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Circuit propagation delay estimation through multivariate regression-based modeling under spatio-temporal variability

Shrikanth Ganapathy, Ramon Canal, Antonio Gonzalez, Antonio Rubio
2010 2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010)  
In this paper, we present a multivariate regression based technique that computes the propagation delay of circuits subject to manufacturing process variations in the presence of temporal variations like  ...  Propagation delays which decide circuit performance are likely to suffer the most from this phenomena.  ...  In Section 4, we discuss the multivariate regression based modeling technique to compute the delay of circuits under spatio-temporal variations.  ... 
doi:10.1109/date.2010.5457167 dblp:conf/date/GanapathyCGR10 fatcat:m5lqmp6wbjfe5bismmwrgw2spa

Uncovering the Organization of Neural Circuits with Generalized Phase Locking Analysis [article]

Shervin Safavi, Theofanis I. Panagiotaropoulos, Vishal Kapoor, Juan F. Ramirez-Villegas, Nikos K. Logothetis, Michel Besserve
2020 bioRxiv   pre-print
However, assessing the overall organization of neural circuits based on multivariate data requires going beyond pairwise approaches, and remains largely unaddressed.  ...  GPLA estimates the dominant spatio-temporal distributions of field activity and neural ensembles, and the strength of the coupling between them.  ...  Then we estimate −1 by using a linear regression with unwhitned and whitened LFPs ( −1 is the × matrix of coefficient for regression).  ... 
doi:10.1101/2020.12.09.413401 fatcat:viphzu4jtncvvkfbq5o3kvfnfm

The Human Brain Encodes a Chronicle of Visual Events at each Instant of Time thanks to the Multiplexing of Traveling Waves

J-R. King, V. Wyart
2021 Journal of Neuroscience  
Dynamical modeling shows these results can be explained by a hierarchy of neural assemblies which continuously propagates multiple visual contents.  ...  Our results show that a chain of neural circuits, which consist of (i) a hidden maintenance mechanism, and (ii) an observable update mechanism, accounts for the dynamics of macroscopic brain representations  ...  Acknowledgments This work was supported by the European Union's Horizon 2020 research & innovation program under the Marie Sklodowska-Curie Grant Agreement No. 660086 (J-R.K.), as well as by the Bettencourt-Schueller  ... 
doi:10.1523/jneurosci.2098-20.2021 pmid:33811150 pmcid:PMC8387111 fatcat:lkztgu2zrzeovmebepphibuqe4

PVNet: A LRCN Architecture for Spatio-Temporal Photovoltaic PowerForecasting from Numerical Weather Prediction [article]

Johan Mathe, Nina Miolane, Nicolas Sebastien, Jeremie Lequeux
2020 arXiv   pre-print
We compare its performance to the persistence model and state-of-the-art methods.  ...  This network architecture fully leverages both temporal and spatial weather data, sampled over the whole geographical area of interest.  ...  Instead, the impact of the variables is assessed by independent experiments (Kardakos et al., 2013) of by fitting regression models like multi-regression analyses (Malvoni et al., 2013) or multivariate  ... 
arXiv:1902.01453v3 fatcat:oj7dsjndpvc4bnstqyikcgr6fy

Spiking neural networks for computer vision

Michael Hopkins, Garibaldi Pineda-García, Petruţ A. Bogdan, Steve B. Furber
2018 Interface Focus  
The resulting spatio-temporal patterns of events are then processed through networks of spiking neurons.  ...  Event-based vision sensors, and event-based processing exemplified by the SpiNNaker (Spiking Neural Network Architecture) machine, can be used to model the biological vision pathway at various levels of  ...  This allows a particular spatio-temporal pattern to be recognized through coincidence detection ( figure 3b ).  ... 
doi:10.1098/rsfs.2018.0007 pmid:29951187 pmcid:PMC6015816 fatcat:lsmbpt6sofeevktqytj2ifjzam

Propagation of BOLD Activity Reveals Task-dependent Directed Interactions Across Human Visual Cortex

Nicolás Gravel, Remco J Renken, Ben M Harvey, Gustavo Deco, Frans W Cornelissen, Matthieu Gilson
2020 Cerebral Cortex  
To explore this hypothesis, we characterize the propagation of BOLD activity across V1, V2, and V3 using a modeling approach that aims to disentangle the contributions of local activity and directed interactions  ...  It does so by estimating the effective connectivity (EC) and the excitability of a noise-diffusion network to reproduce the spatiotemporal covariance structure of the data.  ...  This model aims to reproduce the BOLD spatio temporal covariance structure.  ... 
doi:10.1093/cercor/bhaa165 pmid:32577717 fatcat:5wrrst56vfgofddvjt7qsvhvbe

Bayesian binary quantile regression for the analysis of Bachelor-to-Master transition

Cristina Mollica, Lea Petrella
2016 Journal of Applied Statistics  
methods for Predictive and Exploratory Path modeling  ...  Specialized teams Currently the ERCIM WG has over 1150 members and the following specialized teams BM: Bayesian Methodology CODA: Complex data structures and Object Data Analysis CPEP: Component-based  ...  spatio-temporal models is in modelling agricultural yield which accounts for spatial and temporal dependencies.  ... 
doi:10.1080/02664763.2016.1263835 fatcat:l5eyielgxrct7hq5ljqeej5ccy

Disrupted Thalamus White Matter Anatomy and Posterior Default Mode Network Effective Connectivity in Amnestic Mild Cognitive Impairment

