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The Effect of Signaling Latencies and Node Refractory States on the Dynamics of Networks [article]

Gabriel A. Silva
2019 arXiv   pre-print
When a mismatch between signal arrival times and the internal states of activated nodes occurs, it can cause a break down in the signaling dynamics of the network.  ...  The framework describes the dynamics between the offset in the latencies of propagating signals, which reflect the geometry of the edges and conduction velocities, and the internal refractory dynamics  ...  This work was supported by grants 63795EGII and N00014-15-1-2779 from the Army Research Office (ARO), United States Department of Defense, and in part from unrestricted funds to the Center for Engineered  ... 
arXiv:1804.07609v3 fatcat:2n6hqolrtvfrndlnxbinhc4eny

The prevalence of small world networks explained by modeling the competing dynamics of local signaling events in geometric networks [article]

Gabriel A. Silva
2017 arXiv   pre-print
We define a ratio between the signaling latencies on the edges of the network and the internal time it takes individual nodes to process incoming signals.  ...  A number of methods, including some from our own group, have explored how one goes about computing or predicting the dynamics of networks given information about internal models of individual nodes and  ...  The critical interplay between the latencies and timing of the signaling dynamics on the input edges and the evolving refractory state of v j explicitly determine the running summation towards threshold  ... 
arXiv:1510.08729v5 fatcat:zmhftgbjafhkteb5wyoo5ovf4a

An Optimized Structure-Function Design Principle Underlies Efficient Signaling Dynamics in Neurons

Francesca Puppo, Vivek George, Gabriel A. Silva
2018 Scientific Reports  
The complexity of these interactions are reflected in the wide variability of axon arbor morphologies and dynamical states neurons can take on.  ...  Dynamic signaling on branching axons is critical for rapid and efficient communication between neurons in the brain.  ...  Army ℝesearch Office (AℝO), United States Department of Defense (grant numbers 65375-NS and 63795EGII). And in part by unrestricted funds to the Center for Engineered Natural Intelligence (CENI).  ... 
doi:10.1038/s41598-018-28527-2 pmid:29992977 pmcid:PMC6041316 fatcat:omhf3lnvjrbkdcrqnsvpb7hmeu

Control of Synchronization Patterns in Neural-like Boolean Networks

David P. Rosin, Damien Rontani, Daniel J. Gauthier, Eckehard Schöll
2013 Physical Review Letters  
We observe a transition in the network dynamics when the refractory time of the individual systems is adjusted.  ...  When the refractory time is on the same order-of-magnitude as the mean link time delays or the heterogeneities of the link time delays, cluster synchronization patterns change, or are suppressed entirely  ...  The influence of the refractory time on the network dynamics is most prominent at the nodes with high in degree.  ... 
doi:10.1103/physrevlett.110.104102 pmid:23521258 fatcat:6f23ldk2szfxpmj6pyxnvzdbzq

Construction of edge-ordered multidirected graphlets for comparing dynamics of spatial temporal neural networks [article]

Joshua M. Roldan, Sebastian Pardo G., Vivek Kurien George, Gabriel A. Silva
2020 arXiv   pre-print
by the geometry of the structural networks and the resultant latencies involved with transfer of information.  ...  The integration and transmission of information in the brain are dependent on the interplay between structural and dynamical properties.  ...  We have shown that the interplay between temporal latencies of propagating discrete signaling events on the network relative to the internal dynamics of the individual nodes -when they become refractory  ... 
arXiv:2006.15971v1 fatcat:oum5up2ozfg3dnu4433b4c72jy

Understanding the Human Brain using Brain Organoids and a Structure-Function Theory [article]

Gabriel A Silva, Alysson R Muotri, Christopher White
2020 bioRxiv   pre-print
Physical constraints imposed on the brain can guide the analyses an interpretation of experimental data and the construction of mathematical models that attempt to make sense of how the brain works and  ...  Moreover, we show these constraints appear in canonical and novel math models of neural activity and learning, and we make the case that constraint-based modeling and use of representations can bridge  ...  A key result from considerations of the interplay between network geometry and dynamics is the refraction ratio -the ratio between the refractory period and effective latencies.  ... 
doi:10.1101/2020.07.28.225631 fatcat:3um4jycuzvap5cryq4rwkyufwu

Micro-lasers for neuromorphic computing

Venkata Anirudh Pammi, Sylvain Barbay
2020 Photoniques  
This article reviews some of the latest advances in this field using single and coupled semiconductor excitable micro-lasers.  ...  Optical spike-based computing offers speed and parallelism of optical technologies combined with a sparse way of representing information in spikes, thus with a potential for efficient brain-inspired computing  ...  But one of the neighbours is inevitably in its refractory period and does not respond to this spike whereas the other node does.  ... 
doi:10.1051/photon/202010426 fatcat:4a24wzp4nfcznoqae4e4dw6aa4

Learning without gradient descent encoded by the dynamics of a neurobiological model [article]

Vivek Kurien George, Vikash Morar, Weiwei Yang, Jonathan Larson, Bryan Tower, Shweti Mahajan, Arkin Gupta, Christopher White, Gabriel A. Silva
2021 arXiv   pre-print
We show that MNIST images can be uniquely encoded and classified by the dynamics of geometric networks with nearly state-of-the-art accuracy in an unsupervised way, and without the need for any training  ...  The success of state-of-the-art machine learning is essentially all based on different variations of gradient descent algorithms that minimize some version of a cost or loss function.  ...  and node refractory states) allow information (inputs) to be encoded by the resultant dynamics of the network.  ... 
arXiv:2103.08878v2 fatcat:6xmrkwed6vcazj4rmcwipcqsdq

