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Bayesian Belief Updating of Spatiotemporal Seizure Dynamics [article]

Gerald K Cooray and Richard Rosch and Torsten Baldeweg and Louis Lemieux and Karl Friston and Biswa Sengupta
2017 arXiv   pre-print
Spatiotemporal dynamics are modelled using a partial differential equation -- in contrast to the ordinary differential equation used in our previous work on temporal estimation of seizure dynamics [Cooray  ...  Epileptic seizure activity shows complicated dynamics in both space and time. To understand the evolution and propagation of seizures spatially extended sets of data need to be analysed.  ...  Bayesian belief updating The following equations operationalize the Bayesian belief updating of the parameters as data is inverted sequentially across the windowed data, y i , see (Cooray et al., 2016  ... 
arXiv:1705.07278v2 fatcat:gmzb7fnpcvgedjbqnyfhpsazqi

Dynamic causal modelling of electrographic seizure activity using Bayesian belief updating

Gerald K. Cooray, Biswa Sengupta, Pamela K. Douglas, Karl Friston
2016 NeuroImage  
We describe the theoretical background behind a Bayesian belief updating scheme for DCM.  ...  To characterise the spatiotemporal evolution of seizure activity, large data sets often need to be analysed.  ...  Practical aspects of Bayesian belief updating A.3.1.  ... 
doi:10.1016/j.neuroimage.2015.07.063 pmid:26220742 pmcid:PMC4692455 fatcat:jwcim6klaja6tkpwgi4vnao6ra

Characterising seizures in anti-NMDA-receptor encephalitis with dynamic causal modelling

Gerald K. Cooray, Biswa Sengupta, Pamela Douglas, Marita Englund, Ronny Wickstrom, Karl Friston
2015 NeuroImage  
The spectral density of reconstructed source activity was then characterised with dynamic causal modelling (DCM).  ...  Bayesian model comparison established a role for changes in both excitatory and inhibitory connectivity during seizure activity (in addition to changes in the exogenous input).  ...  In a forthcoming study, we will compare the analysis described above with computationally efficient Bayesian belief updating schemes.  ... 
doi:10.1016/j.neuroimage.2015.05.064 pmid:26032883 pmcid:PMC4558461 fatcat:7vafr5fr6jet3ksxjmj2b6fr7q

The Bayesian Virtual Epileptic Patient: A probabilistic framework designed to infer the spatial map of epileptogenicity in a personalized large-scale brain model of epilepsy spread

M. Hashemi, A.N. Vattikonda, V. Sip, M. Guye, F. Bartolomei, M.M. Woodman, V.K. Jirsa
2020 NeuroImage  
Our results indicate that NUTS and ADVI accurately estimate the degree of epileptogenicity of brain regions, therefore, the hypothetical brain areas responsible for the seizure initiation and propagation  ...  In this technical note, we propose a probabilistic framework, namely the Bayesian Virtual Epileptic Patient (BVEP), which relies on the fusion of structural data of individuals to infer the spatial map  ...  In another study, Bayesian belief updating 868 scheme for DCM has been used to estimate the synaptic drivers of cortical 869 dynamics during a seizure from EEG/ECoG recordings with a little com-870 putational  ... 
doi:10.1016/j.neuroimage.2020.116839 pmid:32387625 fatcat:dg7y5l5szbeejdvpggru722njq

Dual mechanisms of ictal high frequency oscillations in human rhythmic onset seizures

Elliot H. Smith, Edward M. Merricks, Jyun-You Liou, Camilla Casadei, Lucia Melloni, Thomas Thesen, Daniel J. Friedman, Werner K. Doyle, Ronald G. Emerson, Robert R. Goodman, Guy M. McKhann, Sameer A. Sheth (+2 others)
2020 Scientific Reports  
HFOs are a proposed biomarker of epileptic brain tissue and may also be useful for seizure forecasting.  ...  These results describe the neuronal and synaptic correlates of two types of pathological HFOs in humans and have important implications for clinical interpretation of rhythmic onset seizures.  ...  We therefore sought to quantify the extent to which our beliefs about the hypotheses tested in these models were updated by using Bayesian analysis.  ... 
doi:10.1038/s41598-020-76138-7 pmid:33154490 fatcat:lhkral3dyjfmbl7sr5x6usd7uu

