Decoding brain states from fMRI connectivity graphs

By Jonas Richiardi, Hamdi Eryilmaz, Sophie Schwartz, Patrik Vuilleumier, D. Van de Ville. NeuroImage, 2011

331 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/797c91792a6c47d0fd21754c687d0d239a8798d7

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In Cognitive Neuroscience

Citations in the corpus

Dynamic reconfiguration of human brain networks during learning (2010, methodology): “This could be done using statistical methods [58], machine-learning techniques [59], or a combination of the two [60].”
Benchmarking functional connectome‐based predictive models for resting‐state fMRI (2019, positive): “…brain functional connectome are used to characterize individual subjects behavior, cognition, and mental health (Craddock et al., 2009; Richiardi et al., 2010; Milazzo et al., 2014; Smith et al., 2015; Miller et al., 2016; Colclough et al., 2017; Dubois et al., 2018), aging (Liem et…”
Tracking whole-brain connectivity dynamics in the resting state. (2014, neutral): “…exico on D ecem ber 11, 2012 http://cercor.oxfordjournals.org/ D ow nloaded from experimental manipulations of subjects’ internal states, to permit the mapping (and decoding) of cognitive states from connectivity data (e.g., Richiardi et al. 2011; Gonzalez-Castillo et al. 2012; Shirer et al. 2012).”
Metric learning with spectral graph convolutions on brain connectivity networks (2018, methodology): “Hence, graph embedding has been widely used to estimate brain network similarity (Dosenbach et al., 2010; Richiardi et al., 2011; Zeng et al., 2012; Abraham et al., 2017), although it often discards valuable information about the graph structure.”
Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest (2013, background): “…(FC), is modulated by learning (Bassett et al., 2011), cognitive and affective states (Cribben et al., 2012; Ekman et al., 2012; Eryilmaz et al., 2011; Richiardi et al., 2011; Shirer et al., 2012) and also spontaneously (Britz et al., 2010; Chang and Glover, 2010; Kitzbichler et al., 2009).”
Analytic estimation of statistical significance maps for support vector machine based multi-variate image analysis and classification (2013, neutral): “…Fan et al., 2007; Klöppel et al., 2008; Koutsouleris et al., 2009; Langs et al., 2011; Mingoia et al., 2012; Mouro-Miranda et al., 2005; Pereira et al., 1998; Richiardi et al., 2011; Sabuncu and Van Leemput, 2011; Vemuri et al., 2008; Venkataraman et al., 2012; Wang et al., 2007; Xu et al., 2009).”
Cognitive Network Neuroscience (2015, background): “…a new set of features that can be used to decode healthy brain states (Mokhtari & Hossein-Zadeh, 2013; Heinzle et al., 2012; Shirer et al., 2012; Richiardi et al., 2011) or to classify diseased and nondiseased cohorts in an effort to develop neurodiagnostics (Fekete et al., 2013; Bassett,…”
Decoding subject-driven cognitive states with whole-brain connectivity patterns. (2012, background): “A number of recent studies have used structurally defined ROIs to gain insights into the basic properties of both structural and functional brain networks (Hagmann et al. 2008; Supekar et al. 2008; Honey et al. 2009) and to classify brain states (Richiardi et al. 2010).”
On spurious and real fluctuations of dynamic functional connectivity during rest (2015, neutral): “FC has revealed reorganization of brain networks during cognitive tasks (Ekman et al., 2012; Lewis et al., 2009; Richiardi et al., 2011, 2013; Shirer et al., 2012), but also at rest (Allen et al., 2014; Chang and Glover, 2010; Hutchison et al., 2013b; Kang et al., 2011; Leonardi et al., 2013;…”