Thomas Alderson, Elizabeth Kehoe, Liam Maguire, Dervla Farrell, Brian Lawlor, Rose A. Kenny, Declan Lyons, Arun L. W. Bokde, Damien Coyle
2017 Frontiers in Aging Neuroscience  
In healthy subjects, DMN and task positive network interaction are modulated by the thalamus suggesting that abnormal task-based DMN deactivation in aMCI may be a consequence of impaired thalamo-cortical  ...  We conclude that dysfunctional posterior DMN activity in aMCI is consistent with disrupted corticothalamo-cortical processing and thalamic-based dissemination of hippocampal disease agents to cortical  ...  the Strengthening the All Island Research Base programme.  ... 
doi:10.3389/fnagi.2017.00370 pmid:29167639 pmcid:PMC5682321 fatcat:kcr6vtbej5a4tlhf6yfcrot5pm

A Comparison of Approaches for High-Level Power Estimation of LUT-Based DSP Components

Ruzica Jevtic, Carlos Carreras, Domenik Helms
2008 2008 International Conference on Reconfigurable Computing and FPGAs  
The first model is a power macro-model based on the Hamming distance of input signals.  ...  The second model is an analytical high-level power model based on switching activity computation and knowledge about the component's internal structure, which has been improved to also consider additional  ...  Acknowledgements: This work was supported in part by the Spanish Ministry of Education and Science under project TEC2006-13067-C03-03.  ... 
doi:10.1109/reconfig.2008.19 dblp:conf/reconfig/JevticCH08 fatcat:gdocjhpyvrfdjbswbdmtjwbbyq

Computational modeling of observational learning inspired by the cortical underpinnings of human primates

Emmanouil Hourdakis, Panos Trahanias
2012 Adaptive Behavior  
(b) The actor-critic architecture mapped on the model of Figure 3. Figure 7 . 7 The spatio-temporal dynamics of an event as they are transformed by a liquid column.  ...  The structure of the SOM is formed, through vector quantization, during the execution phase based on the output of the forward model pathway discussed above.  ... 
doi:10.1177/1059712312445902 fatcat:e6dqfc4eg5eg7fdehldellq3wi

30th Annual Computational Neuroscience Meeting: CNS*2021–Meeting Abstracts

2021 Journal of Computational Neuroscience  
Currently, most functional models of neural activity are based on firing rates, while the most relevant signals for inter-neuron communication are spikes.  ...  Based on different distributions of PC spines for PFs and AAs, the PC received input through 110,777 PF synapses (77.08%) and 32,933 AA synapses (22.92%).  ...  Here we extended the previous model with a detailed granular layer model (Cichon & Gan, 2015 Apr) to apply input to MFs.  ... 
doi:10.1007/s10827-021-00801-9 pmid:34931275 pmcid:PMC8687879 fatcat:evpmmfpaivgpxdqpive5xdgmwu

2020 Index IEEE Transactions on Signal Processing Vol. 68

2020 IEEE Transactions on Signal Processing  
Domingos, J., +, TSP 2020 4422-4437 Modeling of Spatio-Temporal Hawkes Processes With Randomized Kernels.  ...  ., +, TSP 2020 3849-3859 Model-Driven Deep Learning for MIMO Detection. He, H., +, TSP 2020 1702-1715 Modeling of Spatio-Temporal Hawkes Processes With Randomized Kernels.  ... 
doi:10.1109/tsp.2021.3055469 fatcat:6uswtuxm5ba6zahdwh5atxhcsy

27th Annual Computational Neuroscience Meeting (CNS*2018): Part One

2018 BMC Neuroscience  
Acknowledgements We acknowledge the Initiative and Networking Fund of the Helmholtz Association, the Helmholtz Association through the Helmholtz Portfolio Theme"Supercomputing and Modeling for the Human  ...  Alliance through the Initiative and Networking Fund of the Helmholtz Association and the Helmholtz Portfolio theme "Supercomputing and Modeling for the Human Brain" and the European Union Seventh Framework  ...  Namely, we propose a variable-projection optimization approach to estimate the parameters of the multivariate (coupled) van der Pol oscillator, and demonstrate that the proposed model can accurately capture  ... 
doi:10.1186/s12868-018-0452-x pmid:30373544 pmcid:PMC6205781 fatcat:xv7pgbp76zbdfksl545xof2vzy

28th Annual Computational Neuroscience Meeting: CNS*2019

2019 BMC Neuroscience  
Activity from both the LP and PD neurons of the stomatogastric ganglion of a crab was recorded using intracellular electrodes and sent to a computer through a DAQ device.  ...  The computer then performed online event detection on the signals and forwarded this information to the robot via Bluetooth connection, accurately preserving the temporal structure of the intervals building  ...  temporal code propagation.  ... 
doi:10.1186/s12868-019-0538-0 fatcat:3pt5qvsh45awzbpwhqwbzrg4su

Causal evidence of network communication in whole-brain dynamics through a multiplexed neural code [article]

Piergiorgio Salvan, Alberto Lazari, Diego Vidaurre, Francesca Mandino, Heidi Johansen-Berg, Joanes Grandjean
2020 bioRxiv   pre-print
This theta modulation mechanism, however, is impaired in the AD model.  ...  Here, in wild-type mice and in a transgenic model (3xTgAD) of Alzheimer s Disease (AD), we use optogenetic activation of the entorhinal cortex, concurrent whole-brain fMRI, and hidden Markov modeling.  ...  model. e ) The estimated model, in terms of regression betas, were then averaged across cross-validation folds.  ... 
doi:10.1101/2020.06.09.142695 fatcat:z5czh3faarfxdmrllrqgpwamla
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