Dual mechanisms of ictal high frequency oscillations in rhythmic onset seizures [article]

Elliot H Smith, Edward Merricks, Jyun-You Liou, Camilla Casadei, Lucia Melloni, Daniel Friedman, Werner Doyle, Robert Goodman, Ronald Emerson, Guy McKhann, Sameer Sheth, John Rolston (+1 others)
2020 medRxiv   pre-print
Despite this, there has been limited investigation into the spatial context of HFOs with recruitment of local cortex into seizure discharging.  ...  , which may explain the variable utility of HFOs in seizure localization and forecasting.  ...  We therefore sought to quantify the extent to which our beliefs about the hypotheses tested in these models were updated by using Bayesian analysis.  ... 
doi:10.1101/2020.01.09.20017053 fatcat:q7hlpjasxvcvxbrzvukuke3rwa

Dual mechanisms of ictal high frequency oscillations in human rhythmic onset seizures [article]

Elliot H Smith, Edward M Merricks, Jyun-you Liou, Camilla Casadei, Lucía Melloni, Thomas Thesen, Daniel Friedman, Werner Doyle, Ronald G. Emerson, Robert Goodman, Guy M McKhann, Sameer Sheth (+2 others)
2020 bioRxiv   pre-print
We compare features of ictal discharges in both the seizure core and penumbra (spatial seizure domains defined by multiunit activity patterns).  ...  Furthermore, we tie these timing-related differences to spatial domains of seizures, showing that penumbral discharges are widely distributed and less useful for seizure localization.  ...  We therefore sought to quantify the extent to which our beliefs about the hypotheses tested in these models were updated by using Bayesian analysis.  ... 
doi:10.1101/2020.04.07.030205 fatcat:z2pvdfrqrjh53jqayigq3xukyi

Clinical Applications of Stochastic Dynamic Models of the Brain, Part I: A Primer

James A. Roberts, Karl J. Friston, Michael Breakspear
2017 Biological Psychiatry: Cognitive Neuroscience and Neuroimaging  
The dynamic evolution of systems composed of both dynamic and random effects can be studied with stochastic dynamic models (SDMs).  ...  194 Article body: 3982 Number of figures: 4 Number of tables: 0 Number of supplemental items: 1 Short title: Stochastic Dynamic Models Abstract: Biological phenomena arise through interactions between  ...  Financial disclosures The authors declare no conflicts of interest and have no financial disclosures.  ... 
doi:10.1016/j.bpsc.2017.01.010 pmid:29528293 fatcat:acdmusal4vdkpiaifdm7tdobcu

Dynamic effective connectivity in resting state fMRI

Hae-Jeong Park, Karl J. Friston, Chongwon Pae, Bumhee Park, Adeel Razi
2018 NeuroImage  
This dynamic aspect of brain connectivity has recently attracted a lot of attention in the resting state fMRI community.  ...  This work illustrates the advantage of hierarchical modelling with spDCM, in characterizing the dynamics of effective connectivity.  ...  Similar approaches have been used previously to estimate the spatiotemporal dynamics of seizure activity based on DCM for EEG; either using Bayesian belief updating (Cooray et al., 2016) or using PEB  ... 
doi:10.1016/j.neuroimage.2017.11.033 pmid:29158202 pmcid:PMC6138953 fatcat:cr5guk2tvvblnlqmny2mk6nxxm

TAPAS: An Open-Source Software Package for Translational Neuromodeling and Computational Psychiatry

