Subspace-based Identification Algorithm for characterizing causal networks in resting brain
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TL;DR: A novel state-space system identification approach for studying causal interactions among brain regions in the absence of explicit cognitive task is introduced, and the Subspace-based Identification Algorithm (SIA) is sufficiently robust against above-mentioned factors, and can reliably uncover the underlying causal interactions of resting-state fMRI.
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About: This article is published in NeuroImage. The article was published on 02 Apr 2012. and is currently open access. The article focuses on the topics: Resting state fMRI & Causal inference.
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Citations
A blind deconvolution approach to recover effective connectivity brain networks from resting state fMRI data
Guo-Rong Wu,Wei Liao,Sebastiano Stramaglia,Jurong Ding,Jurong Ding,Huafu Chen,Daniele Marinazzo +6 more
TL;DR: In this article, a blind deconvolution technique for BOLD-fMRI signal is proposed, where point processes corresponding to signal fluctuations with a given signature are individuated, and a region-specific hemodynamic response function (HRF) is extracted and used to deconvolve BOLD signal.
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TL;DR: The ADHD‐200 Preprocessed release was the first large public resource of preprocessed resting‐state fMRI and structural MRI data, and remains to this day the only resource featuring a battery of alternative processing paths.
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•Posted Content
A blind deconvolution approach to recover effective connectivity brain networks from resting state fMRI data
Guo-Rong Wu,Wei Liao,Sebastiano Stramaglia,Jurong Ding,Jurong Ding,Huafu Chen,Daniele Marinazzo +6 more
TL;DR: This work considers resting fMRI as 'spontaneous event-related', individuate point processes corresponding to signal fluctuations with a given signature, extract a region-specific HRF and use it in deconvolution, after following an alignment procedure.
Models of communication and control for brain networks: distinctions, convergence, and future outlook
Pragya Srivastava,Erfan Nozari,Jason Z. Kim,Harang Ju,Dale Zhou,Cassiano O. Becker,Fabio Pasqualetti,Danielle S. Bassett +7 more
TL;DR: In this paper, the authors explicitly bridge computational models of communication and principles of network control in a conceptual review of the current literature and highlight the convergence of and distinctions between the two frameworks.
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Novel Experimental and Analysis Paradigms for Neuroimaging
wenjing Yan
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TL;DR: Results are relevant for the understanding of hemodynamic and neurochemical aberrations in ASD, as well as have methodological implications for resting state functional connectivity studies in Autism and more generally in disorders that are accompanied by neurochemical alterations that may impact HRF shape.
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References
Modulation of functional connectivity during the resting state and the motor task.
TL;DR: The existence of a large organized functional connectivity network related to motor function in the resting brain with fMRI is shown and it is found that such a network can be modulated from a conscious resting state to planning, initiation, coordination, guidance, and termination of voluntary movement state.
Subspace identification of multivariable linear parameter-varying systems
Vincent Verdult,Michel Verhaegen +1 more
TL;DR: A subspace identification method that deals with multivariable linear parameter-varying state-space systems with affine parameter dependence and an efficient selection algorithm that does not require the formation of the complete data matrices, but processes them row by row.
222
Evaluating the effective connectivity of resting state networks using conditional Granger causality
Wei Liao,Dante Mantini,Zhiqiang Zhang,Zhengyong Pan,Jurong Ding,Qiyong Gong,Yihong Yang,Huafu Chen +7 more
TL;DR: This work identified that self-referential and default-mode networks (DMNs) play distinct and crucial roles in the human brain functional architecture and revealed the causal influences among these RSNs at different processing levels, and supplied information for a deeper understanding of the brain network dynamics.
215
Effect of hemodynamic variability on Granger causality analysis of fMRI
TL;DR: It is found that, in the absence of HRF confounds, even tens of milliseconds of neuronal delays can be inferred from fMRI, and faster sampling and low measurement noise improved the sensitivity of GC analysis of fMRI data to neuronal causality.
207
Altered Effective Connectivity Network of the Amygdala in Social Anxiety Disorder: A Resting-State fMRI Study
Wei Liao,Changjian Qiu,Claudio Gentili,Martin Walter,Zhengyong Pan,Jurong Ding,Wei Zhang,Qiyong Gong,Huafu Chen +8 more
TL;DR: This study is the first to reveal a network of abnormal effective connectivity of core structures in SAD and lends neurobiological support towards cognitive models considering disinhibition and an attentional bias towards negative stimuli as a core feature of the disorder.
191