High-Resolution CBV-fMRI Allows Mapping of Laminar Activity and Connectivity of Cortical Input and Output in Human M1

Block-interleaved segmented echo-planar imaging for improved activity detection in submillimeter high-resolution functional MRI at 7 T

PURPOSE

Isotropic submillimeter high-resolution functional MRI (fMRI) facilitates noninvasive investigation of neuronal activities at the mesoscale level, including cortical columns and laminae. However, the task-evoked functional activity becomes less detectable when using single-shot echo planar imaging (EPI) with parallel imaging techniques such as generalized autocalibrating partially parallel acquisitions (GRAPPA), owing to a reduction in temporal signal-to-noise ratio (tSNR). Although conventional multishot EPI (msEPI) enhances tSNR, it reduces temporal resolution, making it less suitable for fMRI studies involving short-duration stimuli. To overcome this problem, a novel msEPI-based fMRI acquisition and reconstruction method, called block-interleaved segmented EPI (BISEPI), was proposed.

METHODS

This technique uses timing information of a block design paradigm during acquisition and reconstruction to preserve both temporal resolution and tSNR. Furthermore, a k-space-based motion correction method is incorporated to mitigate head motion artifacts.

RESULTS

Results from human studies showed that the proposed method reduced g-factor penalties typically observed in GRAPPA-accelerated EPI. It provided high tSNR, improved motion robustness, and enhanced sensitivity to blood oxygen level-dependent signal responses.

CONCLUSION

The proposed method circumvents both conventional msEPI-related and GRAPPA-related problems and enables the detection of blood oxygen level-dependent signal responses at submillimeter spatial resolution. It is effective for paradigms using short-duration, low-power stimuli at 0.7-mm isotropic resolution, and standard-power stimuli at 0.4-mm isotropic resolution.

Motor imagery enhances performance beyond the imagined action

Motor imagery is frequently utilized to improve the performance of specific target movements in sports and rehabilitation. In this study, we show that motor imagery can facilitate learning of not only the imagined target movements but also sequentially linked overt movements. Hybrid sequences comprising imagined and physically executed segments allowed participants to learn specific movement characteristics of the executed segments when they were consistently associated with specific imagined segments. Electrophysiological recordings revealed that the degree of event-related synchronization in the alpha and beta bands during a basic motor imagery task was correlated with imagery-evoked motor learning. Thus, both behavioral and neural evidence indicate that motor imagery's benefits extend beyond the imagined movements, improving performance in linked overt movements. This provides decisive evidence for the functional equivalence of imagined and overt movements and suggests applications for imagery in sports and rehabilitation.

Layer-specific spatiotemporal dynamics of feedforward and feedback in human visual object perception

Visual object perception is mediated by information flow between regions of the ventral visual stream along feedforward and feedback anatomical connections. However, feedforward and feedback signals during naturalistic vision are rapid and overlapping, complicating their identification and precise functional specification. Here we recorded human layer-specific fMRI responses to naturalistic object images in early visual cortex (EVC) and lateral occipital complex (LOC) to isolate feedforward and feedback information signals spatially by their cortical layer specific termination pattern. We combined these layer-specific fMRI responses with electroencephalography (EEG) responses for the same images to segregate feedforward and feedback signals in both time and space. Feedforward signals emerge early in the middle layers of EVC and LOC, followed by feedback signals in the superficial layer of both regions, and the deep layer of EVC. Comparing the identified dynamics in LOC to a visual deep neural network (DNN), revealed that early feedforward signals in LOC encode medium complexity features, whereas later feedback signals increase the representational format to high complexity features. Together this specifies the spatiotemporal dynamics and functional role of feedforward and feedback information flow mediating visual object perception.

Harmonic analysis and optimization for closed-loop superconducting shim coils of 7 T MRI magnet

BACKGROUND

High-resolution brain imaging is crucial in clinical diagnosis and neuroscience, with ultra-high field strength MRI systems (≥ 7 T $ \ge 7\ {\mathrm{T}}$ ) offering significant advantages for imaging neuronal microstructures. However, achieving magnetic field homogeneity is challenging due to engineering faults during the installation of superconducting strip windings and the primary magnet.

PURPOSE

This study aims to design and optimize active superconducting shim coils for a 7 T animal MRI system, focusing on the impact of safety margin, size, and adjustability of the second-order shim coils on the MRI system's optimization.

METHODS

The study employs a nonlinear optimization method to determine the parameters of the shim coils, considering the size of the coil, the level of undesired harmonics, and the whole number approximation of the turns in each coil. The study also conducts a thorough robustness analysis, examining the effects of coil winding accuracy, former processing accuracy, and assembly angle accuracy on the harmonic intensity of each coil.

RESULTS

The optimization design results for the 7 T MRI system's shim coils show that the magnetic field changes are less than 0.5 %. After second-order shimming and the harmonic coupling an, the low-order harmonics are minimized, resulting in an improved magnetic field peak-to-peak uniformity from 254.47 to 8.970 ppm.

CONCLUSION

The study successfully demonstrates the creation of a set of second-order shim coils for a 7 T animal MRI system through numerical optimization. The design outputs provide essential technological support for the development of a human whole-body 7 T MRI system, ensuring high-quality imaging at the neuronal level. The project also highlights the importance of considering manufacturing and assembly flaws in the shim coil design process to achieve effective shimming in practical engineering scenarios.

Multilayer network analysis across cortical depths in 7-T resting-state fMRI

In graph theory, "multilayer networks" represent systems involving several interconnected topological levels. One example in neuroscience is the stratification of connections between different cortical depths or "laminae," which is becoming noninvasively accessible in humans using ultrahigh-resolution functional MRI (fMRI). Here, we applied multilayer graph theory to examine functional connectivity across different cortical depths in humans, using 7-T fMRI (1-mm3 voxels; 30 participants). Blood oxygenation level dependent (BOLD) signals were derived from five depths between the white matter and pial surface. We compared networks where the interregional connections were limited to a single cortical depth only ("layer-by-layer matrices") with those considering all possible connections between areas and cortical depths ("multilayer matrix"). We utilized global and local graph theory features that quantitatively characterize network attributes including network composition, nodal centrality, path-based measures, and hub segregation. Detecting functional differences between cortical depths was improved using multilayer connectomics compared with the layer-by-layer versions. Superficial depths of the cortex dominated information transfer, and deeper depths drove clustering. These differences were largest in frontotemporal and limbic regions. fMRI functional connectivity across different cortical depths may contain neurophysiologically relevant information; thus, multilayer connectomics could provide a methodological framework for studies on how information flows across this stratification.

A deep neural network for adaptive spatial smoothing of task fMRI data

Over the past decade, functional magnetic resonance imaging (fMRI) has emerged as a widely adopted in vivo imaging technique for examining neural activity in the brain. A common preprocessing step in fMRI analysis is spatial smoothing, which helps in detecting cluster-like active regions. The use of a heuristically selected Gaussian filter for spatial smoothing is frequently preferred due to its simplicity and computational efficiency. Neurons in the cerebral cortex are located within a thin sheet of gray matter at the surface of the brain, and the human brain's gyrification results in a complex gray matter anatomy. For task-based fMRI activation analysis, isotropic Gaussian smoothing can reduce spatial specificity, introducing spatial blurring artifacts where inactive voxels near active regions are mistakenly identified as active. This blurring is beneficial for group-level analysis as it helps mitigate anatomical variability across subjects and inaccuracies in spatial normalization. However, it poses challenges in subject-level analysis, particularly in clinical applications such as presurgical planning and fMRI fingerprinting, which demand high spatial specificity. Previous studies have proposed several adaptive spatial smoothing techniques to address these issues. In this study, we introduce a versatile deep neural network (DNN) that builds on the strengths of previous approaches while overcoming their limitations. This method can incorporate additional neighboring voxels for estimating optimal spatial smoothing without significantly increasing computational costs, making it suitable for ultrahigh-resolution (sub-millimeter) task fMRI data. Furthermore, the proposed neural network incorporates brain tissue properties, enabling more accurate characterization of brain activation at the individual level.

