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Frequency specific interactions of MEG resting state activity within and across brain networks as revealed by the multivariate interaction measure

L. Marzetti, S. Della Penna, A.Z. Snyder, V. Pizzella, G. Nolte, F. de Pasquale, G.L. Romani, M. Corbetta
2013 NeuroImage  
Resting state networks (RSNs) are sets of brain regions exhibiting temporally coherent activity fluctuations in the absence of imposed task structure.  ...  RSNs have been extensively studied with fMRI in the infra-slow frequency range (nominally b 10 −1 Hz). The topography of fMRI RSNs reflects stationary temporal correlation over minutes.  ...  This is equivalent to solving a set of eigenvalue equations. Each solution (eigenvalue) might be considered as a meaningful measure of brain interaction.  ... 
doi:10.1016/j.neuroimage.2013.04.062 pmid:23631996 pmcid:PMC3843123 fatcat:grgvyqex2vctljewbucydbfv44

Modeling & Analysis

2003 NeuroImage  
One way of solving this problem is to make extra assumptions in order to reduce the dimensionality of the parameter space.  ...  Analyses of perfusion fMRI time-series suggest that, unlike BOLD fMRI, these data do not posses significant temporal autocorrelation under the null-hypothesis [2], and therefore might be approached with  ...  The present work takes an experimental approach to this problem in order to evaluate the temporal BOLD signal.  ... 
doi:10.1016/s1053-8119(05)70006-9 fatcat:zff2suxcofbxvetfrwfwcxi3zm

The Virtual Brain Integrates Computational Modeling and Multimodal Neuroimaging

Petra Ritter, Michael Schirner, Anthony R. McIntosh, Viktor K. Jirsa
2013 Brain Connectivity  
Adding detail to these models will widen their ability to reproduce a broader range of dynamic features of the brain.  ...  This integrated framework allows the modelbased simulation, analysis, and inference of neurophysiological mechanisms over several brain scales that underlie the generation of macroscopic neuroimaging signals  ...  McDonnell Foundation (Brain Network Recovery Group JSMF22002082) granted to P.R., A.R.M., and V.J.; the German Ministry of Education and Research (Bernstein Focus State Dependencies of Learning 01GQ0971  ... 
doi:10.1089/brain.2012.0120 pmid:23442172 pmcid:PMC3696923 fatcat:i6677e3cubaqzcbikvczz2uvba

Temporal sequences of brain activity at rest are constrained by white matter structure and modulated by cognitive demands [article]

Eli J. Cornblath, Arian Ashourvan, Jason Z. Kim, Richard F. Betzel, Rastko Ciric, Azeez Adebimpe, Graham L. Baum, Xiaosong He, Kosha Ruparel, Tyler M. Moore, Ruben C. Gur, Raquel E. Gur, Russell T. Shinohara, David R. Roalf (+2 others)
2019 arXiv   pre-print
Using diffusion-weighted imaging acquired from the same subjects, we use tools from network control theory to show that linear spread of activity along white matter connections constrains the brain's state  ...  We find that specific state space trajectories, which represent temporal sequences of brain activity, are modulated by cognitive load and related to task performance.  ...  While pairwise correlation-based approaches summarize inter-regional synchrony over a period of time, cutting-edge signal-processing approaches to fMRI can provide a richer account of brain dynamics by  ... 
arXiv:1809.02849v2 fatcat:56h3alee75fu3gkvphiadwlpzm

Unifying Large- and Small-Scale Theories of Coordination

J A Scott Kelso
2021 Entropy  
on the concepts of Synergetics and nonlinear dynamics (extended Haken-Kelso-Bunz or HKB).  ...  It occurs by virtue of informational coupling among component parts and processes and can be quite specific (as when cells in the brain resonate to signals in the environment) or nonspecific (as when simple  ...  This paper is dedicated to the memory of my friend and colleague, the physicist Armin Fuchs. Conflicts of Interest: The author declares no conflict of interest.  ... 
doi:10.3390/e23050537 pmid:33925736 fatcat:byzw7krjzbhw5ewo7k52mmbvpy

Frequency-resolved dynamic functional connectivity and scale-invariant connectivity-state behavior [article]

Markus Goldhacker, Ana Maria Tomé, Mark W. Greenlee, Elmar W. Lang
2015 arXiv   pre-print
Entering dynamic functional connectivity by applying sliding window techniques on resting-state fMRI (rs-fMRI) time courses emerged from this topic.  ...  Investigating temporal variability of functional connectivity is an emerging field in connectomics.  ...  Thus, for each subject or session not only one static brain graph or one set of dynamic brain graphs can be constructed, rather brain connectomes can be resolved at various inherent frequency scales.  ... 
arXiv:1511.00964v1 fatcat:5ma7lar5cjeg7iaxtbqwxk7i2i

Modeling of Large-Scale Functional Brain Networks Based on Structural Connectivity from DTI: Comparison with EEG Derived Phase Coupling Networks and Evaluation of Alternative Methods along the Modeling Path

Holger Finger, Marlene Bönstrup, Bastian Cheng, Arnaud Messé, Claus Hilgetag, Götz Thomalla, Christian Gerloff, Peter König, Jean Daunizeau
2016 PLoS Computational Biology  
synchrony taking place with near zero or zero-phase lag.  ...  assumption of a strong structure-function relationship by simulating local node dynamics based on SC and comparing the phase relationships emerging from the simulated neural activity with empirically  ...  Interpretation of results and revising the work: AM CH HF MB BC PK CG GT. Wrote the paper: HF MB PK.  ... 
doi:10.1371/journal.pcbi.1005025 pmid:27504629 pmcid:PMC4978387 fatcat:jpnwdabqfrb7digbnbap2fiyke