Stefan Frässle, Eduardo A. Aponte, Saskia Bollmann, Kay H. Brodersen, Cao T. Do, Olivia K. Harrison, Samuel J. Harrison, Jakob Heinzle, Sandra Iglesias, Lars Kasper, Ekaterina I. Lomakina, Christoph Mathys (+9 others)
2021 Frontiers in Psychiatry  
Here, we review the different tools within TAPAS and illustrate how these may help provide a deeper understanding of neural and cognitive mechanisms of disease, with the ultimate goal of establishing automatized  ...  Psychiatry faces fundamental challenges with regard to mechanistically guided differential diagnosis, as well as prediction of clinical trajectories and treatment response of individual patients.  ...  Hierarchical belief updating via PEs plays a central role in "Bayesian brain" theories, such as predictive coding (170, 203) . Iglesias et al.  ... 
doi:10.3389/fpsyt.2021.680811 pmid:34149484 pmcid:PMC8206497 fatcat:ichfqltpdbdfflh2ozfk4lduda

Bayesian networks in neuroscience: a survey

Concha Bielza, Pedro Larrañaga
2014 Frontiers in Computational Neuroscience  
(C) The dynamic BN unfolded in time for three time slices.  ...  In this paper we review Bayesian networks and how they can be learned automatically from data by means of structure learning algorithms.  ...  ACKNOWLEDGMENTS Research partially supported by the Spanish Ministry of Economy and Competitiveness (grant TIN2013-41592-P), the Cajal Blue Brain Project (Spanish partner of the Blue Brain Project initiative  ... 
doi:10.3389/fncom.2014.00131 pmid:25360109 pmcid:PMC4199264 fatcat:2ip7hztt4fexdj5cw4a2gpmgbu

Dynamic causal modeling of hippocampal activity measured via mesoscopic voltage-sensitive dye imaging

Jiyoung Kang, Kyesam Jung, Jinseok Eo, Junho Son, Hae-Jeong Park
2020 NeuroImage  
The aim of this paper is to present a dynamic causal modeling (DCM) framework for hippocampal activity measured via voltage-sensitive dye imaging (VSDI).  ...  The proposed method was applied to model spatiotemporal patterns of accumulative responses to consecutive stimuli in separate groups of wild-type mice and epileptic aristaless-related homeobox gene (Arx  ...  The surrogate model incorporates 16 prior belief about the objective function and updates the prior with samples evaluated from 17 the function to derive a posterior and thus leads to a better approximation  ... 
doi:10.1016/j.neuroimage.2020.116755 pmid:32199955 fatcat:diy6et336fbqvl6kwa5xscsioy

Computational Neuroscience Approach to Psychiatry: A Review on Theory-driven Approaches

Ali Khaleghi, Mohammad Reza Mohammadi, Kian Shahi, Ali Motie Nasrabadi
2022 Clinical Psychopharmacology and Neuroscience  
, prediction and treatment of psychiatric disorder.  ...  Computational neuroscience approach to psychiatry integrates multiple levels and types of simulation, analysis and computation according to the different types of computational models to enhance comprehending  ...  and quantitative phenotyping in terms of attitudes and beliefs [62, 63] .  ... 
doi:10.9758/cpn.2022.20.1.26 pmid:35078946 pmcid:PMC8813324 fatcat:dlvyukxl35fixlz2auk5y6urea

29th Annual Computational Neuroscience Meeting: CNS*2020

2020 BMC Neuroscience  
Together this work contributes to our understanding of both normal neural development and the etiology of neurodevelopmental disorders.  ...  I will discuss an interdisciplinary program of mathematical and experimental work which addresses some of the computational principles underlying neural development.  ...  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

Proceedings: ISBET 200 – 14th World Congress of the International Society for Brain Electromagnetic Topography, November 19-23, 2003

Yoshio Okada
2003 Brain Topography  
Inverse methods may be classified as local vs. global, overdetermined vs. underdetermined, and instantaneous vs. spatiotemporal.  ...  We can thus present the results as dynamical statistical parameter maps (dSPMs), similar to the corresponding static maps produced in fMRI and PET.  ...  We use a dipole based spatiotemporal Bayesian inference analysis to demonstrate the use of this noise model [3] .  ... 
doi:10.1023/b:brat.0000019284.29068.8d fatcat:tpvp3dcojrczjkuzcu3xefyizy
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