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
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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.
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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
A New Approach to Linear Filtering and Prediction Problems
Tamer Basar
- 01 Jan 2001
TL;DR: In this paper, the clssical filleting and prediclion problem is re-examined using the Bode-Shannon representation of random processes and the?stat-tran-sition? method of analysis of dynamic systems.
22.7K
Community structure in social and biological networks
Michelle Girvan,Mark Newman +1 more
TL;DR: This article proposes a method for detecting communities, built around the idea of using centrality indices to find community boundaries, and tests it on computer-generated and real-world graphs whose community structure is already known and finds that the method detects this known structure with high sensitivity and reliability.
Complex network measures of brain connectivity: uses and interpretations.
Mikail Rubinov,Olaf Sporns +1 more
TL;DR: Construction of brain networks from connectivity data is discussed and the most commonly used network measures of structural and functional connectivity are described, which variously detect functional integration and segregation, quantify centrality of individual brain regions or pathways, and test resilience of networks to insult.
11.4K
•Proceedings Article
Gephi: An Open Source Software for Exploring and Manipulating Networks
Mathieu Bastian,Sébastien Heymann,Mathieu Jacomy +2 more
- 19 Mar 2009
TL;DR: This work presents several key features of Gephi in the context of interactive exploration and interpretation of networks, and highlights key aspects of dynamic network visualization.