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A generative model of whole-brain effective connectivity

Stefan Frässle, Ekaterina I. Lomakina, Lars Kasper, Zina M. Manjaly, Alex Leff, Klaas P. Pruessmann, Joachim M. Buhmann, Klaas E. Stephan
2018 NeuroImage  
A generative model of whole-brain effective connectivity. NeuroImage, 179(1):505-529.  ...  The development of whole-brain models that can infer effective (directed) connection strengths from fMRI data represents a central challenge for computational neuroimaging.  ...  Estimates of effective connectivity typically derive from a generative model that provides a forward mapping from hidden (latent) neuronal circuit dynamics to observable brain signals .  ... 
doi:10.1016/j.neuroimage.2018.05.058 pmid:29807151 fatcat:hsczojmxvrhw5ceumn54v6xxaq

A generative model of whole-brain effective connectivity

Stefan Frässle, Ekaterina I. Lomakina, Lars Kasper, Zina M. Manjaly, Alex Leff, Klaas P. Prüssmann, Joachim M. Buhmann, Klaas E. Stephan
2018
The development of whole-brain models that can infer effective (directed) connection strengths from fMRI data represents a central challenge for computational neuroimaging.  ...  This demonstrates the feasibility of whole-brain inference on effective connectivity from fMRI datain single subjects and with a run-time below 1 min when using parallelized code.  ...  Estimates of effective connectivity typically derive from a generative model that provides a forward mapping from hidden (latent) neuronal circuit dynamics to observable brain signals (Friston et al.,  ... 
doi:10.3929/ethz-b-000275013 fatcat:ta2yvyoa35fhbli3yakcgwqeme

Mapping how local perturbations influence systems-level brain dynamics

Leonardo L. Gollo, James A. Roberts, Luca Cocchi
2017 NeuroImage  
We then systematically analyze a model of large-scale brain dynamics, assessing how localized changes in brain activity at the different sites affect whole-brain dynamics.  ...  Our results highlight the importance of a periphery-to-core hierarchy to determine the effect of local stimulation on the brain network.  ...  Acknowledgments This work was supported by the Australian Research Council Centre of Excellence for Integrative Brain Function (ARC Centre Grant CE140100007) (JR) and the National Health and Medical Research  ... 
doi:10.1016/j.neuroimage.2017.01.057 pmid:28126550 fatcat:u4xa2g3sv5hotdnf55fo4hbtqi

Analysis of brain subnetworks within the context of their whole‐brain networks

Mohsen Bahrami, Paul J. Laurienti, Sean L. Simpson
2019 Human Brain Mapping  
We also provide a multivariate mixed-effects modeling framework that allows analyzing subnetworks within the context of their whole-brain networks, and show that it can better disentangle global (whole-brain  ...  The provided multivariate model is an extension of a previously developed model for global, system-level hypotheses about the brain.  ...  The authors would like to thank Robert Lyday for generous computer assistance.  ... 
doi:10.1002/hbm.24762 pmid:31441167 pmcid:PMC6865778 fatcat:kxuw7szj4zgfnecmfqg2mgycrm

A deconvolution-based approach to identifying large-scale effective connectivity

Keith Bush, Suijian Zhou, Josh Cisler, Jiang Bian, Onder Hazaroglu, Keenan Gillispie, Kenji Yoshigoe, Clint Kilts
2015 Magnetic Resonance Imaging  
We then validated the ability for the proposed method to reliably detect effective connectivity in whole-brain fMRI signal parcellated into networks of viable size.  ...  We then test, both in simulation as well as whole-brain fMRI BOLD signal, the viability of this approach.  ...  Acknowledgements This work was supported in part by National Institutes of Health grants R21MH097784-01 and R01DA036360-01 as well as by as the National Science Foundation grants CRI CNS-0855248 and MRI  ... 
doi:10.1016/j.mri.2015.07.015 pmid:26248273 pmcid:PMC4658309 fatcat:aa3adnv7mzaxfpmgxgmgpnpxge