In the brain of the beholder: bi-stable motion reveals mesoscopic-scale feedback modulation in V1

Understanding the neural processes underlying conscious perception remains a central goal in neuroscience. Visual illusions, whether static or dynamic, provide an effective ecological paradigm for studying conscious perception, as they induce subjective experiences from constant visual inputs. While previous neuroimaging studies have dissociated perceptual interpretation of visual motion from sensory input within the motion-sensitive area (hMT+) in humans, less is known about the role of the primary visual area (V1) and its relationship to hMT+ during a bistable perception. To address this, we conducted a layer-fMRI study at 7 T with human participants exposed to a bistable motion quartet stimulus. Despite a constant sensory input, the bistable motion quartet elicits switching horizontal and vertical apparent motion percepts likely due to lateral and feedback connections across low and high-level brain regions (feedback processing). As control, we used an "unambiguous" version of the motion quartet, hereafter referred to as "physical" motion stimulus, where horizontal and vertical motion is physically presented as visual stimulus in an alternated fashion (feedforward processing). With the advantage of a sub-millimeter resolution gained at ultra-high magnetic field (7 Tesla), we aimed to unveil the differential laminar modulation of V1 (early visual area) and hMT+ (high-order visual area) during the physical and bistable condition. Our results indicate that: (1) hMT+ functional activity correlates with conscious perception during both physical and ambiguous stimuli with similar strength. There is no evidence of differential laminar profiles in hMT+ between the two experimental conditions. (2) Between inducer squares, V1 shows a significantly reduced functional response to the ambiguous stimulus compared to the physical stimulus, as it primarily reflects feedback signals with diminished feedforward input. Distinct V1 laminar profiles differentiate the two experimental conditions. (3) The temporal dynamics of V1 and hMT+ become more similar during the ambiguous condition. (4) V1 exhibits reduced specificity to horizontal and vertical motion perception during the ambiguous condition at the retinotopic locations corresponding to the perceived motion. Our findings demonstrate that during the ambiguous condition, there is a stronger temporal coupling between hMT+ and V1 due to feedback signals from hMT+ to V1. Such feedback to V1 might be contributing to the stabilization of the vivid perception of directed motion at the face of constant ambiguous stimulation.

The pulsing brain: state of the art and an interdisciplinary perspective

Understanding the pulsing dynamics of tissue and fluids in the intracranial environment is an evolving research theme aimed at gaining new insights into brain physiology and disease progression. This article provides an overview of related research in magnetic resonance imaging, ultrasound medical diagnostics and mathematical modelling of biological tissues and fluids. It highlights recent developments, illustrates current research goals and emphasizes the importance of collaboration between these fields.

The laminar pattern of proprioceptive activation in human primary motor cortex

The primary motor cortex (M1) is increasingly being recognized for its vital role in proprioceptive somatosensation. However, our current understanding of proprioceptive processing at the laminar scale is limited. Empirical findings in primates and rodents suggest a pronounced role of superficial cortical layers, but the involvement of deep layers has yet to be examined in humans. Submillimeter resolution functional magnetic resonance imaging (fMRI) has emerged in recent years, paving the way for studying layer-dependent activity in humans (laminar fMRI). In the present study, laminar fMRI was employed to investigate the influence of proprioceptive somatosensation on M1 deep layer activation using passive finger movements. Significant M1 deep layer activation was observed in response to proprioceptive stimulation across 10 healthy subjects using a vascular space occupancy (VASO)-sequence at 7 T. For further validation, two additional datasets were included which were obtained using a balanced steady-state free precession sequence with ultrahigh (0.3 mm) in-plane resolution, yielding converging results. These results were interpreted in the light of previous laminar fMRI studies and the active inference account of motor control. We propose that a considerable proportion of M1 deep layer activation is due to proprioceptive influence and that deep layers of M1 constitute a key component in proprioceptive circuits.

Open-transmit and flexible receiver array for high resolution ultrahigh-field fMRI of the human sensorimotor cortex

In this study, we developed an open-transmit and 24-channel flexible receiver head coil assembly tailored for high-resolution ultrahigh-field functional magnetic resonance imaging (fMRI) of the human somatosensory and motor cortex. Leveraging the increased signal-to-noise ratio (SNR) and spatial resolution of ultrahigh field MRI, we address the technical challenges inherent in fMRI coil design. The open-birdcage transmit coil enhances patient comfort and enables visual task implementation, demonstrating superior performance in transmit efficiency and specific absorption rate distribution compared to conventional coils. Furthermore, the 24-channel flexible receiver head coil offers enhanced SNR and image quality, facilitating sub-millimeter vascular-space-occupancy imaging for precise functional mapping. These advancements provide valuable tools for unraveling the intricacies of somatosensory and motor cortex function. By enriching human brain functional studies, they contribute significantly to our understanding of the mechanisms underlying somatosensory and motor cortex function and may have valuable clinical applications in neurology and neuroscience research.

Mesoscale functional organization and connectivity of color, disparity, and naturalistic texture in human second visual area

Although parallel processing has been extensively studied in the low-level geniculostriate pathway and the high-level dorsal and ventral visual streams, less is known at the intermediate-level visual areas. In this study, we employed high-resolution fMRI at 7T to investigate the columnar and laminar organizations for color, disparity, and naturalistic texture in the human secondary visual cortex (V2), and their informational connectivity with lower- and higher-order visual areas. Although fMRI activations in V2 showed reproducible interdigitated color-selective thin and disparity-selective thick 'stripe' columns, we found no clear evidence of columnar organization for naturalistic textures. Cortical depth-dependent analyses revealed the strongest color-selectivity in the superficial layers of V2, along with both feedforward and feedback informational connectivity with V1 and V4. Disparity selectivity was similar across different cortical depths of V2, which showed significant feedforward and feedback connectivity with V1 and V3ab. Interestingly, the selectivity for naturalistic texture was strongest in the deep layers of V2, with significant feedback connectivity from V4. Thus, while local circuitry within cortical columns is crucial for processing color and disparity information, feedback signals from V4 are involved in generating the selectivity for naturalistic textures in area V2.

T1234: A distortion-matched structural scan solution to misregistration of high resolution fMRI data

PURPOSE

Registration of functional and structural data poses a challenge for high-resolution fMRI studies at 7 T. This study aims to develop a rapid acquisition method that provides distortion-matched, artifact-mitigated structural reference data.

METHODS

We introduce an efficient sequence protocol termed T1234, which offers adjustable distortions. This includes data that match distortions of functional data and data that are free of distortions. This approach involves a T1-weighted 2-inversion 3D-EPI sequence with four combinations of read and phase encoding directions optimized for high-resolution fMRI. A forward Bloch model was used for T1 quantification and protocol optimization. Fifteen participants were scanned at 7 T using both structural and functional protocols to evaluate the use of T1234.

RESULTS

Results from two protocols are presented. A fast distortion-free protocol reliably produced whole-brain segmentations at 0.8 mm isotropic resolution within 3:00-3:40 min. It demonstrates robustness across sessions, participants, and three different 7 T SIEMENS scanners. For a protocol with geometric distortions that matched functional data, T1234 facilitates layer-specific fMRI signal analysis with enhanced laminar precision.

CONCLUSION

This structural mapping approach enables precise registration with fMRI data. T1234 has been successfully implemented, validated, and tested, and is now available to users at our center and at over 50 centers worldwide.

Layer-specific BOLD effects in gradient and spin-echo acquisitions in somatosensory cortex

PURPOSE

Previous studies have shown varied BOLD signals with gradient echo (GE) across cortical depth. To interpret these variations, and understand the effects of vascular geometry and size, the magnitudes and layer distributions of GE and spin-echo (SE) BOLD functional MRI signals were compared in the somatosensory cortex of squirrel monkeys during tactile stimulation and in a resting state at high spatial resolution and high field.

METHODS

A block-design stimulation was used to identify tactile-evoked activation signals in somatosensory Areas 3b and 1. Layer-specific connectivities were calculated using resting-state data. Signal power spectra were compared by depth and pulse sequence. The measured ratios of transverse relaxation rate changes were compared with Anderson and Weiss's model.

RESULTS

SE signals showed a 26% lower percentage signal change during tactile stimulation compared with GE, along with a slower time course. SE signals remained consistent but weaker in lower layers, whereas GE signals decreased with cortical depth. This pattern extended to resting-state power spectra. Resting-state functional connectivity indicated larger connectivity between the top layers of Area 3b and Area 1 for GE, with minimal changes for SE. Comparisons with theory suggest vessel diameters ranging from 19.4 to 9 microns are responsible for BOLD effects across cortical layers at 9.4 T.

