Neural Representations of Visual Motion Processing in the Human Brain Using Laminar Imaging at 9.4 Tesla

During natural behavior, much of the motion signal falling into our eyes is due to our own movements. Therefore, in order to correctly perceive motion in our environment, it is important to parse visual motion signals into those caused by self-motion such as eye- or head-movements and those caused by external motion. Neural mechanisms underlying this task, which are also required to allow for a stable perception of the world during pursuit eye movements, are not fully understood. Both, perceptual stability as well as perception of real-world (i.e. objective) motion are the product of integration between motion signals on the retina and efference copies of eye movements. The central aim of this thesis is to examine whether different levels of cortical depth or distinct columnar structures of visual motion regions are differentially involved in disentangling signals related to self-motion, objective, or object motion. Based on previous studies reporting segregated populations of voxels in high level visual areas such as V3A, V6, and MST responding predominantly to either retinal or extra- retinal (‘real’) motion, we speculated such voxels to reside within laminar or columnar functional units. We used ultra-high field (9.4T) fMRI along with an experimental paradigm that independently manipulated retinal and extra-retinal motion signals (smooth pursuit) while controlling for effects of eye-movements, to investigate whether processing of real world motion in human V5/MT, putative MST (pMST), and V1 is associated to differential laminar signal intensities. We also examined motion integration across cortical depths in human motion areas V3A and V6 that have strong objective motion responses. We found a unique, condition specific laminar profile in human area V6, showing reduced mid-layer responses for retinal motion only, suggestive of an inhibitory retinal contribution to motion integration in mid layers or alternatively an excitatory contribution in deep and superficial layers. We also found evidence indicating that in V5/MT and pMST, processing related to retinal, objective, and pursuit motion are either integrated or colocalized at the scale of our resolution. In contrast, in V1, independent functional processes seem to be driving the response to retinal and objective motion on the one hand, and to pursuit signals on the other. The lack of differential signals across depth in these regions suggests either that a columnar rather than laminar segregation governs these functions in these areas, or that the methods used were unable to detect differential neural laminar processing. Furthermore, the thesis provides a thorough analysis of the relevant technical modalities used for data acquisition and data analysis at ultra-high field in the context of laminar fMRI. Relying on our technical implementations we were able to conduct two high-resolution fMRI experiments that helped us to further investigate the laminar organization of self-induced and externally induced motion cues in human high-level visual areas and to form speculations about the site and the mechanisms of their integration

High-Field fMRI for Human Applications: An Overview of Spatial Resolution and Signal Specificity

In the last decade, dozens of 7 Tesla scanners have been purchased or installed around the world, while 3 Tesla systems have become a standard. This increased interest in higher field strengths is driven by a demonstrated advantage of high fields for available signal-to-noise ratio (SNR) in the magnetic resonance signal. Functional imaging studies have additional advantages of increases in both the contrast and the spatial specificity of the susceptibility based BOLD signal. One use of this resultant increase in the contrast to noise ratio (CNR) for functional MRI studies at high field is increased image resolution. However, there are many factors to consider in predicting exactly what kind of resolution gains might be made at high fields, and what the opportunity costs might be. The first part of this article discusses both hardware and image quality considerations for higher resolution functional imaging. The second part draws distinctions between image resolution, spatial specificity, and functional specificity of the fMRI signals that can be acquired at high fields, suggesting practical limitations for attainable resolutions of fMRI experiments at a given field, given the current state of the art in imaging techniques. Finally, practical resolution limitations and pulse sequence options for studies in human subjects are considered

Temporal SNR characteristics in segmented 3D-EPI at 7T.

Three-dimensional segmented echo planar imaging (3D-EPI) is a promising approach for high-resolution functional magnetic resonance imaging, as it provides an increased signal-to-noise ratio (SNR) at similar temporal resolution to traditional multislice 2D-EPI readouts. Recently, the 3D-EPI technique has become more frequently used and it is important to better understand its implications for fMRI. In this study, the temporal SNR characteristics of 3D-EPI with varying numbers of segments are studied. It is shown that, in humans, the temporal variance increases with the number of segments used to form the EPI acquisition and that for segmented acquisitions, the maximum available temporal SNR is reduced compared to single shot acquisitions. This reduction with increased segmentation is not found in phantom data and thus likely due to physiological processes. When operating in the thermal noise dominated regime, fMRI experiments with a motor task revealed that the 3D variant outperforms the 2D-EPI in terms of temporal SNR and sensitivity to detect activated brain regions. Thus, the theoretical SNR advantage of a segmented 3D-EPI sequence for fMRI only exists in a low SNR situation. However, other advantages of 3D-EPI, such as the application of parallel imaging techniques in two dimensions and the low specific absorption rate requirements, may encourage the use of the 3D-EPI sequence for fMRI in situations with higher SNR

Exploring structure and function of sensory cortex with 7 T MRI

In this paper, we present an overview of 7 Tesla magnetic resonance imaging (MRI) studies of the detailed function and anatomy of sensory areas of the human brain. We discuss the motivation for the studies, with particular emphasis on increasing the spatial resolution of functional MRI (fMRI) using reduced field-of-view (FOV) data acquisitions. MRI at ultra-high-field (UHF) – defined here as 7 T and above – has several advantages over lower field strengths. The intrinsic signal-to-noise ratio (SNR) of images is higher at UHF, and coupled with the increased blood-oxygen-level-dependent (BOLD) signal change, this results in increased BOLD contrast-to-noise ratio (CNR), which can be exploited to improve spatial resolution or detect weaker signals. Additionally, the BOLD signal from the intra-vascular (IV) compartment is relatively diminished compared to lower field strengths. Together, these properties make 7 T functional MRI an attractive proposition for high spatial specificity measures. But with the advantages come some challenges. For example, increased vulnerability to susceptibility-induced geometric distortions and signal loss in EPI acquisitions tend to be much larger. Some of these technical issues can be addressed with currently available tools and will be discussed. We highlight the key methodological considerations for high resolution functional and structural imaging at 7 T. We then present recent data using the high spatial resolution available at UHF in studies of the visual and somatosensory cortex to highlight promising developments in this area