Dynamic causal modelling: A critical review of the biophysical and statistical foundations

By Jean Daunizeau, Olivier David, Klaas E. Stephan. NeuroImage, 2011

322 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/136b2f12e54a0b605f0b5dfd03126a3fa2be2238

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Citations in the corpus

Bayesian model selection for group studies - Revisited (2014, unknown): “on model parameters can be found in Daunizeau et al. (2012). Note that Bayesian model selection rests on the VB free energy approximation to the model evidence (cf.”
Attention, Uncertainty, and Free-Energy (2010, methodology): “For example, the schemes used to invert stochastic dynamic causal models of imaging time series (e.g., Daunizeau et al., 2009) use Eq.”
Observing the Observer (II): Deciding When to Decide (2010, methodology): “Thealgorithmic implementation of the variational Bayesian inversion of the response model is formally identical to that of a Dynamic Causal Model (DCM, see e.g. [19] for a recent review).”
Effective connectivity: Influence, causality and biophysical modeling (2011, unknown): “, Daunizeau et al., 2009b for a variational Bayesian scheme). As reviewed in Valdes-Sosa et al. (2009a) the main challenges are how to scale the numerics of these schemes for more realistic and extensive modeling.”
VBA: A Probabilistic Treatment of Nonlinear Models for Neurobiological and Behavioural Data (2014, background): “Dynamic causal modelling –DCMhas been specifically developed to address this question (see the seminal DCM work in [26], and a recent review in [5]).”
Wiener-Granger Causality: A well established methodology (2011, unknown): “Second, unlike WGC, DCM does not incorporate stochastic processes, though there are recent extensions of DCM in this direction (Daunizeau et al., 2011-this issue).”
Understanding DCM: Ten simple rules for the clinician (2013, unknown): “…of DCM further, as well as explore the limitations and DCMfriendly experimental design, a recent review critically evaluates these matters (Daunizeau et al., 2011a,b), and a number of electrophysiological validation studies have been published in recent years (Daunizeau et al., 2012a,b;…”
LFP and oscillations—what do they tell us? (2015, methodology): “It is an established procedure in the analysis of functional magnetic resonance timeseries [14,15] and is now used increasingly for the characterisation of electrophysiological measurements.”
Dynamic causal modeling of cortical activity from the acute to the chronic stage after stroke (2011, unknown): “However, some biophysiological and neurovascular processes are neglected in the current DCM implementation, probably because they may not be easily identified from fMRI data (Daunizeau et al., 2009).”
Analysing connectivity with Granger causality and dynamic causal modelling (2013, methodology): “However, this calls for bespoke models of the system in question [41 ].”
Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review (2019, background): “DCM is based on a general bilinear state equation that quantiﬁes how variations in neural activity in one node are aﬀected by the activation in another node under predeﬁned stimuli ( Friston et al., 2003; Stephan et al., 2010).”