CONCLUSION

These results provide further evidence that at high field, SE BOLD signals are relatively free of contributions from sources other than microvascular changes in response to neural activity, whereas GE signals, even in the superficial layers, are not dominated by very large vessels.

Does the Cortical-Depth Dependence of the Hemodynamic Response Function Differ Between Age Groups?

Functional magnetic resonance imaging (fMRI) is a widely used tool to investigate the functional brain responses in living humans. Valid comparisons of fMRI results depend on consistency of the blood-oxygen-level-dependent (BOLD) hemodynamic response function (HRF). Although common statistical approaches assume a single HRF across the entire brain, the HRF differs across individuals, regions of the brain, and cortical depth. Here, we measure HRF properties in primary visual cortex (V1) using 7 T fMRI with ultra-high spatiotemporal resolution line-scanning (250 μm in laminar direction, sampled every 105 ms). Line-scanning allowed us to investigate age-related HRF changes as a function of cortical depth. Eleven young and eleven middle-aged healthy participants participated in the experiments. We estimated the HRFs using a smooth basis function deconvolution approach. We also compared the results with conventional resolutions. From these HRFs, we extracted properties related to response magnitude and temporal dynamics. The cortical depth dependent HRFs were similar to the HRFs extracted using conventional resolutions validating the cortical depth dependent approach. We found that the properties of the HRF in the two age groups are similar across cortical depth. In other words, the variance between participants is larger than the variance between age groups. This suggests that middle-aged individuals can participate in cortical depth dependent studies free of bias in HRF properties.

Mapping curvature domains in human V4 using CBV-sensitive layer-fMRI at 3T

Introduction

A full understanding of how we see our world remains a fundamental research question in vision neuroscience. While topographic profiling has allowed us to identify different visual areas, the exact functional characteristics and organization of areas up in the visual hierarchy (beyond V1 & V2) is still debated. It is hypothesized that visual area V4 represents a vital intermediate stage of processing spatial and curvature information preceding object recognition. Advancements in magnetic resonance imaging hardware and acquisition techniques (e.g., non-BOLD functional MRI) now permits the capture of cortical layer-specific functional properties and organization of the human brain (including the visual system) at high precision.

Methods

Here, we use functional cerebral blood volume measures to study the modularity in how responses to contours (curvature) are organized within area V4 of the human brain. To achieve this at 3 Tesla (a clinically relevant field strength) we utilize optimized high-resolution 3D-Echo Planar Imaging (EPI) Vascular Space Occupancy (VASO) measurements.

Results

Data here provide the first evidence of curvature domains in human V4 that are consistent with previous findings from non-human primates. We show that VASO and BOLD tSNR maps for functional imaging align with high field equivalents, with robust time series of changes to visual stimuli measured across the visual cortex. V4 curvature preference maps for VASO show strong modular organization compared to BOLD imaging contrast. It is noted that BOLD has a much lower sensitivity (due to known venous vasculature weightings) and specificity to stimulus contrast. We show evidence that curvature domains persist across the cortical depth. The work advances our understanding of the role of mid-level area V4 in human processing of curvature and shape features.

Impact

Knowledge of how the functional architecture and hierarchical integration of local contours (curvature) contribute to formation of shapes can inform computational models of object recognition. Techniques described here allow for quantification of individual differences in functional architecture of mid-level visual areas to help drive a better understanding of how changes in functional brain organization relate to difference in visual perception.

NORDIC denoising on VASO data

The use of submillimeter resolution functional magnetic resonance imaging (fMRI) is increasing in popularity due to the prospect of studying human brain activation non-invasively at the scale of cortical layers and columns. This method, known as laminar fMRI, is inherently signal-to-noise ratio (SNR)-limited, especially at lower field strengths, with the dominant noise source being of thermal origin. Furthermore, laminar fMRI is challenged with signal displacements due to draining vein effects in conventional gradient-echo blood oxygen level-dependent (BOLD) imaging contrasts. fMRI contrasts such as cerebral blood volume (CBV)-sensitive vascular space occupancy (VASO) sequences have the potential to mitigate draining vein effects. However, VASO comes along with another reduction in detection sensitivity. NOise Reduction with DIstribution Corrected (NORDIC) PCA (principal component analysis) is a denoising technique specifically aimed at suppressing thermal noise, which has proven useful for increasing the SNR of high-resolution functional data. While NORDIC has been examined for BOLD acquisitions, its application to VASO data has been limited, which was the focus of the present study. We present a preliminary analysis to evaluate NORDIC's capability to suppress thermal noise while preserving the VASO signal across a wide parameter space at 3T. For the data presented here, with a proper set of parameters, NORDIC reduced thermal noise with minimal bias on the underlying signal and preserved spatial resolution. Denoising performance was found to vary with different implementation strategies and parameter choices, for which we provide recommendations. We conclude that when applied properly, NORDIC has the potential to overcome the sensitivity limitations of laminar-specific VASO fMRI. Since very few groups currently have 3T VASO data, by sharing our analysis and code, we can compile and compare the effects of NORDIC across a broader range of acquisition parameters and study designs. Such a communal effort will help develop robust recommendations that will increase the utility of laminar fMRI at lower field strengths.

Differentiating BOLD and non-BOLD signals in fMRI time series using cross-cortical depth delay patterns

Over the past two decades, rapid advancements in magnetic resonance technology have significantly enhanced the imaging resolution of functional Magnetic Resonance Imaging (fMRI), far surpassing its initial capabilities. Beyond mapping brain functional architecture at unprecedented scales, high-spatial-resolution acquisitions have also inspired and enabled several novel analytical strategies that can potentially improve the sensitivity and neuronal specificity of fMRI. With small voxels, one can sample from different levels of the vascular hierarchy within the cerebral cortex and resolve the temporal progression of hemodynamic changes from parenchymal to pial vessels. We propose that this characteristic pattern of temporal progression across cortical depths can aid in distinguishing neurogenic blood-oxygenation-level-dependent (BOLD) signals from typical nuisance factors arising from non-BOLD origins, such as head motion and pulsatility. In this study, we examine the feasibility of applying cross-cortical depth temporal delay patterns to automatically categorize BOLD and non-BOLD signal components in modern-resolution BOLD-fMRI data. We construct an independent component analysis (ICA)-based framework for fMRI de-noising, analogous to previously proposed multi-echo (ME) ICA, except that here we explore the across-depth instead of across-echo dependence to distinguish BOLD and non-BOLD components. The efficacy of this framework is demonstrated using visual task data at three graded spatiotemporal resolutions (voxel sizes = 1.1, 1.5, and 2.0 mm isotropic at temporal intervals = 1700, 1120, and 928 ms). The proposed framework leverages prior knowledge of the spatiotemporal properties of BOLD-fMRI and serves as an alternative to ME-ICA for cleaning moderate- and high-spatial-resolution fMRI data when multi-echo acquisitions are not available.

Enabling brain-wide mapping of layer-specific functional connectivity at 3T via layer-dependent fMRI with draining-vein suppression

Layer-dependent functional magnetic resonance imaging (fMRI) is a promising yet challenging approach for investigating layer-specific functional connectivity (FC). Achieving a brain-wide mapping of layer-specific FC requires several technical advancements, including sub-millimeter spatial resolution, sufficient temporal resolution, functional sensitivity, global brain coverage, and high spatial specificity. Although gradient echo (GE)-based echo planar imaging (EPI) is commonly used for rapid fMRI acquisition, it faces significant challenges due to the draining-vein contamination. In this study, we addressed these limitations by integrating velocity-nulling (VN) gradients into a GE-BOLD fMRI sequence to suppress vascular signals from the vessels with fast-flowing velocity. The extravascular contamination from pial veins was mitigated using a GE-EPI sequence at 3T rather than 7T, combined with phase regression methods. Additionally, we incorporated advanced techniques, including simultaneous multislice (SMS) acceleration and NOise Reduction with DIstribution Corrected principal component analysis (NORDIC PCA) denoising, to improve temporal resolution, spatial coverage, and signal sensitivity. This resulted in a VN fMRI sequence with 0.9-mm isotropic spatial resolution, a repetition time (TR) of 4 seconds, and brain-wide coverage. The VN gradient strength was determined based on results from a button-pressing task. Using resting-state data, we validated layer-specific FC through seed-based analyses, identifying distinct connectivity patterns in the superficial and deep layers of the primary motor cortex (M1), with significant inter-layer differences. Further analyses with a seed in the primary sensory cortex (S1) demonstrated the reliability of the method. Brain-wide layer-dependent FC analyses yielded results consistent with prior literature, reinforcing the efficacy of VN fMRI in resolving layer-specific functional connectivity. Given the widespread availability of 3T scanners, this technical advancement has the potential for significant impact across multiple domains of neuroscience research.

