Statistical parametric mapping
By W. D. Penny, Karl J. Friston, John Ashburner, Stefan J. Kiebel, Thomas E. Nichols. 2013
1,414 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience
View Paper: https://www.semanticscholar.org/paper/559f06ecfe15b6f994ab6f685e9293cd43947550
How researchers see this paper
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In Cognitive Neuroscience
- Gaël Varoquaux
- Justin Riddle
- Martin Reuter
- Anders Eklund
- Hans Knutsson
- Peter C. M. Molenaar
- Bertrand Thirion
- Alexandre Abraham
Citations in the corpus
- A hitchhiker's guide to diffusion tensor imaging (2012, methodology): “, AFNI, Freesurfer, SPM, Slicer) are commonly used to convert from the original DICOM format (Smith et al., 2004; Pieper et al., 2006; Friston et al., 2007; Fischl, 2012).”
- Group search algorithm recovers effective connectivity maps for individuals in homogeneous and heterogeneous samples (2012, methodology): “Contents lists available at SciVerse ScienceDirect NeuroImage j ourna l homepage: www.e lsev ie r .com/ locate /yn img Group search algorithm recovers effective connectivity maps for individuals in homogeneous and heterogeneous samples Kathleen M. Gates ⁎, Peter C.M. Molenaar”
- FastSurfer - A fast and accurate deep learning based neuroimaging pipeline (2019, methodology): “e that includes cortical surface reconstruction and segmentation. 1.1. Neuroimage Analysis To date, a few well maintained neuroimage processing pipelines such as FreeSurfer [11], BrainSuite [12], SPM [13], ANTs [14], or FSL [15] are the only means available to process and evaluate the incoming ow of”
- Machine learning for neuroimaging with scikit-learn (2014, methodology): “ correction, coregistration with an anatomical image and normalization to a common template like the MNI (Montreal Neurologic Institute) one if necessary. Reference softwares for these tasks are SPM (Friston, 2007) and FSL (Smith et al., 2004). A Python interface to these tools is available in nipyp”
- Cross‐validation failure: Small sample sizes lead to large error bars (2017, methodology): “Bayesian approaches such as Bayesian model selection or Bayesian model averaging rely on model evidence to test or select models (Penny et al., 2007, chap.”