Modeling regional and psychophysiologic interactions in fMRI: the importance of hemodynamic deconvolution

[1]  Karl J. Friston,et al.  Classical and Bayesian Inference in Neuroimaging: Theory , 2002, NeuroImage.

[2]  E. Zarahn.  Testing for Neural Responses during Temporal Components of Trials with BOLD fMRI , 2000, NeuroImage.

[3]  G. Glover.  Deconvolution of Impulse Response in Event-Related BOLD fMRI1 , 1999, NeuroImage.

[4]  K J Friston,et al.  The predictive value of changes in effective connectivity for human learning. , 1999, Science.

[5]  M. D’Esposito,et al.  Temporal isolation of the neural correlates of spatial mnemonic processing with fMRI. , 1999, Brain research. Cognitive brain research.

[6]  M. D’Esposito,et al.  The variability of human BOLD hemodynamic responses , 1998, NeuroImage.

[7]  R. Turner,et al.  Event-Related fMRI: Characterizing Differential Responses , 1998, NeuroImage.

[8]  Karl J. Friston,et al.  Nonlinear event‐related responses in fMRI , 1998, Magnetic resonance in medicine.

[9]  C. Büchel,et al.  Modulation of connectivity in visual pathways by attention: cortical interactions evaluated with structural equation modelling and fMRI. , 1997, Cerebral cortex.

[10]  Karl J. Friston,et al.  Psychophysiological and Modulatory Interactions in Neuroimaging , 1997, NeuroImage.

[11]  Karl J. Friston,et al.  Event‐related f MRI , 1997, Human brain mapping.

[12]  Leslie G. Ungerleider,et al.  Network analysis of cortical visual pathways mapped with PET , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.