Statistical parametric maps in functional imaging: A general linear approach

By Karl J. Friston, Andrew Holmes, Keith J. Worsley, Jean-Baptiste Poline, ChrisD . Frith, Richard S. J. Frackowiak. 1994

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Citations in the corpus

Causal and anti-causal learning in pattern recognition for neuroimaging (2015, background): “the general linear model [8] or the class-conditional mean: E{X|Y }.”
Relevant Feature Set Estimation with a Knock-out Strategy and Random Forests (2015, unknown): “…we used the following different methods in our analysis in addition to the proposed one: 1 Mass-univariate analysis with generalized linear models (Friston et al., 1994), (Ashburner and Friston, 2000) (Univariate) 2 LASSO (Tibshirani, 1996) 3 Elastic Net (Zou and Hastie, 2005) 4 Sparse logistic…”
Bach Speaks: A Cortical "Language-Network" Serves the Processing of Music (2002, methodology): “A very similar network was activated by modulations, except that (with the threshold of z 3.09) no significant activations were found in the right STS and in the left pars opercularis (in contrast to both clusters and deviant instruments, cf. Table 1, Fig.”
fMRI of emotional responses to odors: : influence of hedonic valence and judgment, handedness, and gender (2003, methodology): “The significance of signal differences was assessed through Z scores in an omnibus sense (Friston et al., 1995b), using an uncorrected probability with a threshold of P Ͻ 0.001.”
Is emotional contagion special? An fMRI study on neural systems for affective and cognitive empathy (2008, methodology): “SPM5 software was used for the data analysis (Friston et al., 1995).”
Support vector machine learning-based fMRI data group analysis (2007, methodology): “Treating each functional image as an independent observation without considering the acquisition time, the SVM-based ap- proaches have the disadvantage of ignoring the dynamic changes in the brain response, which can be explored using other multivariate methods such as ICA, CVA, or PLS.”
Neural correlates of outcome after stroke: a cross-sectional fMRI study (2003, methodology): “The resulting covariates were convolved with a canonical synthetic haemodynamic response function, and were used in a general linear model (Friston et al., 1995a) together with a single covariate representing the mean (constant) term over scans.”
Generative modeling of brain maps with spatial autocorrelation (2020, background): “For instance, the non-independence of signals measured in proximal brain regions impacts expectations for the spatial extent of task activation peaks in neuroimaging (Friston et al., 1994).”
Predictability Modulates Human Brain Response to Reward (2001, background): “Twenty-five normal adults underwent fMRI scanning while being administered small amounts of either oral fruit juice or water.”
The Brain-Derived Neurotrophic Factor val66met Polymorphism and Variation in Human Cortical Morphology (2004, unknown): “The normalized and smoothed gray matter images were analyzed using statistical parametric mapping with the framework of the General Linear Model (Friston et al., 1995) in SPM2.”
Functional neuroimaging of normal human sleep by positron emission tomography (2000, methodology): “The ®nal step of statistical inferences takes into account the multiple comparisons that have been made (Friston et al. 1991a, 1994)4 .”
Bayesian fMRI data analysis with sparse spatial basis function priors (2007, methodology): “Temporal modelling of the data is implemented using the General Linear Model (GLM).”