneutic circle.  ...  These include oscillatory and chaotic activity both in single neurons and in (often synchronized) neural networks, the self-organizing development and plasticity of ordered neural structures, and learning  ... 
doi:10.1016/b978-0-12-815480-9.00004-9 fatcat:qnziptielbbtfdwsxozpt2tiqe

A review of EEG and MEG for brainnetome research

Xin Zhang, Xu Lei, Ting Wu, Tianzi Jiang
2013 Cognitive Neurodynamics  
Because electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive and have outstanding temporal resolution and because they are the primary clinical techniques used to capture the dynamics  ...  Therefore, the synchronous operation of the brain's multiple regions or neuronal assemblies can be represented as a network with nodes that are interconnected by links.  ...  Acknowledgments We appreciate discussions with Rhoda E. and  ... 
doi:10.1007/s11571-013-9274-9 pmid:24624229 pmcid:PMC3945460 fatcat:6jjnffm5zfhtbgovklf45eogja

Reconstructing effective phase connectivity of oscillator networks from observations

Björn Kralemann, Arkady Pikovsky, Michael Rosenblum
2014 New Journal of Physics  
, and thus reliably reproduce the network structure.  ...  We demonstrate that by comparing the coupling functions from all possible triplets of oscillators, we are able to achieve in the reconstruction a good separation between existing and non-existing connections  ...  In both cases all values indicating causal influence were judged as significant results, see table C1 . Figure B1 .  ... 
doi:10.1088/1367-2630/16/8/085013 fatcat:gauh23rnljecrnwelgu3wbquxu

Replication Management and Optimistic Replication Challenges in Mobile Environment

Archana Sharma, Vineet Kansal
2011 International Journal of Database Management Systems  
In return, they become far more efficient and available than traditional replication algorithms that keep all the replicas consistent, especially when the network and computers are unreliable.  ...  This paper explores the various replication strategies, replication in mobile environment, benefits and challenges of optimistic replication in mobile applications.  ...  The kind of connection between base station and mobile client influences the choice of a transport media. If no network connection can be established, a disk-file-based transport has to be used.  ... 
doi:10.5121/ijdms.2011.3407 fatcat:zvsq2x3xjbclbf42oby75zorwi

The organization of physiological brain networks

C.J. Stam, E.C.W. van Straaten
2012 Clinical Neurophysiology  
Keywords: Brain networks Graph theory Small-world networks Scale-free networks Functional connectivity Synchronization Neurological disease EEG MEG MRI h i g h l i g h t s The brain can be represented  ...  as a complex network with functionally connected units at several levels that changes in neurological and psychiatric disease.  ...  These advances in the physics of synchronization influenced the possibilities for detecting and quantifying synchronization in neurophysiological data.  ... 
doi:10.1016/j.clinph.2012.01.011 pmid:22356937 fatcat:d6qeu4q46vcmpdnxqgpko3jtga

Effective phase connectivity from observations [article]

Björn Kralemann and Arkady Pikovsky and Michael Rosenblum
2014 arXiv   pre-print
, and thus reliably reproduce the network structure.  ...  We demonstrate that by comparing the coupling functions from all possible triplets of oscillators, we are able to achieve in the reconstruction a good separation between existing and non-existing connections  ...  In both cases all values indicating causal influence were judged as significant results, see Table C1 .  ... 
arXiv:1402.4331v2 fatcat:jwev7txor5ashggb6dn426pema

Dynamical complexity in small-world networks of spiking neurons

Murray Shanahan
2008 Physical Review E  
A computer model is described which is used to assess the dynamical complexity of a class of networks of spiking neurons with small-world properties.  ...  Causal density, which counts the number of independent significant interactions among a system's components, is used to assess dynamical complexity.  ...  The concept of causal density is based on that of Granger-causality [18] , which is a measure of the causal influence among the variables of a dynamical system.  ... 
doi:10.1103/physreve.78.041924 pmid:18999472 fatcat:lhq5sjvudveuxklgsaw5qcp26q

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

Bálint Varga, Bettina Soós, Balázs Jákli, Eszter Bálint, Zoltán Somogyvári, László Négyessy
2021 Frontiers in Systems Neuroscience  
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.  ...  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  ...  ZS supervised the dynamic network modeling and computation of spectral Granger causality and revised the manuscript. EB updated the binary visuo-tactile network.  ... 
doi:10.3389/fnsys.2021.645709 pmid:34108867 pmcid:PMC8181740 fatcat:bhtlpns66zdkji6g674ebosck4

Inferring Causal Networks of Dynamical Systems through Transient Dynamics and Perturbation [article]

George Stepaniants, Bingni W. Brunton, J. Nathan Kutz
2020 arXiv   pre-print
Our proposed PCI method demonstrated consistently strong performance in inferring causal relations for small (2-5 node) and large (10-20 node) networks, with both linear and nonlinear dynamics.  ...  We explore in depth a strategy to disambiguate between possible underlying causal networks by perturbing the network, where the actuations are either targeted or applied at random.  ...  All code and additional experiments can be found at https://github.com/sgstepaniants/netinf.  ... 
arXiv:2006.13154v2 fatcat:peuktohj6nfqdoya6zbodseseq
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