Measuring structural-functional correspondence: Spatial variability of specialised brain regions after macro-anatomical alignment

By Martin A. Frost, Rainer Goebel. NeuroImage, 2012

322 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/39339c0b836c84e6c9dfaaabc874b1eabc3662b1

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In Cognitive Neuroscience

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Citations in the corpus

The Minimal Preprocessing Pipelines for the Human Connectome Project (2013, unknown): “The major change from Glasser and Van Essen (2011) was to lengthen TE in the T2w scans to improve intracortical contrast for myelin detection.”
Building a Science of Individual Differences from fMRI. (2016, background): “Although switching to cortical folding-based inter-subject alignment [20,21] has been shown to somewhat reduce functional mismatch [22,23] (but see [24]), this has not yet become common practice.”
Functional system and areal organization of a highly sampled individual human brain (2015, methodology): “The group data were geodesically registered on the surface based on macroanatomic sulcal and gyral features; this registration represents the current state of the art, but it does not achieve a true areato-area registration (Frost and Goebel, 2012).”
An algorithmic method for functionally defining regions of interest in the ventral visual pathway (2012, methodology): “One benefit of the Frost & Goebel's maps is that they can be used for surface-based analyses, which generally achieve better inter-subject alignment of activations (e.g., Fischl et al., 2008; Frost and Goebel, 2011).”
Parcellations and Connectivity Patterns in Human and Macaque Cerebral Cortex (2016, background): “…registration (SBR) and surface-based atlases have inherent advantages over conventional, volume-based registration because they respect the topology of the cortical sheet (Anticevic et al. 2008; Fischl et al. 1999; 2008; Frost and Goebel 2012; Tucholka et al. 2012; Van Essen et al. 2012c).”
Data Augmentation Using Learned Transformations for One-Shot Medical Image Segmentation (2019, background): “Firstly, human brains exhibit substantial anatomical variations [28, 59, 76].”
On testing for spatial correspondence between maps of human brain structure and function (2018, unknown): “541 tasks and macroanatomical gyral boundaries (Frost and Goebel, 2012), but this question would benefit from examination throughout the entire cortical sheet across a wide range of cognitive domains simultaneously.”
SCT: Spinal Cord Toolbox, an open‐source software for processing spinal cord MRI data (2017, background): “), without knowing the exact internal structure of white matter tracts or functional clusters (Frost and Goebel, 2012; Mori et al., 2009).”
Individual Variability in Functional Connectivity Architecture of the Human Brain (2013, background): “, 1999), as well as in fMRI-derived localization (Frost and Goebel, 2012).”
Can brain state be manipulated to emphasize individual differences in functional connectivity? (2017, background): “high-order association regions of neocortex, including prefrontal, parietal and temporal lobes, and lowest in primary sensory cortices (Frost and Goebel, 2012; Laumann et al., 2015; Mueller et al., 2013).”
Top-down and bottom-up interactions rely on nested brain oscillations to shape rhythmic visual attention sampling (2025, unknown): “These group maps were then back-transformed to the individual brain anatomy, with the TMS target defined as the center of gravity for the area with the highest probability [73,74].”