Smoothing and cluster thresholding for cortical surface-based group analysis of fMRI data

By Donald J. Hagler Jr., Ayse Pinar Saygin, Martin I. Sereno. NeuroImage, 2006

501 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/e24ca526eec5f20c0451781e62899b5b0ac2f554

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Mert Rory Sabuncu
2. D. V. Van Essen
3. Donna L. Dierker
4. B. T. T. Yeo
5. Anders M. Fjell
6. Kristine B. Walhovd
7. Krzysztof J. Gorgolewski
8. Polina Golland

In Radiology, Nuclear Medicine and Imaging

1. Mert Rory Sabuncu
2. B. T. T. Yeo
3. D. V. Van Essen
4. Donna L. Dierker
5. Anders M. Fjell
6. Kristine B. Walhovd
7. Krzysztof J. Gorgolewski
8. John W. Harwell

Citations in the corpus

• Spatial regression models over two-dimensional manifolds (2016, methodology): “For large bandwidths, heat kernel estimates are comparable to the simpler and less computationally demanding method of nearest neighbor averaging [11].”
• SCT: Spinal Cord Toolbox, an open‐source software for processing spinal cord MRI data (2017, methodology): “This approach is analogous to the 2D surface smoothing that is popular for brain cortical analysis (Hagler et al., 2006; Kiebel et al., 1999).”
• Human cortical representations for reaching: Mirror neurons for execution, observation, and imagery (2007, methodology): “AFNI's AlphaSim (Ward, 2000b) was adapted to cortical surface data to ensure that the corrected p-value for these thresholds was 0.05 (Hagler et al., 2006).”
• Spherical Demons: Fast Diffeomorphic Landmark-Free Surface Registration (2009, background): “Approximating smoothing kernels by iterative smoothing is an active area of research in medical imaging [17], [32].”
• Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python (2011, methodology): “Third method involves reconstructing surface of the cortex and smoothing along it (Hagler et al., 2006).”
• Similar patterns of cortical expansion during human development and evolution (2010, methodology): “Maps of postnatal surface area expansion and evolutionary area expansion were smoothed 10 iterations (5-mm smoothing kernel) using an average neighbors algorithm (10, 56).”
• Effects of memory training on cortical thickness in the elderly (2010, methodology): “In the present study TBV was defined as the sum of the volume of brain structures identified by FreeSurfer, after correcting for partial-volume effects.”
• Relevant Feature Set Estimation with a Knock-out Strategy and Random Forests (2015, unknown): “To account for this, post-processing techniques such as Worsley et al. (1996), Andrade et al. (2001), Hagler et al. (2006), and Smith and Nichols (2009) attempt to integrate the multivariate information by assuming that “real” effects would be visible in larger spatial neighborhoods.”