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  
Part of this complexity is related to the number of different cell types that work together to encode stimuli.  ...  BMC Neuroscience 2016, 17(Suppl 1):A1 Neural circuits are notorious for the complexity of their organization.  ...  Acknowledgements: The work of JB, RG, and SMC was supported in part by R01MH1006674 from the National Institutes of Health.  ... 
doi:10.1186/s12868-016-0283-6 pmid:27534393 pmcid:PMC5001212 fatcat:bt45etzj2bbolfcxlxo7hlv6ju

29th Annual Computational Neuroscience Meeting: CNS*2020

2020 BMC Neuroscience  
Deep RL offers a rich framework for studying the interplay among learning, representation and decision-making, offering to the brain sciences a new set of research tools and a wide range of novel hypotheses  ...  by visual experience, and (iii) how patterns of neural activity in the zebrafish brain develop to facilitate precisely targeted hunting behaviour.  ...  Acknowledgements: This research is funded by the National Science Foundation (grants #1822517 and #1921515 to SJ), the National Institute of Mental Health (grant #MH117488 to SJ), the California Nano-Systems  ... 
doi:10.1186/s12868-020-00593-1 pmid:33342424 fatcat:edosycf35zfifm552a2aogis7a

Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis

Luigi A. Maglanoc, Tobias Kaufmann, Rune Jonassen, Eva Hilland, Dani Beck, Nils Inge Landrø, Lars T. Westlye
2019 Human Brain Mapping  
Multimodal fusion of brain imaging data alone may not be sufficient for dissecting the clinical and neurobiological heterogeneity of depression.  ...  Precise clinical stratification and methods for brain phenotyping at the individual level based on large training samples may be needed to parse the neuroanatomy of depression.  ...  ), the Department of Psychology, University of Oslo and the KG Jebsen Stiftelsen (223723).  ... 
doi:10.1002/hbm.24802 pmid:31571370 fatcat:g7y765irerdihhx4mx64nehug4

Binding under Conflict Conditions: State–Space Analysis of Multivariate EEG Synchronization

Maria G. Knyazeva, Cristian Carmeli, Eleonora Fornari, Reto Meuli, Michael Small, Richard S. Frackowiak, Philippe Maeder
2011 Journal of Cognitive Neuroscience  
The effect of perception manifested itself as reciprocal modulations over the posterior and anterior regions (theta/beta-gamma bands).  ...  the frontal networks of sensory memory  ...  Yet the brain "effortlessly" solves the so-called binding problem-that is, it segregates elements in complex scenes and integrates features that belong to the same object.  ... 
doi:10.1162/jocn.2010.21588 pmid:20946055 fatcat:7w62ae2bm5b7na4e2rbqi43qeu

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  
This work was supported by the BRAINS RO1 (to S.A.L.; MH 091811). ACKNOWLEDGMENTS The authors report no conflicts of interest.  ...  Medial prefrontal cortex and self-referential mental activity: Relation to a default mode of brain function.  ...  mode network (DMN) as mapped in healthy subjects with task-free fMRI ).  ... 
doi:10.1017/s1355617716000047 fatcat:f2preenihbes5ftkrxbo7tgt64

Mathematical Frameworks for Oscillatory Network Dynamics in Neuroscience

Peter Ashwin, Stephen Coombes, Rachel Nicks
2016 Journal of Mathematical Neuroscience  
There are also surprises in the dynamical complexity of the attractors that can robustly appear - for example, heteroclinic network attractors.  ...  In this review we present a set of mathematical tools that are suitable for addressing the dynamics of oscillatory neural networks, broadening from a standard phase oscillator perspective to provide a  ...  Acknowledgements We would like to thank many people for commenting on draft versions of the manuscript, in particular Chris Bick, Áine Byrne, Kurtis Gibson, Diego Pázo, Mason Porter and Kyle Wedgwood.  ... 
doi:10.1186/s13408-015-0033-6 pmid:26739133 pmcid:PMC4703605 fatcat:m2sisazz2ndqvb76b23kivib7m

The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields

Gustavo Deco, Viktor K. Jirsa, Peter A. Robinson, Michael Breakspear, Karl Friston, Olaf Sporns
2008 PLoS Computational Biology  
Modeling at the single neuron level is necessary because this is the level at which information is exchanged between the computing elements of the brain; the neurons.  ...  Macroscopic models can inform us about whole brain dynamics and interactions between large-scale neural systems such as cortical regions, the thalamus, and brain stem.  ...  We thank the attendees of Session IV at BCW2006* for the interesting discussions, which represent the source of inspiration for the present review.  ... 
doi:10.1371/journal.pcbi.1000092 pmid:18769680 pmcid:PMC2519166 fatcat:lh4lwlajdzdhzdqwm7ecaxo4zi

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  
However, the dynamics and mechanisms generating them depend on properties of the inhibitory network.  ...  The KnowledgeSpace also represents an important component of the Neuroinformatics Platform being deployed in the Human Brain Project web portal.  ...  problem of temporally overlapping spikes.  ... 
doi:10.1186/s12868-017-0370-3 fatcat:qq2cmqlotbg7vpqlqmmcql4u5i
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