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

The Correlation between Astrocytic Calcium and fMRI Signals is Related to the Thalamic Regulation of Cortical States

BOLD fMRI has been wildly used for mapping brain activity, but the cellular contribution of BOLD signals is still controversial. In this study, we investigated the correlation between neuronal/astrocytic calcium and the BOLD signal using simultaneous GCaMP-mediated calcium and BOLD signal recording, in the event-related state and in resting state, in anesthetized and in free-moving rats. To our knowledge, the results provide the first demonstration that evoked and intrinsic astrocytic calcium signals could occur concurrently accompanied by opposite BOLD signals which are associated with vasodilation and vasoconstriction. We show that the intrinsic astrocytic calcium is involved in brain state changes and is related to the activation of central thalamus. First, by simultaneous LFP and fiber optic calcium recording, the results show that the coupling between LFP and calcium indicates that neuronal activity is the basis of the calcium signal in both neurons and astrocytes. Second, we found that evoked neuronal and astrocytic calcium signals are always positively correlated with BOLD responses. However, intrinsic astrocytic calcium signals are accompanied by the activation of the central thalamus followed by a striking negative BOLD signal in cortex, which suggests that central thalamus may be involved in the initiation of the intrinsic astrocytic calcium signal. Third, we confirmed that the intrinsic astrocytic calcium signal is preserved in free moving rats. Moreover, the occurrences of intrinsic astrocytic calcium spikes are coincident with the transition between different sleep stages, which suggests intrinsic astrocytic calcium spikes reflect brain state transitions. These results demonstrate that the correlation between astrocytic calcium and fMRI signals is related to the thalamic regulation of cortical states. On the other hand, by studying the relationship between vessel–specific BOLD signals and spontaneous calcium activity from adjacent neurons, we show that low frequency spontaneous neuronal activity is the cellular mechanism of the BOLD signal during resting state

The Human Connectome Project's neuroimaging approach

Noninvasive human neuroimaging has yielded many discoveries about the brain. Numerous methodological advances have also occurred, though inertia has slowed their adoption. This paper presents an integrated approach to data acquisition, analysis and sharing that builds upon recent advances, particularly from the Human Connectome Project (HCP). The 'HCP-style' paradigm has seven core tenets: (i) collect multimodal imaging data from many subjects; (ii) acquire data at high spatial and temporal resolution; (iii) preprocess data to minimize distortions, blurring and temporal artifacts; (iv) represent data using the natural geometry of cortical and subcortical structures; (v) accurately align corresponding brain areas across subjects and studies; (vi) analyze data using neurobiologically accurate brain parcellations; and (vii) share published data via user-friendly databases. We illustrate the HCP-style paradigm using existing HCP data sets and provide guidance for future research. Widespread adoption of this paradigm should accelerate progress in understanding the brain in health and disease

Use of functional neuroimaging and optogenetics to explore deep brain stimulation targets for the treatment of Parkinson's disease and epilepsy

Deep brain stimulation (DBS) is a neurosurgical therapy for Parkinson’s disease and epilepsy. In DBS, an electrode is stereotactically implanted in a specific region of the brain and electrical pulses are delivered using a subcutaneous pacemaker-like stimulator. DBS-therapy has proven to effectively suppress tremor or seizures in pharmaco-resistant Parkinson’s disease and epilepsy patients respectively. It is most commonly applied in the subthalamic nucleus for Parkinson’s disease, or in the anterior thalamic nucleus for epilepsy. Despite the rapidly growing use of DBS at these classic brain structures, there are still non-responders to the treatment. This creates a need to explore other brain structures as potential DBS-targets. However, research in patients is restricted mainly because of ethical reasons. Therefore, in order to search for potential new DBS targets, animal research is indispensable. Previous animal studies of DBS-relevant circuitry largely relied on electrophysiological recordings at predefined brain areas with assumed relevance to DBS therapy. Due to their inherent regional biases, such experimental techniques prevent the identification of less recognized brain structures that might be suitable DBS targets. Therefore, functional neuroimaging techniques, such as functional Magnetic Resonance Imaging and Positron Emission Tomography, were used in this thesis because they allow to visualize and to analyze the whole brain during DBS. Additionally, optogenetics, a new technique that uses light instead of electricity, was employed to manipulate brain cells with unprecedented selectivity

On the influence of the vascular architecture on Gradient Echo and Spin Echo BOLD fMRI signals across cortical depth: a simulation approach based on realistic 3D vascular networks

GE-BOLD contrast stands out as the predominant technique in functional MRI experiments for its high sensitivity and straightforward implementation. GE-BOLD exhibits rather similar sensitivity to vessels independent of their size at submillimeter resolution studies like those examining cortical columns and laminae. However, the presence of nonspecific macrovascular contributions poses a challenge to accurately isolate neuronal activity. SE-BOLD increases specificity towards small vessels, thereby enhancing its specificity to neuronal activity, due to the effective suppression of extravascular contributions caused by macrovessels with its refocusing pulse. However, even SE-BOLD measurements may not completely remove these macrovascular contributions. By simulating hemodynamic signals across cortical depth, we gain insights into vascular contributions to the laminar BOLD signal. In this study, we employed four realistic 3D vascular models to simulate oxygen saturation states in various vascular compartments, aiming to characterize both intravascular and extravascular contributions to GE and SE signals, and corresponding BOLD signal changes, across cortical depth at 7T. Simulations suggest that SE-BOLD cannot completely reduce the macrovascular contribution near the pial surface. Simulations also show that both the specificity and signal amplitude of BOLD signals at 7T depend on the spatial arrangement of large vessels throughout cortical depth and on the pial surface

LayNii: a software suite for layer-fMRI

High-resolution fMRI in the sub-millimeter regime allows researchers to resolve brain activity across cortical layers and columns non-invasively. While these high-resolution data make it possible to address novel questions of directional information flow within and across brain circuits, the corresponding data analyses are challenged by MRI artifacts, including image blurring, image distortions, low SNR, and restricted coverage. These challenges often result in insufficient spatial accuracy of conventional analysis pipelines. Here we introduce a new software suite that is specifically designed for layer-specific functional MRI: LayNii. This toolbox is a collection of command-line executable programs written in C/C++ and is distributed opensource and as pre-compiled binaries for Linux, Windows, and macOS. LayNii is designed for layer-fMRI data that suffer from SNR and coverage constraints and thus cannot be straightforwardly analyzed in alternative software packages. Some of the most popular programs of LayNii contain ‘layerification’ and columnarization in the native voxel space of functional data as well as many other layer-fMRI specific analysis tasks: layer-specific smoothing, model-based vein mitigation of GE-BOLD data, quality assessment of artifact dominated sub-millimeter fMRI, as well as analyses of VASO data

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