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Diffusion Microscopist Simulator: A General Monte Carlo Simulation System for Diffusion Magnetic Resonance Imaging

Chun-Hung Yeh, Benoît Schmitt, Denis Le Bihan, Jing-Rebecca Li-Schlittgen, Ching-Po Lin, Cyril Poupon, Wang Zhan
2013 PLoS ONE  
The former has the capacity to perform large-scale simulations of Brownian dynamics in the virtual environments of neural tissues at various levels of complexity, and the latter is flexible enough to synthesize  ...  , the biophysical modeling of polar cell membranes, and the high angular resolution diffusion imaging and fiber tractography of complex fiber configurations.  ...  Françoise Piguet (INSERM U745, University Paris-Descartes) for her instruction in immunostaining and to Dr. Jean-François Mangin (NeuroSpin, CEA Saclay) for his encouragement to complete this project.  ... 
doi:10.1371/journal.pone.0076626 pmid:24130783 pmcid:PMC3794953 fatcat:q4ttibokhbgs3emfm4f6g4jpjy

Cell biology: Networks, regulation, pathways [article]

Gasper Tkacik, William Bialek
2007 arXiv   pre-print
We begin with the building blocks of cellular networks, and proceed toward the different classes of models being explored, finally discussing the "design principles" which have been suggested for these  ...  This review was written for the Encyclopedia of Complexity and System Science (Springer-Verlag, Berlin, 2008), and is intended as a guide to the growing literature which approaches the phenomena of cell  ...  Our work was supported in part by NIH grants P50 GM071508 and R01 GM077599, by NSF Grants IIS-0613435 and PHY-0650617, by the Swartz Foundation, and by the Burroughs Wellcome Fund.  ... 
arXiv:0712.4385v1 fatcat:aeu72h57wnhsnb2ubrjdwbgb6a

Applications of Community Detection Techniques to Brain Graphs: Algorithmic Considerations and Implications for Neural Function

Javier O. Garcia, Arian Ashourvan, Sarah Muldoon, Jean M. Vettel, Danielle S. Bassett
2018 Proceedings of the IEEE  
, a resource of statistical measures that can be used to characterize community structure, and an appreciation of the usefulness of these approaches in uncovering behaviorally-relevant network dynamics  ...  Tools that have proven particularly useful for addressing this question are community detection approaches, which can identify communities or modules: groups of neural units that are densely interconnected  ...  D.S.B. and A.A. would also like to acknowledge support from the John D. and Catherine T. MacArthur Foundation, the Alfred P.  ... 
doi:10.1109/jproc.2017.2786710 pmid:30559531 pmcid:PMC6294140 fatcat:ipqbbzs6qfgz7om4pozjvvfmyq

Applications of community detection techniques to brain graphs: Algorithmic considerations and implications for neural function [article]

Javier O. Garcia, Arian Ashourvan, Sarah Muldoon, Jean M. Vettel, Danielle S. Bassett
2017 bioRxiv   pre-print
, a resource of statistical measures that can be used to characterize community structure, and an appreciation of the utility of these approaches in uncovering behaviorally-relevant network dynamics in  ...  Tools that have proven particularly useful for addressing this question are community detection approaches, which can be used to identify communities or modules in brain graphs: groups of neural units  ...  D.S.B. and A.A. would also like to acknowledge support from the John D. and Catherine T. MacArthur Foundation, the Alfred P.  ... 
doi:10.1101/209429 fatcat:efka3akhtnekjjfdas3irugnfy

28th Annual Computational Neuroscience Meeting: CNS*2019

2019 BMC Neuroscience  
Some efforts use neurons with intrinsic rich dynamics as observed in several experimental works of CPGs [2, 3].  ...  We have recently revealed the presence of dynamical invariants in the pyloric CPG in the form of cycle-by-cycle linear relations among specific time intervals and the instantaneous period [4].  ...  In this work we present an implementation of L2L which works on High Performance Computing (HPC) [6] for hyperparameter optimization of spiking neural networks.  ... 
doi:10.1186/s12868-019-0538-0 fatcat:3pt5qvsh45awzbpwhqwbzrg4su

