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Conductance-based Dynamic Causal Modeling: A mathematical review of its application to cross-power spectral densities [article]

Inês Pereira, Stefan Frässle, Jakob Heinzle, Dario Schöbi, Cao Tri Do, Moritz Gruber, Klaas E. Stephan
2021 arXiv   pre-print
Dynamic Causal Modeling (DCM) is a Bayesian framework for inferring on hidden (latent) neuronal states, based on measurements of brain activity.  ...  In this paper, we focus on one of the most advanced formulations of DCM, i.e. conductance-based DCM for cross-spectral densities, whose components are described across multiple technical papers.  ...  Acknowledgements This paper is based on the MSc thesis "DCM for anti-NMDAR encephalitis revisited -detailed model testing and simplification" by Inês Pereira at the University of Zurich and ETH Zurich  ... 
arXiv:2104.02957v1 fatcat:n2rhpi4o6jclnknlbw4rb7wpyi

Conductance-based dynamic causal modeling: A mathematical review of its application to cross-power spectral densities

Inês Pereira, Stefan Frässle, Jakob Heinzle, Dario Schöbi, Cao Tri Do, Moritz Gruber, Klaas Enno Stephan
2021
Dynamic Causal Modeling (DCM) is a Bayesian framework for inferring on hidden (latent) neuronal states, based on measurements of brain activity.  ...  In this paper, we focus on one of the most advanced formulations of DCM, i.e. conductance-based DCM for cross-spectral densities, whose components are described across multiple technical papers.  ...  Acknowledgments This paper is based on the MSc thesis "DCM for anti-NMDAR encephalitis revisited -detailed model testing and simplification "by Inês Pereira at the University of Zurich and ETH Zurich  ... 
doi:10.5167/uzh-211733 fatcat:wv52yhccvbeq7kfow2uzaulvey

Adiabatic dynamic causal modelling

Amirhossein Jafarian, Peter Zeidman, Rob. C Wykes, Matthew Walker, Karl J. Friston
2021 NeuroImage  
In this foundational paper, we describe the underlying model, establish its face validity using simulations and provide an illustrative application to a chemoconvulsant animal model of seizure activity  ...  This allows one to specify and compare models of slowly changing parameters (using Bayesian model reduction) that generate a sequence of empirical cross spectra of electrophysiological recordings.  ...  We conclude with a discussion of the limitations and potential applications of adiabatic DCM. Theory This section provides a brief review of dynamic causal modelling.  ... 
doi:10.1016/j.neuroimage.2021.118243 pmid:34116151 pmcid:PMC8350149 fatcat:rgmthiuvojffzow7pr3r5jhk4e

Neural masses and fields in dynamic causal modeling

Rosalyn Moran, Dimitris A. Pinotsis, Karl Friston
2013 Frontiers in Computational Neuroscience  
Using an identical neuronal architecture, we show that a set of conductance based models-that consider the dynamics of specific ion-channels-present a richer space of responses; owing to non-linear interactions  ...  This paper reviews the suite of neuronal population models including neural masses, fields and conductance-based models that are used in DCM.  ...  It therefore only makes sense to consider mean field treatments of conductance-based models.  ... 
doi:10.3389/fncom.2013.00057 pmid:23755005 pmcid:PMC3664834 fatcat:zvjhx44ylbdh3daetqky6lypji

Tracking slow modulations in synaptic gain using dynamic causal modelling: Validation in epilepsy

Margarita Papadopoulou, Marco Leite, Pieter van Mierlo, Kristl Vonck, Louis Lemieux, Karl Friston, Daniele Marinazzo
2015 NeuroImage  
Crucially, these changes spoke to an increase in the sensitivity of principal cells to intrinsic inhibitory afferents and a transient loss of excitatory-inhibitory balance.  ...  Bayesian model selection was used to identify the intrinsic (within-source) and extrinsic (between-source) connectivity.  ...  Dynamic causal modelling of cross spectral density can be implemented using the DCM Toolbox.  ... 
doi:10.1016/j.neuroimage.2014.12.007 pmid:25498428 pmcid:PMC4306529 fatcat:q7yss2ng2vhw7egfaoo37tdh44

Dynamic causal modelling revisited

K.J. Friston, Katrin H. Preller, Chris Mathys, Hayriye Cagnan, Jakob Heinzle, Adeel Razi, Peter Zeidman
2017 NeuroImage  
This paper revisits the dynamic causal modelling of fMRI timeseries by replacing the usual (Taylor) approximation to neuronal dynamics with a neural mass model of the canonical microcircuit.  ...  In this technical note, we describe the resulting dynamic causal model and provide an illustrative application to the attention to visual motion dataset used in previous papers.  ...  DCM for ERP or cross spectral density responses.  ... 
doi:10.1016/j.neuroimage.2017.02.045 pmid:28219774 pmcid:PMC6693530 fatcat:dpkawcek4nbndkwsq5pehtle4a

Bayesian Modelling of Induced Responses and Neuronal Rhythms

Dimitris A. Pinotsis, Roman Loonis, Andre M. Bastos, Earl K. Miller, Karl J. Friston
2016 Brain Topography  
of inter-subject variability and (ii) the construction of novel dynamic causal models of intralaminar recordings to explain layer-specific activity.  ...  We hope to show that electrophysiological measurements contain much more spatial information than is often thought: on the one hand, the dynamic causal modelling of non-invasive (low spatial resolution  ...  , and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1007/s10548-016-0526-y pmid:27718099 fatcat:pswqqxexfjbw7k46qbjxauz2ry

