Dynamic causal modelling

Friston, Karl J.; Harrison, L.; Penny, Will D.

doi:10.1016/s1053-8119(03)00202-7

Cited by 4,197 publications

(4,315 citation statements)

References 19 publications

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“…DCM uses a deterministic model of neural dynamics in a network of interacting brain areas to provide Bayesian estimates of the effective strength of synaptic connections among neuronal populations and modulatory effect of experimental manipulations as well as model evidence (Friston, et al, 2003; Penny, et al, 2004). Specifically, DCM uses a differential equation ẋ =( A+uB ) x+Cu where × is a vector of the neuronal states summarizing the activity of regions of interests (ROIs) and u is a vector representing external or experimental input.…”

Section: Methodsmentioning

confidence: 99%

“…Numbers represent empathetic pain-related modulation of connectivity (log-scale parameters in the leading diagonal of the B connectivity matrix (Friston, et al, 2003; Penny, et al, 2004). (B) ASD group showed greater disinhibition in the AIC modulated by empathetic pain, compared to HC group.…”

Section: Figurementioning

confidence: 99%

“…Importantly, we modeled interoceptive precision in terms of the modulatory effect exerted by experimental context (i.e. viewing others’ pain) on the within-area self-connection of AIC using dynamic causal modelling (DCM) of the fMRI data (Friston, et al, 2003; Penny, et al, 2004). The self-connection of a given neural region is assumed to be negative so that its activity returns to equilibrium levels; thereby modelling cortical gain control.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, changes in self-disinhibition reflect changes in gain (or precision) following experimental manipulations. Using DCM, we also modeled the directed interactions among the LPFC, AIC, and EBA, and estimated how experimental context modulates directed connections among these cortical areas (Friston, et al, 2003; Penny, et al, 2004; Stephan, et al, 2010) to test a competing hypothesis that decreased precision at the higher level of LPFC and decreased top-down connectivity from the LPFC to AIC, rather than increased interoceptive precision, contributes to empathy deficits in ASD. Our hypothesis makes a number of specific predictions: individuals with ASD would show (1) disinhibited (peripheral) autonomic responses to arousing empathetic pain stimuli; (2) disinhibited or increased cortical response to empathetic pain in brain regions subserving interoceptive and autonomic processes, such as the AIC; and (3) greater modulation of self-connectivity within the AIC by empathetic pain.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Autonomic and brain responses associated with empathy deficits in autism spectrum disorder

Eilam‐Stock

Zhou

et al. 2015

Human Brain Mapping

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110

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Accumulating evidence suggests that autonomic signals and their cortical representations are closely linked to emotional processes, and that related abnormalities could lead to social deficits. Although socio-emotional impairments are a defining feature of autism spectrum disorder (ASD), empirical evidence directly supporting the link between autonomic, cortical, and socio-emotional abnormalities in ASD is still lacking. In this study, we examined autonomic arousal indexed by skin conductance responses (SCR), concurrent cortical responses measured by functional magnetic resonance imaging, and effective brain connectivity estimated by dynamic causal modeling, in seventeen un-medicated high-functioning adults with ASD and seventeen matched controls, while they performed an empathy-for-pain task. Compared to controls, adults with ASD showed enhanced SCR related to empathetic pain, along with increased neural activity in the anterior insular cortex, although their behavioral empathetic pain discriminability was reduced and overall SCR was decreased. ASD individuals also showed enhanced correlation between SCR and neural activities in the anterior insula. Importantly, significant group differences in effective brain connectivity were limited to greater reduction in the negative intrinsic connectivity of the anterior insular cortex in the ASD group, indicating a failure in attenuating anterior insular responses to empathetic pain. These results suggest that aberrant interoceptive precision, as indexed by abnormalities in autonomic activity and its central representations, may underlie empathy deficits in ASD.

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Section: Methodsmentioning

confidence: 99%

Section: Figurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Autonomic and brain responses associated with empathy deficits in autism spectrum disorder

Eilam‐Stock

Zhou

et al. 2015

Human Brain Mapping

100

110

View full text Add to dashboard Cite

show abstract

“…Task effects on functional connectivity can be addressed with tools such as psychophysiological interactions (PPI) analysis [Friston et al, 1997; O'Reilly et al, 2012] which reveals task induced changes in connectivity within a GLM framework. The framework of Dynamic Causal Modeling [Friston et al, 2003] can also indicate that connectivity between two brain regions is modulated by an external stimulus or condition such as attention [Penny et al, 2004]. However, to our knowledge there is no other measure of functional connectivity that directly quantifies the specific content of communication as DFI does, and so it represents a transformative perspective for network‐based analysis of neuroimaging data.…”

Section: Review Of Information Theory For Neuroimagingmentioning

confidence: 99%

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula

Ince

Giordano

Kayser

et al. 2016

Human Brain Mapping

282

298

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We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open‐source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541–1573, 2017. © 2016 Wiley Periodicals, Inc.

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Disordered Corticolimbic Interactions During Affective Processing in Children and Adolescents at Risk for Schizophrenia Revealed by Functional Magnetic Resonance Imaging and Dynamic Causal Modeling

Diwadkar

Wadehra

Pruitt

et al. 2012

Arch Gen Psychiatry

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Dynamic causal modelling

Cited by 4,197 publications

References 19 publications

Autonomic and brain responses associated with empathy deficits in autism spectrum disorder

Autonomic and brain responses associated with empathy deficits in autism spectrum disorder

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula

Disordered Corticolimbic Interactions During Affective Processing in Children and Adolescents at Risk for Schizophrenia Revealed by Functional Magnetic Resonance Imaging and Dynamic Causal Modeling

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