Multilayer Network Analysis across Cortical Depths in Resting-State 7T fMRI

In graph theory, "multilayer networks" represent systems involving several interconnected topological levels. One example in neuroscience is the stratification of connections between different cortical depths or "laminae", which is becoming non-invasively accessible in humans using ultra-high-resolution functional MRI (fMRI). Here, we applied multilayer graph theory to examine functional connectivity across different cortical depths in humans, using 7T fMRI (1-mm3 voxels; 30 participants). Blood oxygenation level dependent (BOLD) signals were derived from five depths between the white matter and pial surface. We compared networks where the inter-regional connections were limited to a single cortical depth only ("layer-by-layer matrices") to those considering all possible connections between areas and cortical depths ("multilayer matrix"). We utilized global and local graph theory features that quantitatively characterize network attributes including network composition, nodal centrality, path-based measures, and hub segregation. Detecting functional differences between cortical depths was improved using multilayer connectomics compared to the layer-by-layer versions. Superficial depths of the cortex dominated information transfer and deeper depths drove clustering. These differences were largest in frontotemporal and limbic regions. fMRI functional connectivity across different cortical depths may contain neurophysiologically relevant information; thus, multilayer connectomics could provide a methodological framework for studies on how information flows across this stratification.

Closed-loop fMRI at the mesoscopic scale of columns and layers: Can we do it and why would we want to?

Technological advances in fMRI including ultra-high magnetic fields (≥ 7 T) and acquisition methods that increase spatial specificity have paved the way for studies of the human cortex at the scale of layers and columns. This mesoscopic scale promises an improved mechanistic understanding of human cortical function so far only accessible to invasive animal neurophysiology. In recent years, an increasing number of studies have applied such methods to better understand the cortical function in perception and cognition. This future perspective article asks whether closed-loop fMRI studies could equally benefit from these methods to achieve layer and columnar specificity. We outline potential applications and discuss the conceptual and concrete challenges, including data acquisition and volitional control of mesoscopic brain activity. We anticipate an important role of fMRI with mesoscopic resolution for closed-loop fMRI and neurofeedback, yielding new insights into brain function and potentially clinical applications.This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Exploring methodological frontiers in laminar fMRI

This review examines the methodological challenges and advancements in laminar functional magnetic resonance imaging (fMRI). With the advent of ultra-high-field MRI scanners, laminar fMRI has become pivotal in elucidating the intricate micro-architectures and functionalities of the human brain at a mesoscopic scale. Despite its profound potential, laminar fMRI faces significant challenges such as signal loss at high spatial resolution, limited specificity to laminar signatures, complex layer-specific analysis, the necessity for precise anatomical alignment, and prolonged acquisition times. This review discusses current methodologies, highlights typical challenges in laminar fMRI research, introduces innovative sequence and analysis methods, and outlines potential solutions for overcoming existing technical barriers. It aims to provide a technical overview of the field's current state, emphasizing both the impact of existing hurdles and the advancements that shape future prospects.

Distal activity patterns shape the spatial specificity of neurovascular coupling

Neurovascular coupling links brain activity to local changes in blood flow, forming the basis for non-invasive brain mapping. Using multiscale imaging, we investigated how vascular activity spatially relates to neuronal activity elicited by single whiskers across different columns and layers of mouse cortex. Here we show that mesoscopic hemodynamic signals quantitatively reflect neuronal activity across space but are composed of a highly heterogeneous pattern of responses across individual vessel segments that is poorly predicted by local neuronal activity. Rather, this heterogeneity is dependent on vessel directionality, specifically in thalamocortical input layer 4, where capillaries respond preferentially to neuronal activity patterns along their downstream perfusion domain. Thus, capillaries fine-tune blood flow based on distant activity and encode laminar-specific activity patterns. These findings imply that vascular anatomy sets a resolution limit on functional imaging signals, where individual blood vessels inaccurately report neuronal activity in their immediate vicinity but, instead, integrate activity patterns along the vascular arbor.

Assessing Cerebral Microvascular Volumetric Pulsatility with High-Resolution 4D CBV MRI at 7T

Arterial pulsation is crucial for promoting fluid circulation and for influencing neuronal activity. Previous studies assessed the pulsatility index based on blood flow velocity pulsatility in relatively large cerebral arteries of human. Here, we introduce a novel method to quantify the volumetric pulsatility of cerebral microvasculature across cortical layers and in white matter (WM), using high-resolution 4D vascular space occupancy (VASO) MRI with simultaneous recording of pulse signals at 7T. Microvascular volumetric pulsatility index (mvPI) and cerebral blood volume (CBV) changes across cardiac cycles are assessed through retrospective sorting of VASO signals into cardiac phases and estimating mean CBV in resting state (CBV0) by arterial spin labeling (ASL) MRI at 7T. Using data from 11 young (28.4±5.8 years) and 7 older (61.3±6.2 years) healthy participants, we investigated the aging effect on mvPI and compared microvascular pulsatility with large arterial pulsatility assessed by 4D-flow MRI. We observed the highest mvPI in the cerebrospinal fluid (CSF) on the cortical surface (0.19±0.06), which decreased towards the cortical layers as well as in larger arteries. In the deep WM, a significantly increased mvPI (p = 0.029) was observed in the older participants compared to younger ones. Additionally, mvPI in deep WM is significantly associated with the velocity pulsatility index (vePI) of large arteries (r = 0.5997, p = 0.0181). We further performed test-retest scans, non-parametric reliability test and simulations to demonstrate the reproducibility and accuracy of our method. To the best of our knowledge, our method offers the first in vivo measurement of microvascular volumetric pulsatility in human brain which has implications for cerebral microvascular health and its relationship research with glymphatic system, aging and neurodegenerative diseases.

Principles of cortical areas and their implications for neuroimaging

Cortical organization should constrain the study of how the brain performs behavior and cognition. A fundamental concept in cortical organization is that of arealization: that the cortex is parceled into discrete areas. In part one of this report, we review how non-human animal studies have illuminated principles of cortical arealization by revealing: (1) what defines a cortical area, (2) how cortical areas are formed, (3) how cortical areas interact with one another, and (4) what "computations" or "functions" areas perform. In part two, we discuss how these principles apply to neuroimaging research. In doing so, we highlight several examples where the commonly accepted interpretation of neuroimaging observations requires assumptions that violate the principles of arealization, including nonstationary areas that move on short time scales, large-scale gradients as organizing features, and cortical areas with singular functionality that perfectly map psychological constructs. Our belief is that principles of neurobiology should strongly guide the nature of computational explanations.

Cortical Layer-Dependent Signaling in Cognition: Three Computational Modes of the Canonical Circuit

The cerebral cortex performs computations via numerous six-layer modules. The operational dynamics of these modules were studied primarily in early sensory cortices using bottom-up computation for response selectivity as a model, which has been recently revolutionized by genetic approaches in mice. However, cognitive processes such as recall and imagery require top-down generative computation. The question of whether the layered module operates similarly in top-down generative processing as in bottom-up sensory processing has become testable by advances in the layer identification of recorded neurons in behaving monkeys. This review examines recent advances in laminar signaling in these two computations, using predictive coding computation as a common reference, and shows that each of these computations recruits distinct laminar circuits, particularly in layer 5, depending on the cognitive demands. These findings highlight many open questions, including how different interareal feedback pathways, originating from and terminating at different layers, convey distinct functional signals.