On conductance-based neural field models

Dimitris A. Pinotsis, Marco Leite, Karl J. Friston
2013 Frontiers in Computational Neuroscience  
This technical note introduces a conductance-based neural field model that combines biologically realistic synaptic dynamics-based on transmembrane currents-with neural field equations, describing the  ...  However, convolution and conductance-based models showed qualitatively different changes in power, with convolution models showing decreases with increasing inhibition, while conductance models show the  ...  Conductance-based models have a long history in mathematical neuroscience; for a detailed review, see (Tuckwell, 2005) .  ... 
doi:10.3389/fncom.2013.00158 pmid:24273508 pmcid:PMC3824089 fatcat:55e7ucz4ufewnnrafh4zddfvna

Dynamic causal modeling with neural fields

D.A. Pinotsis, R.J. Moran, K.J. Friston
2012 NeuroImage  
Specifically, we consider neural field models of cortical activity as generative models in the context of dynamic causal modeling (DCM).  ...  This allows us to formulate a neural field model that can be reduced to a neural mass model using appropriate constraints on its spatial parameters.  ...  We are most grateful to Professor Peter Dayan, Dr Jean Daunizeau and Dr Vladimir Litvak for useful discussions.  ... 
doi:10.1016/j.neuroimage.2011.08.020 pmid:21924363 pmcid:PMC3236998 fatcat:eeuk47vtafc6hj5yzizk2yjfoa

Computational Models in Electroencephalography

Katharina Glomb, Joana Cabral, Anna Cattani, Alberto Mazzoni, Ashish Raj, Benedetta Franceschiello
2021 Brain Topography  
The final purpose of computational models of EEG is to obtain a comprehensive understanding of the mechanisms that underlie the EEG signal.  ...  In this review, we point out the state of the art of computational modeling in Electroencephalography (EEG) and outline how these models can be used to integrate findings from electrophysiology, network-level  ...  Acknowledgements The authors would like to thank Ana Hernando  ... 
doi:10.1007/s10548-021-00828-2 pmid:33779888 pmcid:PMC8813814 fatcat:2gbjkwizhndxvksrt7fvirilia

E-pile model of self-organized criticality [article]

A. V. Milovanov (Department of Physics and Technology, University of Tromso, Tromso, Norway) K. Rypdal (Department of Physics and Technology, University of Tromso, Tromso, Norway) J. J. Rasmussen (Optics and Plasma Research Department, Technical University of Denmark, Riso National Laboratory, Roskilde, Denmark)
2007 arXiv   pre-print
Variations of the model apply to a number of other physical problems, such as electric plasma discharges, dielectric relaxation, and the dynamics of the Earth's magnetotail.  ...  We introduce a new metaphor, the e-pile model, and a formalism for electric conduction in random media to compute critical exponents for such a system.  ...  The SOC state features no intrinsic length or time scale, its fluctuations are scale-free and are characterized by an inverse powerlaw power spectral density (PSD).  ... 
arXiv:0711.4571v1 fatcat:josiobmvrjb3vmwqtarezvsi5m

Consistent spectral predictors for dynamic causal models of steady-state responses

Rosalyn J. Moran, Klaas E. Stephan, Raymond J. Dolan, Karl J. Friston
2011 NeuroImage  
In this paper, we examine the dynamic repertoires of nonlinear conductancebased neural population models and propose a generative model of their power spectra.  ...  models of neuronal dynamics.  ...  In conclusion, this paper makes two contributions to the ongoing development of dynamic causal models of electrophysiological data: it augments recent conductance-based models with an NMDA channel, and  ... 
doi:10.1016/j.neuroimage.2011.01.012 pmid:21238593 pmcid:PMC3093618 fatcat:2pv2znuexrerxfwnsynyzbwxgy

Computational models in Electroencephalography [article]

Katharina Glomb, Joana Cabral, Anna Cattani, Alberto Mazzoni, Ashish Raj, Benedetta Franceschiello
2020 arXiv   pre-print
The final purpose of computational models of EEG is to obtain a comprehensive understanding of the mechanisms that underlie the EEG signal.  ...  In this review, we point out the state of the art of computational modeling in Electroencephalography (EEG) and outline how these models can be used to integrate findings from electrophysiology, network-level  ...  Conflict of interest The authors declare that they have no conflict of interest. Authors contribution K.G. and B.F. conceived the review. J.C. and A.R. contributed to section 2.2.  ... 
arXiv:2009.08385v1 fatcat:ajypakrxxndnvlosmxu2rai4cm

Dynamic causal modelling of lateral interactions in the visual cortex

D.A. Pinotsis, D.S. Schwarzkopf, V. Litvak, G. Rees, G. Barnes, K.J. Friston
2013 NeuroImage  
This paper presents a dynamic causal model based upon neural field models of the Amari type.  ...  We consider the application of these models to non-invasive data, with a special focus on the mapping from source activity on the cortical surface to a single channel.  ...  Penny and A. Bastos for useful discussions.  ... 
doi:10.1016/j.neuroimage.2012.10.078 pmid:23128079 pmcid:PMC3547173 fatcat:ghi7v5kyybfjhjq4hix2uiklie

Computational and dynamic models in neuroimaging

Karl J. Friston, Raymond J. Dolan
2010 NeuroImage  
It builds on the distinction between models of the brain as a computational machine and computational models of neuronal dynamics per se; i.e., models of brain function and biophysics.  ...  In terms of biophysical modelling, we focus on dynamic causal modelling, with a special emphasis on recent advances in neural-mass models for hemodynamic and electrophysiological time series.  ...  We are particularly grateful to Michael Breakspear for several ideas and references.  ... 
doi:10.1016/j.neuroimage.2009.12.068 pmid:20036335 pmcid:PMC2910283 fatcat:5ntuy7bdfvau3afpxpp254romq
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