On the Detection of Direct Directed Information Flow in fMRI

Mader, Wolfgang; Feess, David; Lange, Rüdiger; Saur, Dorothee; Glauche, V.; Weiller, C.; Timmer, Jens; Schelter, Björn

doi:10.1109/jstsp.2008.2008260

Cited by 19 publications

(14 citation statements)

References 15 publications

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“…For computational details on the dPC method we refer to recent publications by Mader et al (2008) and Saur et al (2010). In short, dPC is an approach in the time domain quantifying Granger-causality, which enables a hypothesis-free exploration of networks in the sense that once the network nodes are defined, no further prior assumptions about the functional network structure are necessary (Eichler, 2005).…”

Section: Methodsmentioning

confidence: 99%

Network modulation during complex syntactic processing

et al. 2012

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Complex sentence processing is supported by a left-lateralized neural network including inferior frontal cortex and posterior superior temporal cortex. This study investigates the pattern of connectivity and information flow within this network. We used fMRI BOLD data derived from 12 healthy participants reported in an earlier study (Thompson, C. K., Den Ouden, D. B., Bonakdarpour, B., Garibaldi, K., & Parrish, T. B. (2010b). Neural plasticity and treatment-induced recovery of sentence processing in agrammatism. Neuropsychologia, 48(11), 3211-3227) to identify activation peaks associated with object-cleft over syntactically less complex subject-cleft processing. Directed Partial Correlation Analysis was conducted on time series extracted from participant-specific activation peaks and showed evidence of functional connectivity between four regions, linearly between premotor cortex, inferior frontal gyrus, posterior superior temporal sulcus and anterior middle temporal gyrus. This pattern served as the basis for Dynamic Causal Modeling of networks with a driving input to posterior superior temporal cortex, which likely supports thematic role assignment, and networks with a driving input to inferior frontal cortex, a core region associated with syntactic computation. The optimal model was determined through both frequentist and Bayesian model selection and turned out to reflect a network with a primary drive from inferior frontal cortex and modulation of the connection between inferior frontal and posterior superior temporal cortex by complex sentence processing. The winning model also showed a substantive role for a feedback mechanism from posterior superior temporal cortex back to inferior frontal cortex. We suggest that complex syntactic processing is driven by word-order analysis, supported by inferior frontal cortex, in an interactive relation with posterior superior temporal cortex, which supports verb argument structure processing.

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Section: Methodsmentioning

confidence: 99%

Network modulation during complex syntactic processing

et al. 2012

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“…The diagnostic tools used here are applicable to a broad class of systems, for inferring their network structures. As discussed in the Introduction, PDC has been successfully applied, for example, to fMRI data for the detection of directed information flow [10]; and classical Granger…”

Section: Discussionmentioning

confidence: 99%

“…Partial directed coherence (PDC) [7,8] is a frequency-domain representation of the concept of Granger causality [9]. More recently, renormalised partial directed coherence (rPDC) was introduced to allow interpretation of the strength of connections [10,11]. In combination with state space modelling [12] rPDC can cope with noisy data.…”

Section: Introductionmentioning

confidence: 99%

Inferring directed climatic interactions with renormalized partial directed coherence and directed partial correlation

Tirabassi

Sommerlade

Masoller

2017

Chaos: An Interdisciplinary Journal of Nonlinear Science

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Inferring interactions between processes promises deeper insight into mechanisms underlying network phenomena. Renormalised partial directed coherence (rPDC) is a frequencydomain representation of the concept of Granger causality while directed partial correlation (DPC) is an alternative approach for quantifying Granger causality in the time domain.Both methodologies have been successfully applied to neurophysiological signals for detecting directed relationships. This paper introduces their application to climatological time series. We first discuss the application to ENSO -Monsoon interaction, and then apply the methodologies to the more challenging air-sea interaction in the South Atlantic Convergence Zone (SACZ). While in the first case the results obtained are fully consistent with present knowledge in climate modeling, in the second case the results are, as expected, less clear, and to fully elucidate the SACZ air-sea interaction, further investigations on the specificity and sensitivity of these methodologies are needed.

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“…Thus, two processes can be correlated even if there is no direct, causal connection. Since this influence is instantaneous in time, this correlation should be referred to as instantaneous interaction (Eichler, 2006;Mader et al, 2008), sometimes misleadingly also called instantaneous causality. Note that without investigating the covariance matrix instantaneous interactions cannot be dealt with.…”

Section: Partial Directed Coherencementioning

confidence: 99%