Laminar multi-contrast fMRI at 7T allows differentiation of neuronal excitation and inhibition underlying positive and negative BOLD responses

A major challenge for human neuroimaging using functional MRI is the differentiation of neuronal excitation and inhibition which may induce positive and negative BOLD responses. Here we present an innovative multi-contrast laminar functional MRI technique that offers comprehensive and quantitative imaging of neurovascular (CBF, CBV, BOLD) and metabolic (CMRO2) responses across cortical layers at 7 Tesla. This technique was first validated through a finger-tapping experiment, revealing 'double-peak' laminar activation patterns within the primary motor cortex. By employing a ring-shaped visual stimulus that elicited positive and negative BOLD responses, we further observed distinct neurovascular and metabolic responses across cortical layers and eccentricities in the primary visual cortex. This suggests potential feedback inhibition of neuronal activities in both superficial and deep cortical layers underlying the negative BOLD signals in the fovea, and also illustrates the neuronal activities in visual areas adjacent to the activated eccentricities.

Laminar CBV and BOLD response-characteristics over time and space in the human primary somatosensory cortex at 7T

Uncovering the cortical representation of the body has been at the core of human brain mapping for decades, with special attention given to the digits. In the last decade, advances in functional magnetic resonance imaging (fMRI) technologies have opened the possibility of noninvasively unraveling the 3rd dimension of digit representations in humans along cortical layers. In laminar fMRI it is common to combine the use of the highly sensitive blood oxygen level dependent (BOLD) contrast with cerebral blood volume sensitive measurements, like vascular space occupancy (VASO), that are more specific to the underlying neuronal populations. However, the spatial and temporal VASO response characteristics across cortical depth to passive stimulation of the digits are still unknown. Therefore, we characterized haemodynamic responses to vibrotactile stimulation of individual digit-tips across cortical depth at 0.75 mm in-plane spatial resolution using BOLD and VASO fMRI at 7T. We could identify digit-specific regions of interest (ROIs) in putative Brodmann area 3b, following the known anatomical organization. In the ROIs, the BOLD response increased towards the cortical surface due to the draining vein effect, while the VASO response was more shifted towards middle cortical layers, likely reflecting bottom-up input from the thalamus, as expected. Interestingly, we also found slightly negative BOLD and VASO responses for non-preferred digits in the ROIs, potentially indicating neuronal surround inhibition. Finally, we explored the temporal signal dynamics for BOLD and VASO as a function of distance from activation peaks resulting from stimulation of contralateral digits. With this analysis, we showed a triphasic response consisting of an initial peak and a subsequent negative deflection during stimulation, followed by a positive post-stimulus response in BOLD and to some extent in VASO. While similar responses were reported with invasive methods in animal models, here we demonstrate a potential neuronal excitation-inhibition mechanism in a center-surround architecture across layers in the human somatosensory cortex. Given that, unlike in animals, human experiments do not rely on anesthesia and can readily implement extensive behavioral testing, obtaining this effect in humans is an important step towards further uncovering the functional significance of the different aspects of the triphasic response.

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.

A fully synthetic three-dimensional human cerebrovascular model based on histological characteristics to investigate the hemodynamic fingerprint of the layer BOLD fMRI signal formation

Recent advances in functional magnetic resonance imaging (fMRI) at ultra-high field (≥7 tesla), novel hardware, and data analysis methods have enabled detailed research on neurovascular function, such as cortical layer-specific activity, in both human and nonhuman species. A widely used fMRI technique relies on the blood oxygen level-dependent (BOLD) signal. BOLD fMRI offers insights into brain function by measuring local changes in cerebral blood volume, cerebral blood flow, and oxygen metabolism induced by increased neuronal activity. Despite its potential, interpreting BOLD fMRI data is challenging as it is only an indirect measurement of neuronal activity. Computational modeling can help interpret BOLD data by simulating the BOLD signal formation. Current developments have focused on realistic 3D vascular models based on rodent data to understand the spatial and temporal BOLD characteristics. While such rodent-based vascular models highlight the impact of the angioarchitecture on the BOLD signal amplitude, anatomical differences between the rodent and human vasculature necessitate the development of human-specific models. Therefore, a computational framework integrating human cortical vasculature, hemodynamic changes, and biophysical properties is essential. Here, we present a novel computational approach: a three-dimensional VAscular MOdel based on Statistics (3D VAMOS), enabling the investigation of the hemodynamic fingerprint of the BOLD signal within a model encompassing a fully synthetic human 3D cortical vasculature and hemodynamics. Our algorithm generates microvascular and macrovascular architectures based on morphological and topological features from the literature on human cortical vasculature. By simulating specific oxygen saturation states and biophysical interactions, our framework characterizes the intravascular and extravascular signal contributions across cortical depth and voxel-wise levels for gradient-echo and spin-echo readouts. Thereby, the 3D VAMOS computational framework demonstrates that using human characteristics significantly affects the BOLD fingerprint, making it an essential step in understanding the fundamental underpinnings of layer-specific fMRI experiments.

On the optimization of 3D inflow-based vascular-space-occupancy (iVASO) MRI for the quantification of arterial cerebral blood volume (CBVa)

PURPOSE

The inflow-based vascular-space-occupancy (iVASO) MRI was originally developed in a single-slice mode to measure arterial cerebral blood volume (CBVa). When vascular crushers are applied in iVASO, the signals can be sensitized predominantly to small pial arteries and arterioles. The purpose of this study is to perform a systematic optimization and evaluation of a 3D iVASO sequence on both 3 T and 7 T for the quantification of CBVa values in the human brain.

METHODS

Three sets of experiments were performed in three separate cohorts. (1) 3D iVASO MRI protocols were compared to single-slice iVASO, and the reproducibility of whole-brain 3D iVASO MRI was evaluated. (2) The effects from different vascular crushers in iVASO were assessed. (3) 3D iVASO MRI results were evaluated in arterial and venous blood vessels identified using ultrasmall-superparamagnetic-iron-oxides-enhanced MRI to validate its arterial origin.

RESULTS

3D iVASO scans showed signal-to-noise ratio (SNR) and CBVa measures consistent with single-slice iVASO with reasonable intrasubject reproducibility. Among the iVASO scans performed with different vascular crushers, the whole-brain 3D iVASO scan with a motion-sensitized-driven-equilibrium preparation with two binomial refocusing pulses and an effective TE of 50 ms showed the best suppression of macrovascular signals, with a relatively low specific absorption rate. When no vascular crusher was applied, the CBVa maps from 3D iVASO scans showed large CBVa values in arterial vessels but well-suppressed signals in venous vessels.

CONCLUSION

A whole-brain 3D iVASO MRI scan was optimized for CBVa measurement in the human brain. When only microvascular signals are desired, a motion-sensitized-driven-equilibrium-based vascular crusher with binomial refocusing pulses can be applied in 3D iVASO.

Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging

Recent advances in neuroscience requires high-resolution MRI to decipher the structural and functional details of the brain. Developing a high-performance gradient system is an ongoing effort in the field to facilitate high spatial and temporal encoding. Here, we proposed a head-only gradient system NeuroFrontier, dedicated for neuroimaging with an ultra-high gradient strength of 650 mT/m and 600 T/m/s. The proposed system features in 1) ultra-high power of 7MW achieved by running two gradient power amplifiers using a novel paralleling method; 2) a force/torque balanced gradient coil design with a two-step mechanical structure that allows high-efficiency and flexible optimization of the peripheral nerve stimulation; 3) a high-density integrated RF system that is miniaturized and customized for the head-only system; 4) an AI-empowered compressed sensing technique that enables ultra-fast acquisition of high-resolution images and AI-based acceleration in q-t space for diffusion MRI (dMRI); and 5) a prospective head motion correction technique that effectively corrects motion artifacts in real-time with 3D optical tracking. We demonstrated the potential advantages of the proposed system in imaging resolution, speed, and signal-to-noise ratio for 3D structural MRI (sMRI), functional MRI (fMRI) and dMRI in neuroscience applications of submillimeter layer-specific fMRI and dMRI. We also illustrated the unique strength of this system for dMRI-based microstructural mapping, e.g., enhanced lesion contrast at short diffusion-times or high b-values, and improved estimation accuracy for cellular microstructures using diffusion-time-dependent dMRI or for neurite microstructures using q-space approaches.