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

2018 BMC Neuroscience  
the neural recordings of locust.  ...  Acknowledgement This project was supported by the GSU Brains and Behavior program Acknowledgements We would like to most importantly thank all our subjects who participated in these studies.  ...  However, the cellular structure of tissue creates a complex partition of intra-and extra-cellular spaces that are separated by a high impedance membrane.  ... 
doi:10.1186/s12868-018-0452-x pmid:30373544 pmcid:PMC6205781 fatcat:xv7pgbp76zbdfksl545xof2vzy

25th Annual Computational Neuroscience Meeting: CNS-2016

Tatyana O. Sharpee, Alain Destexhe, Mitsuo Kawato, Vladislav Sekulić, Frances K. Skinner, Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári, Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett (+597 others)
2016 BMC Neuroscience  
I will discuss theoretical results that point to functional advantages of splitting neural populations into subtypes, both in feedforward and recurrent networks.  ...  BMC Neuroscience 2016, 17(Suppl 1):A1 Neural circuits are notorious for the complexity of their organization.  ...  We propose that this mechanism may explain why so many disparate epileptic pathologies can produce similar high frequency oscillations [2].  ... 
doi:10.1186/s12868-016-0283-6 pmid:27534393 pmcid:PMC5001212 fatcat:bt45etzj2bbolfcxlxo7hlv6ju

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

2021 Journal of Computational Neuroscience  
One of the goals of neuroscience is to understand the computational principles that describe the formation of behaviorally relevant signals in the brain, as well as how these computations are realized  ...  Currently, most functional models of neural activity are based on firing rates, while the most relevant signals for inter-neuron communication are spikes.  ...  Acknowledgements Research supported by TIN2017-84,452-R, PGC2018-0 9 5 , 8 9 5 -B -I 0 0 , P I D 2 0 2 0 -1 1 4 8 6 7 R B -I 0 0 , a n d 2015-AR2Q9086.  ... 
doi:10.1007/s10827-021-00801-9 pmid:34931275 pmcid:PMC8687879 fatcat:evpmmfpaivgpxdqpive5xdgmwu

Theta phase coding in a network model of the entorhinal cortex layer II with entorhinal-hippocampal loop connections

Jun Igarashi, Hatsuo Hayashi, Katsumi Tateno
2006 Cognitive Neurodynamics  
of a retrained neural network to ensure high reliability.  ...  In this talk, I will begin with the useful behavior of NMF in EEG pattern classification, which plays a critical role in noninvasive brain computer interface (BCI).  ...  CONCLUSION We designed an element circuit for implementing PLL neural networks using the pulse-modulation approach. We verified the fundamental operation of two coupled element circuits with HSPICE.  ... 
doi:10.1007/s11571-006-9003-8 pmid:19003510 pmcid:PMC2267667 fatcat:avihqfr6a5e7tm43lythi27n3a

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3

Adam J. H. Newton, Alexandra H. Seidenstein, Robert A. McDougal, Alberto Pérez-Cervera, Gemma Huguet, Tere M-Seara, Caroline Haimerl, David Angulo-Garcia, Alessandro Torcini, Rosa Cossart, Arnaud Malvache, Kaoutar Skiker (+526 others)
2017 BMC Neuroscience  
Utilizing the sparsity of natural scenes, we derive a compressive-sensing based theoretical framework for network input reconstructions based on neuronal firing rate dynamics [1, 2].  ...  To study changes in oscillation patterns with learning, we modeled brain processing using a directed random network of phase-coupled oscillators interacting according to the Kuramoto model [1].  ...  NEST is a simulator for spiking neural network models [2] , focused on the dynamics, size and structure of neural systems by the generation of networks of single-point neurons.  ... 
doi:10.1186/s12868-017-0372-1 fatcat:q5x3vgivujgshmtthc6ki4fcfu

