Laminar fMRI: applications for cognitive neuroscience

The cortex is a massively recurrent network, characterized by feedforward and feedback connections between brain areas as well as lateral connections within an area. Feedforward, horizontal and feedback responses largely activate separate layers of a cortical unit, meaning they can be dissociated by lamina-resolved neurophysiological techniques. Such techniques are invasive and are therefore rarely used in humans. However, recent developments in high spatial resolution fMRI allow for non-invasive, in vivo measurements of brain responses specific to separate cortical layers. This provides an important opportunity to dissociate between feedforward and feedback brain responses, and investigate communication between brain areas at a more fine- grained level than previously possible in the human species. In this review, we highlight recent studies that successfully used laminar fMRI to isolate layer-specific feedback responses in human sensory cortex. In addition, we review several areas of cognitive neuroscience that stand to benefit from this new technological development, highlighting contemporary hypotheses that yield testable predictions for laminar fMRI. We hope to encourage researchers with the opportunity to embrace this development in fMRI research, as we expect that many future advancements in our current understanding of human brain function will be gained from measuring lamina-specific brain responses

Cortical depth dependent functional responses in humans at 7T: improved specificity with 3D GRASE

Ultra high fields (7T and above) allow functional imaging with high contrast-to-noise ratios and improved spatial resolution. This, along with improved hardware and imaging techniques, allow investigating columnar and laminar functional responses. Using gradient-echo (GE) (T2* weighted) based sequences, layer specific responses have been recorded from human (and animal) primary visual areas. However, their increased sensitivity to large surface veins potentially clouds detecting and interpreting layer specific responses. Conversely, spin-echo (SE) (T2 weighted) sequences are less sensitive to large veins and have been used to map cortical columns in humans. T2 weighted 3D GRASE with inner volume selection provides high isotropic resolution over extended volumes, overcoming some of the many technical limitations of conventional 2D SE-EPI, whereby making layer specific investigations feasible. Further, the demonstration of columnar level specificity with 3D GRASE, despite contributions from both stimulated echoes and conventional T2 contrast, has made it an attractive alternative over 2D SE-EPI. Here, we assess the spatial specificity of cortical depth dependent 3D GRASE functional responses in human V1 and hMT by comparing it to GE responses. In doing so we demonstrate that 3D GRASE is less sensitive to contributions from large veins in superficial layers, while showing increased specificity (functional tuning) throughout the cortex compared to GE

Effects of phase regression on high-resolution functional MRI of the primary visual cortex

High-resolution functional MRI studies have become a powerful tool to non-invasively probe the sub-millimeter functional organization of the human cortex. Advances in MR hardware, imaging techniques and sophisticated post-processing methods have allowed high resolution fMRI to be used in both the clinical and academic neurosciences. However, consensus within the community regarding the use of gradient echo (GE) or spin echo (SE) based acquisition remains largely divided. On one hand, GE provides a high temporal signal-to-noise ratio (tSNR) technique sensitive to both the macro- and micro-vascular signal while SE based methods are more specific to microvasculature but suffer from lower tSNR and specific absorption rate limitations, especially at high field and with short repetition times. Fortunately, the phase of the GE-EPI signal is sensitive to vessel size and this provides a potential avenue to reduce the macrovascular weighting of the signal (phase regression, Menon 2002). In order to determine the efficacy of this technique at high-resolution, phase regression was applied to GE-EPI timeseries and compared to SE-EPI to determine if GE-EPI\u27s specificity to the microvascular compartment improved. To do this, functional data was collected from seven subjects on a neuro-optimized 7 T system at 800 μm isotropic resolution with both GE-EPI and SE-EPI while observing an 8 Hz contrast reversing checkerboard. Phase data from the GE-EPI was used to create a microvasculature-weighted time series (GE-EPI-PR). Anatomical imaging (MP2RAGE) was also collected to allow for surface segmentation so that the functional results could be projected onto a surface. A multi-echo gradient echo sequence was collected and used to identify venous vasculature. The GE-EPI-PR surface activation maps showed a high qualitative similarity with SE-EPI and also produced laminar activity profiles similar to SE-EPI. When the GE-EPI and GE-EPI-PR distributions were compared to SE-EPI it was shown that GE-EPI-PR had similar distribution characteristics to SE-EPI (p \u3c 0.05) across the top 60% of cortex. Furthermore, it was shown that GE-EPI-PR has a higher contrast-to-noise ratio (0.5 ± 0.2, mean ± std. dev. across layers) than SE-EPI (0.27 ± 0.07) demonstrating the technique has higher sensitivity than SE-EPI. Taken together this evidence suggests phase regression is a useful method in low SNR studies such as high-resolution fMRI