Mesoscale organization of ventral and dorsal visual pathways in macaque monkey revealed by 7T fMRI

In human and nonhuman primate brains, columnar (mesoscale) organization has been demonstrated to underlie both lower and higher order aspects of visual information processing. Previous studies have focused on identifying functional preferences of mesoscale domains in specific areas; but there has been little understanding of how mesoscale domains may cooperatively respond to single visual stimuli across dorsal and ventral pathways. Here, we have developed ultrahigh-field 7 T fMRI methods to enable simultaneous mapping, in individual macaque monkeys, of response in both dorsal and ventral pathways to single simple color and motion stimuli. We provide the first evidence that anatomical V2 cytochrome oxidase-stained stripes are well aligned with fMRI maps of V2 stripes, settling a long-standing controversy. In the ventral pathway, a systematic array of paired color and luminance processing domains across V4 was revealed, suggesting a novel organization for surface information processing. In the dorsal pathway, in addition to high quality motion direction maps of MT, MST and V3A, alternating color and motion direction domains in V3 are revealed. As well, submillimeter motion domains were observed in peripheral LIPd and LIPv. In sum, our study provides a novel global snapshot of how mesoscale networks in the ventral and dorsal visual pathways form the organizational basis of visual objection recognition and vision for action.

Multimodal layer modelling reveals in vivo pathology in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a rapidly progressing neurodegenerative disease characterized by the loss of motor control. Current understanding of ALS pathology is largely based on post-mortem investigations at advanced disease stages. A systematic in vivo description of the microstructural changes that characterize early stage ALS, and their subsequent development, is so far lacking. Recent advances in ultra-high field (7 T) MRI data modelling allow us to investigate cortical layers in vivo. Given the layer-specific and topographic signature of ALS pathology, we combined submillimetre structural 7 T MRI data (qT1, QSM), functional localizers of body parts (upper limb, lower limb, face) and layer modelling to systematically describe pathology in the primary motor cortex (M1), in 12 living ALS patients with reference to 12 matched controls. Longitudinal sampling was performed for a subset of patients. We calculated multimodal pathology maps for each layer (superficial layer, layer 5a, layer 5b, layer 6) of M1 to identify hot spots of demyelination, iron and calcium accumulation in different cortical fields. We show preserved mean cortical thickness and layer architecture of M1, despite significantly increased iron in layer 6 and significantly increased calcium in layer 5a and superficial layer, in patients compared to controls. The behaviourally first-affected cortical field shows significantly increased iron in L6 compared to other fields, while calcium accumulation is atopographic and significantly increased in the low myelin borders between cortical fields compared to the fields themselves. A subset of patients with longitudinal data shows that the low myelin borders are particularly disrupted and that calcium hot spots, but to a lesser extent iron hot spots, precede demyelination. Finally, we highlight that a very slow progressing patient (Patient P4) shows a distinct pathology profile compared to the other patients. Our data show that layer-specific markers of in vivo pathology can be identified in ALS patients with a single 7 T MRI measurement after first diagnosis, and that such data provide critical insights into the individual disease state. Our data highlight the non-topographic architecture of ALS disease spread and the role of calcium, rather than iron accumulation, in predicting future demyelination. We also highlight a potentially important role of low myelin borders, that are known to connect to multiple areas within the M1 architecture, in disease spread. Finally, the distinct pathology profile of a very-slow progressing patient (Patient P4) highlights a distinction between disease duration and progression. Our findings demonstrate the importance of in vivo histology imaging for the diagnosis and prognosis of neurodegenerative diseases such as ALS.

Cortical depth profiles in primary visual cortex for illusory and imaginary experiences

Visual illusions and mental imagery are non-physical sensory experiences that involve cortical feedback processing in the primary visual cortex. Using laminar functional magnetic resonance imaging (fMRI) in two studies, we investigate if information about these internal experiences is visible in the activation patterns of different layers of primary visual cortex (V1). We find that imagery content is decodable mainly from deep layers of V1, whereas seemingly 'real' illusory content is decodable mainly from superficial layers. Furthermore, illusory content shares information with perceptual content, whilst imagery content does not generalise to illusory or perceptual information. Together, our results suggest that illusions and imagery, which differ immensely in their subjective experiences, also involve partially distinct early visual microcircuits. However, overlapping microcircuit recruitment might emerge based on the nuanced nature of subjective conscious experience.

Alpha-180 spin-echo based line-scanning method for high resolution laminar-specific fMRI

Laminar-specific functional magnetic resonance imaging (fMRI) has been widely used to study circuit-specific neuronal activity by mapping spatiotemporal fMRI response patterns across cortical layers. Hemodynamic responses reflect indirect neuronal activity given limit of spatial and temporal resolution. Previous gradient-echo based line-scanning fMRI (GELINE) method was proposed with high temporal (50 ms) and spatial (50 µm) resolution to better characterize the fMRI onset time across cortical layers by employing 2 saturation RF pulses. However, the imperfect RF saturation performance led to poor boundary definition of the reduced region of interest (ROI) and aliasing problems outside of the ROI. Here, we propose α (alpha)-180 spin-echo-based line-scanning fMRI (SELINE) method to resolve this issue by employing a refocusing 180° RF pulse perpendicular to the excitation slice. In contrast to GELINE signals peaked at the superficial layer, we detected varied peaks of laminar-specific BOLD signals across deeper cortical layers with the SELINE method, indicating the well-defined exclusion of the large drain-vein effect with the spin-echo sequence. Furthermore, we applied the SELINE method with 200 ms TR to sample the fast hemodynamic changes across cortical layers with a less draining vein effect. In summary, this SELINE method provides a novel acquisition scheme to identify microvascular-sensitive laminar-specific BOLD responses across cortical depth.

Characterisation of laminar and vascular spatiotemporal dynamics of CBV and BOLD signals using VASO and ME-GRE at 7T in humans

Interpretation of cortical laminar functional magnetic resonance imaging (fMRI) activity requires detailed knowledge of the spatiotemporal haemodynamic response across vascular compartments due to the well-known vascular biases (e.g. the draining veins). Further complications arise from the spatiotemporal hemodynamic response that differs depending on the duration of stimulation. This information is crucial for future studies using depth-dependent cerebral blood volume (CBV) measurements, which promise higher specificity for the cortical microvasculature than the blood oxygenation level dependent (BOLD) contrast. To date, direct information about CBV dynamics with respect to stimulus duration, cortical depth and vasculature is missing in humans. Therefore, we characterized the cortical depth-dependent CBV-haemodynamic responses across a wide set of stimulus durations with 0.9 mm isotropic spatial and 0.785 seconds effective temporal resolution in humans using slice-selective slab-inversion vascular space occupancy (SS-SI VASO). Additionally, we investigated signal contributions from macrovascular compartments using fine-scale vascular information from multi-echo gradient-echo (ME-GRE) data at 0.35 mm isotropic resolution. In total, this resulted in >7.5h of scanning per participant (n=5). We have three major findings: (I) While we could demonstrate that 1 second stimulation is viable using VASO, more than 12 seconds stimulation provides better CBV responses in terms of specificity to microvasculature, but durations beyond 24 seconds of stimulation may be wasteful for certain applications. (II) We observe that CBV responses show dilation patterns across the cortex. (III) While we found increasingly strong BOLD signal responses in vessel-dominated voxels with longer stimulation durations, we found increasingly strong CBV signal responses in vessel-dominated voxels only until 4 second stimulation durations. After 4 seconds, only the signal from non-vessel dominated voxels kept increasing. This might explain why CBV responses are more specific to the underlying neuronal activity for long stimulus durations.

Next-generation MRI scanner designed for ultra-high-resolution human brain imaging at 7 Tesla

To increase granularity in human neuroimaging science, we designed and built a next-generation 7 Tesla magnetic resonance imaging scanner to reach ultra-high resolution by implementing several advances in hardware. To improve spatial encoding and increase the image signal-to-noise ratio, we developed a head-only asymmetric gradient coil (200 mT m-1, 900 T m-1s-1) with an additional third layer of windings. We integrated a 128-channel receiver system with 64- and 96-channel receiver coil arrays to boost signal in the cerebral cortex while reducing g-factor noise to enable higher accelerations. A 16-channel transmit system reduced power deposition and improved image uniformity. The scanner routinely performs functional imaging studies at 0.35-0.45 mm isotropic spatial resolution to reveal cortical layer functional activity, achieves high angular resolution in diffusion imaging and reduces acquisition time for both functional and structural imaging.

