Default mode network activity in schizophrenia studied at resting state using probabilistic ICA.

By G. Mingoia, Gerd Wagner, K. Langbein, R. Maitra, Stefan Smesny, M. Dietzek, Hartmut P. Burmeister, Jürgen Rainer Reichenbach, Ralf G. M. Schlösser, Christian Gaser and 2 more. 2012

127 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience

Citations in the corpus

• Interpreting support vector machine models for multivariate group wise analysis in neuroimaging (2015, neutral): “Machine learning based methods Davatzikos (2004) Cuingnet et al. (2011) De Martino et al. (2008) Fan et al. (2007) Gaonkar and Davatzikos (2012) Xu et al. (2009) Van De Ville et al. (2007) Van De Ville et al. (2004) Mingoia et al. (2012) can offer diagnostics based on neuroimaging data.”
• Analytic estimation of statistical significance maps for support vector machine based multi-variate image analysis and classification (2013, unknown): “…al., 2011; Davatzikos et al., 2005; De Martino et al., 2008; 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;…”
• Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia (2015, unknown): “, 2002), including schizophrenia (SZ) (Greicius, 2008; Jafri et al., 2008; Liang et al., 2006; Liu et al., 2008; Mingoia et al., 2012; Yu et al., 2012; Zhou et al., 2007).”