Whole-Brain Multimodal Neuroimaging Model Using Serotonin Receptor Maps Explains Non-linear Functional Effects of LSD

Gustavo Deco, Josephine Cruzat, Joana Cabral, Gitte M. Knudsen, Robin L. Carhart-Harris, Peter C. Whybrow, Nikos K. Logothetis, Morten L. Kringelbach
2018 Current Biology  
Highlights d Causal whole-brain model integrating neurotransmitter data and brain dynamics d This explains the functional effects of serotonin 2A receptor stimulation with LSD d Non-linear effects of specific  ...  brainwide distribution of neurotransmitter density d Exciting possibilities for drug discovery and design in neuropsychiatric disorders Authors  ...  Results of Whole-Brain Model of Placebo and Explaining Effects of LSD with 5HT 2A Modulation of Gain Function (A) Whole-brain fitting of the placebo condition shows the fit of grand average functional  ... 
doi:10.1016/j.cub.2018.07.083 fatcat:zyymvah2uneipcmdgeowte7z5u

Understanding principles of integration and segregation using whole-brain computational connectomics: implications for neuropsychiatric disorders

Louis-David Lord, Angus B. Stevner, Gustavo Deco, Morten L. Kringelbach
2017 Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences  
One contribution of 14 to a theme issue 'Mathematical methods in medicine: neuroscience, cardiology and pathology'. describe how the emerging discipline of whole-brain computational connectomics may be  ...  We emphasize how novel methods from network science and whole-brain computational modelling can expand beyond traditional neuroimaging paradigms and help to uncover the neurobiological determinants of  ...  Investigating disease mechanisms with whole-brain computational modelling (a) Overview of whole-brain computational models The main premise of whole-brain computational models comes from statistical physics  ... 
doi:10.1098/rsta.2016.0283 pmid:28507228 pmcid:PMC5434074 fatcat:ybywypbpevey7fvbiuzuqeceju

Great Expectations: Using Whole-Brain Computational Connectomics for Understanding Neuropsychiatric Disorders

Gustavo Deco, Morten L. Kringelbach
2014 Neuron  
This raises great expectations that whole-brain modeling and computational connectomics may provide an entry point for understanding brain disorders at a causal mechanistic level, and that computational  ...  Here our focus is on the disruption in neuropsychiatric disorders (pathoconnectomics) and how whole-brain computational models can help generate and predict the dynamical interactions and consequences  ...  The research reported herein was supported by the Brain Network Recovery Group through the James S. McDonnell Foundation.  ... 
doi:10.1016/j.neuron.2014.08.034 pmid:25475184 fatcat:kx7rohtyljc7heuahmvoqyorgq

The Effect of Aging on Brain Glucose Metabolic Connectivity Revealed by [18F]FDG PET-MR and Individual Brain Networks

Nathalie Mertens, Stefan Sunaert, Koen Van Laere, Michel Koole
2022 Frontiers in Aging Neuroscience  
Contrary to group-based brain connectivity analyses, the aim of this study was to construct individual brain metabolic networks to determine age-related effects on brain metabolic connectivity.  ...  After constructing individual brain networks, a linear and quadratic regression analysis of metabolic connectivity strengths within- and between-networks was performed to model age-dependency.  ...  To assess brain connectivity, graph theoretical methods are generally applied which model the brain using a weighted, undirected graph.  ... 
doi:10.3389/fnagi.2021.798410 pmid:35221983 pmcid:PMC8865456 fatcat:zvvq3cuvunba7kgfgmryga47iu

Effective connectivity analysis of global and local mental imagery by dynamic causal modeling

Jian Li, Danni Sui, Yi-Yuan Tang
2008 BMC Neuroscience  
Our results indicated a distinct neural pathway or effective connectivity existed in the processing of generation of global and local imagery.  ...  Effective connectivity is parameterized in terms of coupling among unobserved brain states.  ...  Acknowledgements This work was supported in part by National Natural Science Foundation of China Grant 30670699, Ministry of Education Grant NCET-06-0277 and 021010.  ... 
doi:10.1186/1471-2202-9-s1-p34 fatcat:hyszbne53ze2bpymp2456avnoq