Adaptive Integration in the Visual Cortex by Depressing Recurrent Cortical Circuits

Mark C. W. van Rossum, Matthijs A. A. van der Meer, Dengke Xiao, Mike W. Oram
2008 Neural Computation  
Here we explore networks with strong recurrence in a computational model and show that short-term depression of the synapses in the recurrent loops implements an adaptive filter.  ...  The adaptive properties of the model suggest that the abundant recurrent connections found in visual cortex serve to adapt the network's time constant in accordance with the stimulus and normalizes neuronal  ...  M.vR. was partly supported by the EPSRC COLAMN Grant. M.vdM. was supported by the EPSRC and MRC through the Doctoral Training Centre in Neuroinformatics.  ... 
doi:10.1162/neco.2008.06-07-546 pmid:18336081 fatcat:eqhuynjhw5cqzphirqpw72gqxm

FNS allows efficient event-driven spiking neural network simulations based on a neuron model supporting spike latency

Gianluca Susi, Pilar Garcés, Emanuele Paracone, Alessandro Cristini, Mario Salerno, Fernando Maestú, Ernesto Pereda
2021 Scientific Reports  
Among them, spiking neural networks (SNNs) make possible the simulation of neural activity at the level of single neurons, but their use is often threatened by the resources needed in terms of processing  ...  The recent Leaky Integrate-and-Fire with Latency (LIFL) spiking neuron model shows some realistic neuronal features and efficiency at the same time, a combination of characteristics that may result appealing  ...  The authors acknowledge Jose Ángel Pineda-Pardo for the structural data and giving us valuable comments on the manuscript, and Simone Renzi for the web development.  ... 
doi:10.1038/s41598-021-91513-8 pmid:34108523 fatcat:bnl6vieainhy5bltmgo5pqmrw4

Information in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depression

Valentina Onesto, Carlo Cosentino, Enzo Di Fabrizio, Mario Cesarelli, Francesco Amato, Francesco Gentile
2016 BioMed Research International  
We provide an estimate of the information in the network in bits as a function of cell density and short-term depression time.  ...  In simulations in which the posttransmission latency time is varied, we observe that information increases as the latency time decreases and, for specific configurations of the grid, it is largely enhanced  ...  Acknowledgments This work has been partially funded from the Italian Minister of Health (Project no. GR-2010-2320665).  ... 
doi:10.1155/2016/2769698 pmid:27403421 pmcid:PMC4923608 fatcat:63xv6vbtrjgodbcavi4npe5evm

fMRI in Non-human Primate: A Review on Factors That Can Affect Interpretation and Dynamic Causal Modeling Application

D. Blair Jovellar, Doris J. Doudet
2019 Frontiers in Neuroscience  
Employing a Bayesian approach, model parameters are estimated based on prior knowledge of conditions that might be related to neural and BOLD dynamics (e.g., requires empirical knowledge about the range  ...  How do anesthetics affect vascular physiology, BOLD contrast, and neural dynamics-particularly, effective communication within, and between networks?  ...  ACKNOWLEDGMENTS We are grateful to Bernard Ng, Ph.D. and Rafael von Känel, Ph.D. for the stimulating discussions and the reviewers for their detailed comments.  ... 
doi:10.3389/fnins.2019.00973 pmid:31619951 pmcid:PMC6759819 fatcat:znwfnvyftbf5lksodas2kx37bq

Computing temporal sequences associated with dynamic patterns on the C. elegans connectome [article]

Vivek Kurien George, Francesca Puppo, Gabriel A Silva
2020 bioRxiv   pre-print
To study network signaling pathways responsible for the dynamics we developed an analytic framework that constructs Temporal Sequences (TSeq), time- ordered walks of signals on graphs.  ...  We simulated the plausible dynamics resulting from the known C. elegans connectome using a recent model and theoretical analysis that computes the dynamics of neurobiological networks by focusing on how  ...  times at nodes and the subsequent effects that has.  ... 
doi:10.1101/2020.05.08.085191 fatcat:lpe7edquq5azvb7bstxj6q7bny

Are Neural Transactions in the Retina Performed by Phase Ternary Computation?

Johnson AS, Winlow W
2019 Annals of Behavioral Neuroscience  
and ganglion cells of the retina, once these cells have been activated by light falling on the cones.  ...  and a third-time dependent analogue variable, the refractory period.  ...  Acknowledgements Help and support from Dr. Salvatore Cozzalino, Dr. Gianluca Polese and Prof. Anna Di Cosmo, all from the Department of Biology, University of Naples, Federico II, Naples, Italy.  ... 
doi:10.18314/abne.v2i1.1893 fatcat:i4i2wizcqnapddbp7kjld2io44

FNS: an event-driven spiking neural network simulator based on the LIFL neuron model [article]

Gianluca Susi, Pilar Garces, Alessandro Cristini, Emanuele Paracone, Mario Salerno, Fernando Maestu, Ernesto Pereda
2020 arXiv   pre-print
a good matching between the activity of the model and that of the experimetal data.  ...  Taking advantage of the sparse character of brain-like computation, the event-driven technique could represent a way to carry out efficient simulation of large-scale Spiking Neural Networks (SNN).  ...  While the duration of the first phase depends on the network size only (number of neurons and connections of the network), the duration of the second phase also depends on the value of minimum inter-node  ... 
arXiv:1801.00864v3 fatcat:3joh3bizynb27dhtrp6wtm4srm
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