Analysis strategies for high-resolution UHF-fMRI data

Abstract

Functional MRI (fMRI) benefits from both increased sensitivity and specificity with increasing magnetic field strength, making it a key application for Ultra-High Field (UHF) MRI scanners. Most UHF-fMRI studies utilize the dramatic increases in sensitivity and specificity to acquire high-resolution data reaching sub-millimeter scales, which enable new classes of experiments to probe the functional organization of the human brain. This review article surveys advanced data analysis strategies developed for high-resolution fMRI at UHF. These include strategies designed to mitigate distortion and artifacts associated with higher fields in ways that attempt to preserve spatial resolution of the fMRI data, as well as recently introduced analysis techniques that are enabled by these extremely high-resolution data. Particular focus is placed on anatomically-informed analyses, including cortical surface-based analysis, which are powerful techniques that can guide each step of the analysis from preprocessing to statistical analysis to interpretation and visualization. New intracortical analysis techniques for laminar and columnar fMRI are also reviewed and discussed. Prospects for single-subject individualized analyses are also presented and discussed. Altogether, there are both specific challenges and opportunities presented by UHF-fMRI, and the use of proper analysis strategies can help these valuable data reach their full potential.

Addressing challenges of high spatial resolution UHF fMRI for group analysis of higher‐order cognitive tasks: An inter‐sensory task directing attention between visual and somatosensory domains

“…Stelzer, Lohmann, Mueller, Buschmann, & Turner, 2014;Turner & Geyer, 2014;Turner, 2016]) highlight that the use of large smoothing kernels negates the benefits of the high spatial resolution of fMRI achievable at UHF. In addition, they highlight that smoothing is not required for False Discovery Rate correction (Turner & Geyer, 2014) due to the inherent smoothness of fMRI data due to the point-spread function of the BOLD response (Polimeni et al, 2017;Stelzer et al, 2014). Turner (Turner & Geyer, 2014) provides a detailed critique of the problems associated with spatial smoothing (Stelzer et al, 2014;Turner, 2016;Turner & Geyer, 2014).…”

“…To date, the majority of UHF fMRI studies have used reduced field‐of‐view (FOV) 2D‐and 3D echo planar imaging (EPI) acquisitions to study chosen primary sensory areas, such as the visual and sensorimotor cortices (Fracasso, Luijten, Dumoulin, & Petridou, ; Puckett, Bollmann, Barth, & Cunnington, ; Reithler, Peters, & Goebel, ; Schluppeck, Sanchez‐Panchuelo, & Francis, ), thus overcoming a number of challenges of B 0 and B 1 inhomogeneities associated with larger FOV acquisitions (Polimeni, Renvall, Zaretskaya, & Fischl, ; Uludag & Blinder, ). For example, the increase in BOLD CNR of UHF experiments has been used to provide detailed maps of individual subjects’ visual (Goncalves et al, ; Kemper, De Martino, Emmerling, Yacoub, & Goebel, ; Poltoratski, Ling, McCormack, & Tong, ; Rua et al, ) and somatosensory functional responses (Puckett et al, ; Sanchez Panchuelo et al, ; Sanchez Panchuelo, Schluppeck, Harmer, Bowtell, & Francis, ) and how these relate to individual brain anatomy (Besle, Sanchez‐Panchuelo, Bowtell, Francis, & Schluppeck, ; Sanchez‐Panchuelo et al, ; Sanchez‐Panchuelo et al, ).…”

Anatomy-guided Inverse-phase-encoding Registration Method for Correcting Susceptibility Artifacts in Sub-millimeter fMRI

“…These distortions are known as susceptibility artifacts (SAs). The SAs are more severe at high field strengths (Ogawa et al, 1990;Polimeni et al, 2018) and in rapid imaging techniques such as EPI (Schmitt, 2015;Ludeke et al, 1985). These artifacts can be easily seen in the interface regions, particularly between the cerebral cortex and non-brain areas (McRobbie et al, 2003).…”

“…However, the impact of the SAs is much more significant in high spatial resolution (sub-millimeter) fMRI, which has become widely used. Second, existing SA correction methods tend to blur the corrected images (Polimeni et al, 2018), which contradicts the goal of acquiring a higher spatial image resolution.…”

A critical assessment of data quality and venous effects in ultra-high-resolution fMRI

“…We use isotropic voxels (0.8-mm) to ensure unbiased sampling of the convoluted cerebral 33 cortex, and we use multiband slice acceleration (Moeller et al, 2010) to achieve large coverage-such 34 coverage is important because sensory, cognitive, and motor function often reflect coordinated activity of 35 a large number of interacting brain regions. Finally, we use a modern surface-based analysis approach 36 (Glasser et al, 2013; Kemper et al, 2018;Polimeni et al, 2018), necessary for handling the convoluted 37 cortical surface visible in large field-of-view measurements (Polimeni et al, 2010). 38 39 The overarching goal in this study is to assess the quality and nature of ultra-high-resolution fMRI 40 measurements.…”