Detection of directed information flow in biosignals

Winterhalder, Matthias; Schelter, Björn; Hesse, Wolfram; Schwab, Karin; Leistritz, Lutz; Timmer, Jens; Witte, Herbert

doi:10.1515/bmt.2006.058

Cited by 17 publications

(8 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The use of PDC analyses is growing in literature (Winterhalder et al, 2006; Sato et al, 2009); it has been validated in real neurophysiological data (Fanselow et al, 2001; Wang et al, 2003, 2004, 2008; Winterhalder et al, 2005; Huang et al, 2006) as well as in several theoretical studies using simulated data (Sameshima and Baccalá, 1999; Baccala and Sameshima, 2001; Schelter et al, 2006a,b; Takahashi et al, 2010), to demonstrate expected changes in brain networks that other less complex methods had failed to identify. As examples, PDC was able to uncover dopaminergic-dependent changes in connectivity between visual and motor areas in Parkinson patients that were undetectable by traditional spectral analysis (Tropini et al, 2011), and it was used to identify the directionality of widespread oscillatory brain interactions during visual object processing in the recognition of familiar vs. unfamiliar objects (Supp et al, 2007).…”

Section: Discussionmentioning

confidence: 99%

Dynamics of circadian thalamocortical flow of information during a peripheral neuropathic pain condition

Cardoso‐Cruz

Sameshima

Lima

et al. 2011

Front. Integr. Neurosci.

View full text Add to dashboard Cite

It is known that the thalamocortical loop plays a crucial role in the encoding of sensory–discriminative features of painful stimuli. However, only a few studies have addressed the changes in thalamocortical dynamics that may occur after the onset of chronic pain. Our goal was to evaluate how the induction of chronic neuropathic pain affected the flow of information within the thalamocortical loop throughout the brain states of the sleep–wake cycle. To address this issue we recorded local field potentials (LFPs) – both before and after the establishment of neuropathic pain in awake freely moving adult rats chronically implanted with arrays of multielectrodes in the lateral thalamus and primary somatosensory cortex. Our results show that the neuropathic injury induced changes in the number of wake and slow-wave-sleep (SWS) state episodes, and especially in the total number of transitions between brain states. Moreover, partial directed coherence – analysis revealed that the amount of information flow between cortex and thalamus in neuropathic animals decreased significantly, indicating that the overall thalamic activity had less weight over the cortical activity. However, thalamocortical LFPs displayed higher phase-locking during awake and SWS episodes after the nerve lesion, suggesting faster transmission of relevant information along the thalamocortical loop. The observed changes are in agreement with the hypothesis of thalamic dysfunction after the onset of chronic pain, and may result from diminished inhibitory effect of the primary somatosensory cortex over the lateral thalamus.

show abstract

Section: Discussionmentioning

confidence: 99%

Dynamics of circadian thalamocortical flow of information during a peripheral neuropathic pain condition

Cardoso‐Cruz

Sameshima

Lima

et al. 2011

Front. Integr. Neurosci.

View full text Add to dashboard Cite

show abstract

“…This enables the determination of directed causal interactions between two signals in relation to all other signals of the analysed system by applying on a MAR model using the transfer matrix to describe the causal information transfer [20,24]. Moreover, DTF measures both direct and indirect effects from one series to another, and for this reason, a differentiation between direct and indirect causal interactions or both is not possible, thereby leading to a greater number of interactions than are actually present [25]. The DTF is normalized such that describes the ratio between the inflow from signal 2 to signal 1, to all the inflows of the activity to the destination signal 1.…”

Section: (I) Linear Methodsmentioning

confidence: 99%

Cardiovascular and cardiorespiratory coupling analyses: a review

Schulz

Adochiei

Edu

et al. 2013

Phil. Trans. R. Soc. A.

145

127

View full text Add to dashboard Cite

Recently, methods have been developed to analyse couplings in dynamic systems. In the field of medical analysis of complex cardiovascular and cardiorespiratory systems, there is growing interest in how insights may be gained into the interaction between regulatory mechanisms in healthy and diseased persons. The couplings within and between these systems can be linear or nonlinear. However, the complex mechanisms involved in cardiovascular and cardiorespiratory regulation very likely interact with each other in a nonlinear way. Recent advances in nonlinear dynamics and information theory have allowed the multivariate study of information transfer between time series. They therefore might be able to provide additional diagnostic and prognostic information in medicine and might, in particular, be able to complement traditional linear coupling analysis techniques. In this review, we describe the approaches (Granger causality, nonlinear prediction, entropy, symbolization, phase synchronization) most commonly applied to detect direct and indirect couplings between time series, especially focusing on nonlinear approaches. We will discuss their capacity to quantify direct and indirect couplings and the direction (driver–response relationship) of the considered interaction between different biological time series. We also give their basic theoretical background, their basic requirements for application, their main features and demonstrate their usefulness in different applications in the field of cardiovascular and cardiorespiratory coupling analyses.

show abstract

“…Comparisons between the GGC statistic, the DTF, and the PDC are discussed in Eichler, Baccalà and Sameshima, Gourévitch et al, Pereda et al, Winterhalder et al, and more recently in the context of information theory in Chicharro . The causal interpretation of the PDC and the GGC, at least in the bivariate case, relies on Granger's definition of causality .…”

Section: Frequency‐domain Causalitymentioning

confidence: 99%

Time, frequency, and time‐varying Granger‐causality measures in neuroscience

Cekic

Grandjean

Renaud

2018

Statistics in Medicine

View full text Add to dashboard Cite

This article proposes a systematic methodological review and an objective criticism of existing methods enabling the derivation of time, frequency, and time-varying Granger-causality statistics in neuroscience. The capacity to describe the causal links between signals recorded at different brain locations during a neuroscience experiment is indeed of primary interest for neuroscientists, who often have very precise prior hypotheses about the relationships between recorded brain signals. The increasing interest and the huge number of publications related to this topic calls for this systematic review, which describes the very complex methodological aspects underlying the derivation of these statistics. In this article, we first present a general framework that allows us to review and compare Granger-causality statistics in the time domain, and the link with transfer entropy. Then, the spectral and the time-varying extensions are exposed and discussed together with their estimation and distributional properties. Although not the focus of this article, partial and conditional Granger causality, dynamical causal modelling, directed transfer function, directed coherence, partial directed coherence, and their variant are also mentioned.

show abstract

Detection of directed information flow in biosignals

Cited by 17 publications

References 13 publications

Dynamics of circadian thalamocortical flow of information during a peripheral neuropathic pain condition

Dynamics of circadian thalamocortical flow of information during a peripheral neuropathic pain condition

Cardiovascular and cardiorespiratory coupling analyses: a review

Time, frequency, and time‐varying Granger‐causality measures in neuroscience

Contact Info

Product

Resources

About