Reduced dimension stimulus decoding and column-based modeling reveal architectural differences of primary somatosensory finger maps between younger and older adults

The primary somatosensory cortex (SI) contains fine-grained tactile representations of the body, arranged in an orderly fashion. The use of ultra-high resolution fMRI data to detect group differences, for example between younger and older adults' SI maps, is challenging, because group alignment often does not preserve the high spatial detail of the data. Here, we use robust-shared response modeling (rSRM) that allows group analyses by mapping individual stimulus-driven responses to a lower dimensional shared feature space, to detect age-related differences in tactile representations between younger and older adults using 7T-fMRI data. Using this method, we show that finger representations are more precise in Brodmann-Area (BA) 3b and BA1 compared to BA2 and motor areas, and that this hierarchical processing is preserved across age groups. By combining rSRM with column-based decoding (C-SRM), we further show that the number of columns that optimally describes finger maps in SI is higher in younger compared to older adults in BA1, indicating a greater columnar size in older adults' SI. Taken together, we conclude that rSRM is suitable for finding fine-grained group differences in ultra-high resolution fMRI data, and we provide first evidence that the columnar architecture in SI changes with increasing age.

Laminar differences in functional oxygen metabolism in monkey visual cortex measured with calibrated fMRI

Blood-oxygenation-level-dependent functional magnetic resonance imaging (BOLD fMRI) of cortical layers relies on the hemodynamic response and is biased toward large veins on the cortical surface. Functional changes in the cerebral metabolic rate of oxygen (ΔCMRO2) may reflect neural cortical function better than BOLD fMRI, but it is unknown whether the calibrated BOLD model for functional CMRO2 measurement remains valid at high resolution. Here, we measure laminar ΔCMRO2 elicited by visual stimulation in macaque primary visual cortex (V1) and find that ΔCMRO2 peaks in the middle of the cortex, in agreement with autoradiographic measures of metabolism. ΔCMRO2 values in gray matter are similar as found previously. Reductions in CMRO2 are associated with veins at the cortical surface, suggesting that techniques for vein removal may improve the accuracy of the model at very high resolution. However, our results show feasibility of laminar ΔCMRO2 measurement, providing a physiologically meaningful metric of laminar functional metabolism.

Improved dynamic distortion correction for fMRI using single-echo EPI and a readout-reversed first image (REFILL)

The boundaries between tissues with different magnetic susceptibilities generate inhomogeneities in the main magnetic field which change over time due to motion, respiration and system instabilities. The dynamically changing field can be measured from the phase of the fMRI data and corrected. However, methods for doing so need multi-echo data, time-consuming reference scans and/or involve error-prone processing steps, such as phase unwrapping, which are difficult to implement robustly on the MRI host. The improved dynamic distortion correction method we propose is based on the phase of the single-echo EPI data acquired for fMRI, phase offsets calculated from a triple-echo, bipolar reference scan of circa 3-10 s duration using a method which avoids the need for phase unwrapping and an additional correction derived from one EPI volume in which the readout direction is reversed. This Reverse-Encoded First Image and Low resoLution reference scan (REFILL) approach is shown to accurately measure B0 as it changes due to shim, motion and respiration, even with large dynamic changes to the field at 7 T, where it led to a > 20% increase in time-series signal to noise ratio compared to data corrected with the classic static approach. fMRI results from REFILL-corrected data were free of stimulus-correlated distortion artefacts seen when data were corrected with static field mapping. The method is insensitive to shim changes and eddy current differences between the reference scan and the fMRI time series, and employs calculation steps that are simple and robust, allowing most data processing to be performed in real time on the scanner image reconstruction computer. These improvements make it feasible to routinely perform dynamic distortion correction in fMRI.

Mitigating susceptibility-induced distortions in high-resolution 3DEPI fMRI at 7T

Geometric distortion is a major limiting factor for spatial specificity in high-resolution fMRI using EPI readouts and is exacerbated at higher field strengths due to increased B0 field inhomogeneity. Prominent correction schemes are based on B0 field-mapping or acquiring reverse phase-encoded (reversed-PE) data. However, to date, comparisons of these techniques in the context of fMRI have only been performed on 2DEPI data, either at lower field or lower resolution. In this study, we investigate distortion compensation in the context of sub-millimetre 3DEPI data at 7T. B0 field-mapping and reversed-PE distortion correction techniques were applied to both partial coverage BOLD-weighted and whole brain MT-weighted 3DEPI data with matched distortion. Qualitative assessment showed overall improvement in cortical alignment for both correction techniques in both 3DEPI fMRI and whole-brain MT-3DEPI datasets. The distortion-corrected MT-3DEPI images were quantitatively evaluated by comparing cortical alignment with an anatomical reference using dice coefficient (DC) and correlation ratio (CR) measures. These showed that B0 field-mapping and reversed-PE methods both improved correspondence between the MT-3DEPI and anatomical data, with more substantial improvements consistently obtained using the reversed-PE approach. Regional analyses demonstrated that the largest benefit of distortion correction, and in particular of the reversed-PE approach, occurred in frontal and temporal regions where susceptibility-induced distortions are known to be greatest, but had not led to complete signal dropout. In conclusion, distortion correction based on reversed-PE data has shown the greater capacity for achieving faithful alignment with anatomical data in the context of high-resolution fMRI at 7T using 3DEPI.

Layer-fMRI VASO with short stimuli and event-related designs at 7 T

Layers and columns are the dominant processing units in the human (neo)cortex at the mesoscopic scale. While the blood oxygenation dependent (BOLD) signal has a high detection sensitivity, it is biased towards unwanted signals from large draining veins at the cortical surface. The additional fMRI contrast of vascular space occupancy (VASO) has the potential to augment the neuroscientific interpretability of layer-fMRI results by means of capturing complementary information of locally specific changes in cerebral blood volume (CBV). Specifically, VASO is not subject to unwanted sensitivity amplifications of large draining veins. Because of constrained sampling efficiency, it has been mainly applied in combination with efficient block task designs and long trial durations. However, to study cognitive processes in neuroscientific contexts, or probe vascular reactivity, short stimulation periods are often necessary. Here, we developed a VASO acquisition procedure with a short acquisition period and sub-millimeter resolution. During visual event-related stimulation, we show reliable responses in visual cortices within a reasonable number of trials (∼20). Furthermore, the short TR and high spatial specificity of our VASO implementation enabled us to show differences in laminar reactivity and onset times. Finally, we explore the generalizability to a different stimulus modality (somatosensation). With this, we showed that CBV-sensitive VASO provides the means to capture layer-specific haemodynamic responses with high spatio-temporal resolution and is able to be used with event-related paradigms.

Modeling venous bias in resting state functional MRI metrics

Resting-state (rs) functional magnetic resonance imaging (fMRI) is used to detect low-frequency fluctuations in the blood oxygen-level dependent (BOLD) signal across brain regions. Correlations between temporal BOLD signal fluctuations are commonly used to infer functional connectivity. However, because BOLD is based on the dilution of deoxyhemoglobin, it is sensitive to veins of all sizes, and its amplitude is biased by draining veins. These biases affect local BOLD signal location and amplitude, and may also influence BOLD-derived connectivity measures, but the magnitude of this venous bias and its relation to vein size and proximity is unknown. Here, veins were identified using high-resolution quantitative susceptibility maps and utilized in a biophysical model to investigate systematic venous biases on common local rsfMRI-derived measures. Specifically, we studied the impact of vein diameter and distance to veins on the amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF), Hurst exponent (HE), regional homogeneity (ReHo), and eigenvector centrality values in the grey matter. Values were higher across all distances in smaller veins, and decreased with increasing vein diameter. Additionally, rsfMRI values associated with larger veins decrease with increasing distance from the veins. ALFF and ReHo were the most biased by veins, while HE and fALFF exhibited the smallest bias. Across all metrics, the amplitude of the bias was limited in voxel-wise data, confirming that venous structure is not the dominant source of contrast in these rsfMRI metrics. Finally, the models presented can be used to correct this venous bias in rsfMRI metrics.