Socioeconomic Resources are Associated with Distributed Alterations of the Brain's Intrinsic Functional Architecture in Youth [article]

Chandra Sripada, Arianna Morgan Sandmark Gard, Mike Angstadt, Aman Taxali, Tristan Greathouse, Katherine McCurry, Luke W Hyde, Alexander Weigard, Peter Walczyk, Mary Heitzeg
2022 bioRxiv   pre-print
: whole-brain, network-wise, and connection-wise.  ...  We found that parental education was the primary driver of neural effects of SER, with notable concentrations in somatosensory and subcortical regions.  ...  A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/principal-investigators.html.  ... 
doi:10.1101/2022.06.07.495160 fatcat:sti3wi4cjzboveddsrkiy5bpda

Accelerating The Virtual Brain with code generation and GPU computing

M Woodman, Viktor K Jirsa
2013 BMC Neuroscience  
has lead to the development of a whole-brain simulator, built within a freely available neuroinformatics platform called the Virtual Brain (TVB) [1] [2] [3] .  ...  of finite conduction velocities in the brain connectivity in TVB, the models remain computationally expensive.  ...  has lead to the development of a whole-brain simulator, built within a freely available neuroinformatics platform called the Virtual Brain (TVB) [1] [2] [3] .  ... 
doi:10.1186/1471-2202-14-s1-p198 pmcid:PMC3704623 fatcat:gn4rp7de4jb27lxwzs5gw3xuzi

State-Dependent Effective Connectivity in Resting-State fMRI

Hae-Jeong Park, Jinseok Eo, Chongwon Pae, Junho Son, Sung Min Park, Jiyoung Kang
2021 Frontiers in Neural Circuits  
We decomposed the state-dependent effective connectivity using a parametric empirical Bayes scheme that models the effective connectivity of consecutive windows with the time course of the discrete states  ...  We showed the plausibility of the state-dependent effective connectivity analysis in a simulation setting.  ...  of the whole-brain connectivity.  ... 
doi:10.3389/fncir.2021.719364 pmid:34776875 pmcid:PMC8579116 fatcat:ulsmgceazzha5fb5ica2gqme6u

Whole-brain estimates of directed connectivity for human connectomics [article]

Stefan Frässle, Zina-Mary Manjaly, Cao Tri Do, Lars Kasper, Klaas P Pruessmann, Klaas E Stephan
2020 bioRxiv   pre-print
Here, using a motor task at 7T, we demonstrate that a novel generative model can infer known connectivity features in a whole-brain network (>200 regions, >40,000 connections) highly efficiently.  ...  By contrast, whole-brain estimates of effective (directed) connectivity are computationally challenging, and emerging methods require empirical validation.  ...  Inversion of a large-scale circuit model reveals a cortical hierarchy in Frässle, S. et al. A generative model of whole-brain effective connectivity.  ... 
doi:10.1101/2020.02.20.958124 fatcat:kqfbxtnmifbvbgrtjsarbnn7ci

Whole-brain estimates of directed connectivity for human connectomics

Stefan Frässle, Zina M. Manjaly, Cao T. Do, Lars Kasper, Klaas P. Pruessmann, Klaas E. Stephan
2020 NeuroImage  
Here, using a motor task at 7T, we demonstrate that a novel generative model can infer known connectivity features in a whole-brain network (>200 regions, >40,000 connections) highly efficiently.  ...  By contrast, whole-brain estimates of effective (directed) connectivity are computationally challenging, and emerging methods require empirical validation.  ...  We confirm that we have provided a current, correct email address which is accessible by the Corresponding Author.  ... 
doi:10.1016/j.neuroimage.2020.117491 pmid:33115664 fatcat:ecmo2rig3fdb7jywmal3sdxofq
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