High-resolution CBV-fMRI allows mapping of laminar activity and connectivity of cortical input and output in human M1

Layer-dependent fMRI allows measurements of information flow in cortical circuits, as afferent and efferent connections terminate in different cortical layers. However, it is unknown to what level human fMRI is specific and sensitive enough to reveal directional functional activity across layers. To answer this question, we developed acquisition and analysis methods for blood-oxygen-level-dependent (BOLD) and cerebral-blood-volume (CBV)-based laminar fMRI and used these to discriminate four different tasks in the human motor cortex (M1). In agreement with anatomical data from animal studies, we found evidence for somatosensory and premotor input in superficial layers of M1 and for cortico-spinal motor output in deep layers. Laminar resting-state fMRI showed directional functional connectivity of M1 with somatosensory and premotor areas. Our findings demonstrate that CBV-fMRI can be used to investigate cortical activity in humans with unprecedented detail, allowing investigations of information flow between brain regions and outperforming conventional BOLD results that are often buried under vascular biases

Layer-specific activation of sensory input and predictive feedback in the human primary somatosensory cortex

When humans perceive a sensation, their brains integrate inputs from sensory receptors and process them based on their expectations. The mechanisms of this predictive coding in the human somatosensory system are not fully understood. We fill a basic gap in our understanding of the predictive processing of somatosensation by examining the layer-specific activity in sensory input and predictive feedback in the human primary somatosensory cortex (S1). We acquired submillimeter functional magnetic resonance imaging data at 7T (n = 10) during a task of perceived, predictable, and unpredictable touching sequences. We demonstrate that the sensory input from thalamic projects preferentially activates the middle layer, while the superficial and deep layers in S1 are more engaged for cortico-cortical predictive feedback input. These findings are pivotal to understanding the mechanisms of tactile prediction processing in the human somatosensory cortex

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

Vascular artefacts in fMRI of early visual cortex: The effects of resolution and field strength

Large draining veins residing on the cortical surface are recognised as a major problem in fMRI measurements, leading to the displacement, distortion, and reduction in spatial localisation of signals. This is detrimental to the application of fMRI in advanced human brain imaging, such as in retinotopic mapping, where the BOLD signal becomes obscured by the artefacts from nearby draining veins (venous artefacts). There is consensus that at an increased magnetic field strength, the sensitivity to the contributions from these draining veins reduces, which promises the ability to capture measurements at greater sensitivity and specificity. With the advent of fMRI hardware and technologies, there is a great interest in understanding cortical layer-specific neuronal response that had been previously obscured due to the domination of signal change caused by venous artefacts. This forms the basis of support for fMRI at ultra-high magnetic field strength, with the conventional wisdom that the reduced sensitivity to macrovasculature (including draining veins) that comes with higher magnetic field strength can increase the sensitivity to underlying responses that closely reflect neuronal activation. However, this is debatable. Instead, there are instances where human neuronal response profiles displayed a pattern that seemed indicative of synaptic activities even without using ultra-high magnetic field strength. Recent trends in moving to ultra-high magnetic field strengths, especially for depth-dependent fMRI, beget the questions – is ultra-high magnetic field strength really necessary, and can it resolve the artefacts from draining veins? To elucidate these questions, this thesis aims to test the venous artefact and its impact on underlying signals across spatial resolutions and magnetic field strengths, focusing on the quality of the retinotopic organisation of the early visual cortex. The first experimental study was conducted to test the venous artefact and its impact on fMRI signals across the grey matter using high-resolution (isotropic resolution of 1 mm) fMRI images collected at 3 T. Using two surface reconstruction packages, the findings established that venous artefact occurs at the cortical surface and spreads within the grey matter. In this study, the ability of high-resolution fMRI at 3 T to conduct depth-dependent analyses was demonstrated. The second experimental study delves into the role of spatial resolution in the depth-dependent analysis of venous artefacts and their impact. The 1 mm 3 T fMRI images were spatially smoothed to simulate two additional sets of lower-effective resolution images. Here, the results found consistency in the venous artefact but a reduction in the venous effects. This suggests that at lower spatial resolutions, the venous artefact exists, but its impact on underlying signals is concealed. The third experiment incorporates two sets of 7 T fMRI images, with spatial resolutions of 1.6 mm and 0.8 mm, to test the venous artefacts at ultra-high magnetic field strength. The results showed evidence that venous artefacts remained prominent at 7 T. This study was extended into a comparative study by including the 3 T fMRI images used in the first study. Here, the generalisability of the venous artefact was established at 3 T and 7 T, as well as across various spatial resolutions. Finally, the fourth experiment explored a non- BOLD contrast, postulated to be less sensitive to contributions from the draining veins. In this study, VASO-fMRI was conducted with a spatial resolution of 1.1 mm and at 7 T to test the venous artefact and its impact. A reduction in the venous artefact and its impact was demonstrated. However, VASO images were found insufficient to inform the retinotopic organisation of the early visual cortex due to higher noise and lower signals, but they can be beneficial when used in conjunction with BOLD images. In summary, this thesis established the competence of high-resolution fMRI at 3 T for depth-dependent analysis. This suggests that the artefacts arising from draining veins can be avoided by avoiding surfaces or locations that are in proximity to these veins. Furthermore, this thesis sheds light on the generalisability of the venous artefact across magnetic field strengths and spatial resolutions. Finally, the results from the VASO-fMRI study demonstrated how VASO retinotopic mapping could benefit BOLD retinotopic mapping, especially when the BOLD response is highly polluted with macrovasculature

