Cortical thickness analysis examined through power analysis and a population simulation

By Jason P. Lerch, Alan C. Evans. NeuroImage, 2005

749 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/cd7361d934fb3f2516aebd1479951ca7af21647f

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. Alan C. Evans
2. Yong He
3. Bruce Fischl
4. Zhang John Chen
5. Gaolang Gong
6. E. Bullmore
7. D. Bassett
8. David H. Salat

In Radiology, Nuclear Medicine and Imaging

1. Alan C. Evans
2. Yong He
3. Bruce Fischl
4. Zhang John Chen
5. Gaolang Gong
6. David H. Salat
7. E. Bullmore
8. D. Bassett

Citations in the corpus

• Focal decline of cortical thickness in Alzheimer's disease identified by computational neuroanatomy. (2004, positive): “Furthermore, extensive analysis of the precision of our cortical thickness analysis framework was recently preformed (Lerch and Evans, 2004).”
• Cortical thickness analysis in autism with heat kernel smoothing (2005, methodology): “In this study, however, the data lie on a 2D surface so the smoothing must be weighted according to distance along the surface (Andrade et al., 2001; Chung et al., 2003; Lerch and Evans, 2005; Thompson et al., in press).”
• Gender difference analysis of cortical thickness in healthy young adults with surface-based methods (2006, methodology): “Previous studies evaluated the precision of several algorithms (Fischl and Dale, 2000; Jones et al., 2000; MacDonald et al., 2000) and suggested that t link is the simplest and most precise method (Lerch and Evans, 2005).”
• Detection of cortical thickness correlates of cognitive performance: Reliability across MRI scan sessions, scanners, and field strengths (2008, background): “, 2004), the reliability of measures of this fundamental morphometric property of the brain has received relatively little systematic investigation (Fischl and Dale, 2000; Rosas et al., 2002a; Kuperberg et al., 2003b; Sowell et al., 2004; Lerch and Evans, 2005; Han et al., 2006).”
• Trajectories of cortical thickness maturation in normal brain development – The importance of quality control procedures (2015, positive): “Calculate CTh at each cortical point using the tlink metric (Lerch and Evans, 2005) and blur each subject's CThmap using a 20-millimeter full width at half maximum surface-based diffusion smoothing kernel (a necessary step to impose a normal distribution to corticometric data and to increase…”
• The NIH MRI study of normal brain development (2006, neutral): “6, MacDonald et al., 2000; Kabani et al., 2001; Kim et al., 2005; Lerch and Evans, 2005).”
• Convergence and divergence of thickness correlations with diffusion connections across the human cerebral cortex (2012, methodology): “, 2001) and simulation approaches (Lee et al., 2006; Lerch and Evans, 2005).”
• Mapping anatomical correlations across cerebral cortex (MACACC) using cortical thickness from MRI (2006, methodology): “, 2001) and a population simulation (Lerch and Evans, 2005), and used in an Alzheimer’s Disease population study (Lerch et al.”
• Cortical thickness and central surface estimation (2013, methodology): “It provides surface-based smoothing 127 that gives results superior to that obtained from volumetric smooth- 128 ing (Lerch and Evans, 2005).”
• Structural Insights into Aberrant Topological Patterns of Large-Scale Cortical Networks in Alzheimer's Disease (2008, methodology): “, 2001) and simulation approaches (Lerch and Evans, 2005; Lee et al., 2006) and applied to recent AD studies (Lerch et al.”