Acquisition and processing methods of whole-brain layer-fMRI VASO and BOLD: The Kenshu dataset

Cortical depth-dependent functional magnetic resonance image (fMRI), also known as layer-fMRI, has the potential to capture directional neural information flow of brain computations within and across large-scale cortical brain networks. E.g., layer-fMRI can differentiate feedforward and feedback cortical input in hierarchically organized brain networks. Recent advancements in 3D-EPI sampling approaches and MR contrast generation strategies have allowed proof-of-principle studies showing that layer-fMRI can provide sufficient data quality for capturing laminar changes in functional connectivity. These studies have however not shown how reliable the signal is and how repeatable the respective results are. It is especially unclear whether whole-brain layer-fMRI functional connectivity protocols are widely applicable across common neuroscience-driven analysis approaches. Moreover, there are no established preprocessing fMRI methods that are optimized to work for whole-brain layer-fMRI datasets. In this work, we aimed to serve the field of layer-fMRI and build tools for future routine whole-brain layer-fMRI in application-based neuroscience research. We have developed publicly available sequences, acquisition protocols, and processing pipelines for whole-brain layer-fMRI. These protocols are validated across 60 hours of scanning in nine participants. Specifically, we identified and exploited methodological advancements for maximizing tSNR efficiency and test-retest reliability. We are sharing an extensive multi-modal whole-brain layer-fMRI dataset (20 scan hours of movie-watching in a single participant) for the purpose of benchmarking future method developments: The Kenshu dataset. With this dataset, we are also exemplifying the usefulness of whole brain layer-fMRI for commonly applied analysis approaches in modern cognitive neuroscience fMRI studies. This includes connectivity analyses, representational similarity matrix estimations, general linear model analyses, principal component analysis clustering, etc. We believe that this work paves the road for future routine measurements of directional functional connectivity across the entire brain.

Functional magnetic particle imaging (fMPI) of cerebrovascular changes in the rat brain during hypercapnia

Objective.Non-invasive functional brain imaging modalities are limited in number, each with its own complex trade-offs between sensitivity, spatial and temporal resolution, and the directness with which the measured signals reflect neuronal activation. Magnetic particle imaging (MPI) directly maps the cerebral blood volume (CBV), and its high sensitivity derives from the nonlinear magnetization of the superparamagnetic iron oxide nanoparticle (SPION) tracer confined to the blood pool. Our work evaluates functional MPI (fMPI) as a new hemodynamic functional imaging modality by mapping the CBV response in a rodent model where CBV is modulated by hypercapnic breathing manipulation.Approach.The rodent fMPI time-series data were acquired with a mechanically rotating field-free line MPI scanner capable of 5 s temporal resolution and 3 mm spatial resolution. The rat's CBV was modulated for 30 min with alternating 5 min hyper-/hypocapnic states, and processed using conventional fMRI tools. We compare our results to fMRI responses undergoing similar hypercapnia protocols found in the literature, and reinforce this comparison in a study of one rat with 9.4T BOLD fMRI using the identical protocol.Main results.The initial image in the time-series showed mean resting brain voxel SNR values, averaged across rats, of 99.9 following the first 10 mg kg-1SPION injection and 134 following the second. The time-series fit a conventional General Linear Model with a 15%-40% CBV change and a peak pixel CNR between 12 and 29, 2-6× higher than found in fMRI.Significance.This work introduces a functional modality with high sensitivity, although currently limited spatial and temporal resolution. With future clinical-scale development, a large increase in sensitivity could supplement other modalities and help transition functional brain imaging from a neuroscience tool focusing on population averages to a clinically relevant modality capable of detecting differences in individual patients.

Evaluating the capabilities and challenges of layer-fMRI VASO at 3T

Sub-millimeter functional imaging has the potential to capture cortical layer-specific functional information flow within and across brain systems. Recent sequence advancements of fMRI signal readout and contrast generations resulted in wide adaptation of layer-fMRI protocols across the global ultra-high-field (UHF) neuroimaging community. However, most layer-fMRI applications are confined to one of ≈100 privileged UHF imaging centers, and sequence contrasts with unwanted sensitivity to large draining veins. In this work, we propose the application of vein-signal free vascular space occupancy (VASO) layer-fMRI sequences at widely accessible 3T scanners. Specifically, we implement, characterize, and apply a cerebral blood volume (CBV)-sensitive VASO fMRI at a 3T scanner setup, as it is typically used in the majority of cognitive neuroscience and clinical neuroscience fMRI studies. We find that the longerT 2 * , and stronger relative T 1 contrast at 3T can account for some of the lower z-magnetization in the inversion-recovery VASO sequence compared to 7T and 9.4T. In the main series of experiments (N=16), we test the utility of this setup for motor tasks and find that -while being limited by thermal noise- 3T layer-fMRI VASO is feasible within conventional scan durations. In a series of auxiliary studies, we furthermore explore the generalizability of the developed layer-fMRI protocols for a larger range of study designs including: visual stimulation, whole brain movie watching paradigms, and cognitive tasks with weaker effect sizes. We hope that the developed imaging protocols will help to increase accessibility of vein-signal free layer-fMRI imaging tools to a wider community of neuroimaging centers.

Design and application of a multimodality-compatible 1Tx/6Rx RF coil for monkey brain MRI at 7T

OBJECTIVE

Blood-oxygen-level-dependent functional MRI allows to investigte neural activities and connectivity. While the non-human primate plays an essential role in neuroscience research, multimodal methods combining functional MRI with other neuroimaging and neuromodulation enable us to understand the brain network at multiple scales.

APPROACH

In this study, a tight-fitting helmet-shape receive array with a single transmit loop for anesthetized macaque brain MRI at 7T was fabricated with four openings constructed in the coil housing to accommodate multimodal devices, and the coil performance was quantitatively evaluated and compared to a commercial knee coil. In addition, experiments over three macaques with infrared neural stimulation (INS), focused ultrasound stimulation (FUS), and transcranial direct current stimulation (tDCS) were conducted.

MAIN RESULTS

The RF coil showed higher transmit efficiency, comparable homogeneity, improved SNR and enlarged signal coverage over the macaque brain. Infrared neural stimulation was applied to the amygdala in deep brain region, and activations in stimulation sites and connected sites were detected, with the connectivity consistent with anatomical information. Focused ultrasound stimulation was applied to the left visual cortex, and activations were acquired along the ultrasound traveling path, with all time course curves consistent with pre-designed paradigms. The existence of transcranial direct current stimulation electrodes brought no interference to the RF system, as evidenced through high-resolution MPRAGE structure images.

SIGNIFICANCE

This pilot study reveals the feasibility for brain investigation at multiple spatiotemporal scales, which may advance our understanding in dynamic brain networks.

A custom MR-compatible dataglove for fMRI of the human motor cortex at 7T

We present a custom-built MR-compatible data glove to capture hand motion during concurrent fMRI experiments at 7 Tesla. Thermal and phantom tests showed our data glove can be used safely and without degradation of image quality. Subject-specific Blood Oxygen Level Dependent (BOLD) signal models, for use in fMRI analysis, were constructed based on recorded kinematic measurements. Experiments revealed the relative fMRI BOLD signal contribution of flexing, extending, and sustained isotonic extension. The ability to evaluate subject performance in real-time and create subject-specific BOLD signal models enables a wide range of experimental paradigms with improved data quality.Clinical Relevance- Using an MR compatible dataglove, subject specific Blood Oxygen Signal Level Dependent (BOLD) signal models can be constructed to study how the brain implements fine motor control.

Odor-evoked layer-specific fMRI activities in the awake mouse olfactory bulb

Awake rodent fMRI is increasingly common over the use of anesthesia since it permits behavioral paradigms and does not confound normal brain function or neurovascular coupling. It is well established that adequate acclimation to the loud fMRI environment and head fixation reduces stress in the rodents and allows for whole brain imaging with little contamination from motion. However, it is unknown whether high-resolution fMRI with increased susceptibility to motion and lower sensitivity can measure small, but spatially discrete, activations in awake mice. To examine this, we used contrast-enhanced cerebral blood volume-weighted (CBVw) fMRI in the mouse olfactory bulb for its enhanced sensitivity and neural specificity. We determined that activation patterns in the glomerular layer to four different odors were spatially distinct and were consistent with previously established histological patterns. In addition, odor-evoked laminar activations were greatest in superficial layers that decreased with laminar depth, similar to previous observations. Interestingly, the fMRI response strengths in the granule cell layer were greater in awake mice than our previous anesthetized rat studies, suggesting that feedback neural activities were intact with wakefulness. We finally determined that fMRI signal changes to repeated odor exposure (i.e., olfactory adaptation) attenuated relatively more in the feedback granule cell layer compared to the input glomerular layer, which is consistent with prior observations. We, therefore, conclude that high-resolution CBVw fMRI can measure odor-specific activation patterns and distinguish changes in laminar activity of head and body restrained awake mice.