Phase imaging for reducing macrovascular signal contributions in high-resolution fMRI

High resolution functional MRI allows for the investigation of neural activity within the cortical sheet. One consideration in high resolution fMRI is the choice of which sequence to use during imaging, as all methods come with sensitivity and specificity tradeoffs. The most used fMRI sequence is gradient-echo echo planar imaging (GE-EPI) which has the highest sensitivity but is not specific to microvasculature. GE-EPI results in a signal with pial vessel bias which increases complexity of performing studies targeted at structures within the cortex. This work seeks to explore the use of MRI phase signal as a macrovascular filter to correct this bias. First, an in-house phase combination method was designed and tested on the 7T MRI system. This method, the fitted SVD method, uses a low-resolution singular value decomposition and fitting to a polynomial basis to provide computationally efficient, phase sensitive, coil combination that is insensitive to motion. Second, a direct comparison of GE-EPI, GE-EPI with phase regression (GE-EPI-PR), and spin echo EPI (SE-EPI) was performed in humans completing a visual task. The GE-EPI-PR activation showed higher spatial similarity with SE-EPI than GE-EPI across the cortical surface. GE-EPI-PR produced a similar laminar profile to SE-EPI while maintaining a higher contrast-to-noise ratio across layers, making it a useful method in low SNR studies such as high-resolution fMRI. The final study extended this work to a resting state macaque experiment. Macaques are a common model for laminar fMRI as they allow for simultaneous imaging and electrophysiology. We hypothesized that phase regression could improve spatial specificity of the resting state data. Further analysis showed the phase data contained both system and respiratory artifacts which prevented the technique performing as expected under two physiological cleaning strategies. Future work will have to examine on-scanner physiology correction to obtain a phase timeseries without artifacts to allow for the phase regression technique to be used in macaques. This work demonstrates that phase regression reduces signal contributions from pial vessels and will improve specificity in human layer fMRI studies. This method can be completed easily with complex fMRI data which can be created using our fitted SVD method

Depth-Dependent Physiological Modulators of the BOLD Response in the Human Motor Cortex

This dissertation proposes a set of methods for improving spatial localization of cerebral metabolic changes using functional magnetic resonance imaging (fMRI). Blood oxygen level dependent (BOLD) fMRI estabilished itself as the most frequently used technique for mapping brain activity in humans. It is non-invasive and allows to obtain information about brain oxygenation changes in a few minutes. It was discovered in 1990 and, since then, it contributed enormously to the developments in neuroscientific research. Nevertheless, the BOLD contrast suffers from inherent limitations. This comes from the fact that the observed response is the result of a complex interplay between cerebral blood flow (CBF), cerebral blood volume (CBV) and cerebral metabolic rate of oxygen consumption (CMRO2) and has a strong dependency on baseline blood volume and oxygenation. Therefore, the observed response is mislocalized from the site where the metabolic activity takes place and it is subject to high variability across experiments due to normal brain physiology. Since the peak of BOLD changes can be as much as 4 mm apart from the site of metabolic changes, the problem of spatial mislocalization is particularly constraining at submillimeter resolution. Three methods are proposed in this work in order to overcome this limitation and make data more comparable. The first method involves a modification of an estabilished model for calibration of BOLD responses (the dilution model), in order to render it applicable at higher resolutions. The second method proposes a model-free scaling of the BOLD response, based on spatial normalization by a purely vascular response pattern. The third method takes into account the hypothesis that the cortical vasculature could act as a low-pass filter for BOLD fluctuations as the blood is carried downstream, and investigates differences in frequency composition of cortical laminae. All methods are described and tested on a depth-dependent scale in the human motor cortex