Simulating CXCR5 Dynamics in Complex Tissue Microenvironments

Jason Cosgrove, Kieran Alden, Jens V. Stein, Mark C. Coles, Jon Timmis
2021 Frontiers in Immunology  
From these analyses we predict that chemokine receptor signaling dynamics regulate migration in complex tissue microenvironments to a greater extent than the total numbers of receptors on the cell surface  ...  To effectively navigate complex tissue microenvironments, immune cells sense molecular concentration gradients using G-protein coupled receptors.  ...  CXCL13 Diffusion Constant A value of 7.6 ± 1.0 mm 2 s -1 was obtained using high-speed singlemolecule imaging.  ... 
doi:10.3389/fimmu.2021.703088 pmid:34557191 pmcid:PMC8452942 fatcat:7rv2ngqr6rgbbhwdyltwgo6ivm

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1

Sue Denham, Panayiota Poirazi, Erik De Schutter, Karl Friston, Ho Ka Chan, Thomas Nowotny, Dongqi Han, Sungho Hong, Sophie Rosay, Tanja Wernle, Alessandro Treves, Sarah Goethals (+90 others)
2017 BMC Neuroscience  
Utilizing the sparsity of natural scenes, we derive a compressive-sensing based theoretical framework for network input reconstructions based on neuronal firing rate dynamics [1, 2].  ...  To study changes in oscillation patterns with learning, we modeled brain processing using a directed random network of phase-coupled oscillators interacting according to the Kuramoto model [1].  ...  NEST is a simulator for spiking neural network models [2] , focused on the dynamics, size and structure of neural systems by the generation of networks of single-point neurons.  ... 
doi:10.1186/s12868-017-0370-3 fatcat:qq2cmqlotbg7vpqlqmmcql4u5i

Introduction to JINS Special Issue on Human Brain Connectivity in the Modern Era: Relevance to Understanding Health and Disease

Deanna M. Barch, Mieke Verfaellie, Stephen M. Rao
2016 Journal of the International Neuropsychological Society  
JINS Vo l u m e 2 2 , N u m b e r 2 F e b r u a r y 2 0 1 6 I S S N 1 3 5 5 -6 1 7 7  ...  Mapping human whole-brain structural networks with diffusion MRI. PLoS One, 2(7), e597.  ...  This work also involved the use of instrumentation supported by the NIH Shared Instrumentation Grant Program and/or High-End Instrumentation Grant Program; specifically, grant number(s) S10RR022976 and  ... 
doi:10.1017/s1355617716000047 fatcat:f2preenihbes5ftkrxbo7tgt64

Complex networks: Structure and dynamics

S BOCCALETTI, V LATORA, Y MORENO, M CHAVEZ, D HWANG
2006 Physics reports  
time from source to sink in a network of pipes, how to color the regions of a map using the minimum number of colors so that neighboring regions receive different colors, or how to fill n jobs by n people  ...  Coupled biological and chemical systems, neural networks, social interacting species, the Internet and the World Wide Web, are only a few examples of systems composed by a large number of highly interconnected  ...  Their sharing of very stimulating and fruitful discussions (or unpublished results on the subjects treated in this report) is largely responsible for our effort to provide a new account of this rapidly  ... 
doi:10.1016/j.physrep.2005.10.009 fatcat:us3vssqn6ngcxdi4ise2znlcdi

GPI-anchored protein organization and dynamics at the cell surface

Suvrajit Saha, Anupama Ambika Anilkumar, Satyajit Mayor
2015 Journal of Lipid Research  
Use of synthetic GPI analogues have greatly improved our understanding on the structural contribution of the anchor towards the protein's membrane behavior (5, 6) because perturbing the biosynthetic enzymes  ...  In this review, we discuss the complex nature of the organization and dynamics of GPI-anchored proteins at multiple spatial and temporal scales.  ...  Fig. 2 . 2 Single particle tracking of GPI-anchored protein. (A) Probes for single fluorescentmolecule tracking (SFMT, left) and single-particle tracking (SPT, right) as used in (55).  ... 
doi:10.1194/jlr.r062885 pmid:26394904 pmcid:PMC4727430 fatcat:cao3kx435nd5zd6iuiuwnb7nfa
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