How much cortex can a vein drain? Downstream dilution of activation-related cerebral blood oxygenation changes

Functional MRI study with conductivity signal changes during visual stimulation

BACKGROUND

Although blood oxygen level-dependent (BOLD) functional MRI (fMRI) is a standard method, major BOLD signals primarily originate from intravascular sources. Magnetic resonance electrical properties tomography (MREPT)-based fMRI signals may provide additional insights into electrical activity caused by alterations in ion concentrations and mobilities.

PURPOSE

This study aimed to investigate the neuronal response of conductivity during visual stimulation and compare it with BOLD.

MATERIALS AND METHODS

A total of 30 young, healthy volunteers participated in two independent experiments using BOLD and MREPT techniques with a visual stimulation paradigm at 3 T MRI. The first set of MREPT fMRI data was obtained using a multi-echo spin-echo (SE) echo planar imaging (EPI) sequence from 14 participants. The second set of MREPT fMRI data was collected from 16 participants using both a single-echo SE-EPI and a single-echo three-dimensional (3D) balanced fast-field-echo (bFFE) sequence. We reconstructed the time-course Larmor frequency conductivity to evaluate hemodynamics.

RESULTS

Conductivity values slightly increased during visual stimulation. Activation strengths were consistently stronger with BOLD than with conductivity for both SE-EPI MREPT and bFFE MREPT. Additionally, the activated areas were always larger with BOLD than MREPT. Some participants also exhibited decreased conductivity values during visual stimulations. In Experiment 1, conductivity showed significant differences between the fixation and visual stimulation blocks in the secondary visual cortex (SVC) and cuneus, with conductivity differences of 0.43 % and 0.47 %, respectively. No significant differences in conductivity were found in the cerebrospinal fluid (CSF) areas between the two blocks. In Experiment 2, significant conductivity differences were observed between the two blocks in the SVC, cuneus, and lingual gyrus for SE-EPI MREPT, with differences of 0.90 %, 0.67 %, and 0.24 %, respectively. Again, no significant differences were found in the CSF areas.

CONCLUSION

Conductivity values increased slightly during visual stimulation in the visual cortex areas but were much weaker than BOLD responses. The conductivity change during visual stimulation was less than 1 % compared to the fixation block. No significant differences in conductivity were observed between the primary visual cortex (PVC)-CSF and SVC-CSF during fixation and visual stimulations, suggesting that the observed conductivity changes may not be related to CSF changes in the visual cortex but rather to diffusion changes. Future research should explore the potential of MREPT to detect neuronal electrical activity and hemodynamic changes, with further optimization of the MREPT technique.

Leveraging ultra-high field (7T) MRI in psychiatric research

Non-invasive brain imaging has played a critical role in establishing our understanding of the neural properties that contribute to the emergence of psychiatric disorders. However, characterizing core neurobiological mechanisms of psychiatric symptomatology requires greater structural, functional, and neurochemical specificity than is typically obtainable with standard field strength MRI acquisitions (e.g., 3T). Ultra-high field (UHF) imaging at 7 Tesla (7T) provides the opportunity to identify neurobiological systems that confer risk, determine etiology, and characterize disease progression and treatment outcomes of major mental illnesses. Increases in scanner availability, regulatory approval, and sequence availability have made the application of UHF to clinical cohorts more feasible than ever before, yet the application of UHF approaches to the study of mental health remains nascent. In this technical review, we describe core neuroimaging methodologies which benefit from UHF acquisition, including high resolution structural and functional imaging, single (1H) and multi-nuclear (e.g., 31P) MR spectroscopy, and quantitative MR techniques for assessing brain tissue iron and myelin. We discuss advantages provided by 7T MRI, including higher signal- and contrast-to-noise ratio, enhanced spatial resolution, increased test-retest reliability, and molecular and neurochemical specificity, and how these have begun to uncover mechanisms of psychiatric disorders. Finally, we consider current limitations of UHF in its application to clinical cohorts, and point to ongoing work that aims to overcome technical hurdles through the continued development of UHF hardware, software, and protocols.

Widespread Autonomic Physiological Coupling Across the Brain-Body Axis

The brain is closely attuned to visceral signals from the body's internal environment, as evidenced by the numerous associations between neural, hemodynamic, and peripheral physiological signals. We show that these brain-body co-fluctuations can be captured by a single spatiotemporal pattern. Across several independent samples, as well as single-echo and multi-echo fMRI data acquisition sequences, we identify widespread co-fluctuations in the low-frequency range (0.01 - 0.1 Hz) between resting-state global fMRI signals, neural activity, and a host of autonomic signals spanning cardiovascular, pulmonary, exocrine and smooth muscle systems. The same brain-body co-fluctuations observed at rest are elicited by arousal induced by cued deep breathing and intermittent sensory stimuli, as well as spontaneous phasic EEG events during sleep. Further, we show that the spatial structure of global fMRI signals is maintained under experimental suppression of end-tidal carbon dioxide (PETCO2) variations, suggesting that respiratory-driven fluctuations in arterial CO2 accompanying arousal cannot explain the origin of these signals in the brain. These findings establish the global fMRI signal as a significant component of the arousal response governed by the autonomic nervous system.

High Spatiotemporal Resolution Radial Encoding Single-Vessel fMRI

High-field preclinical functional MRI (fMRI) is enabled the high spatial resolution mapping of vessel-specific hemodynamic responses, that is single-vessel fMRI. In contrast to investigating the neuronal sources of the fMRI signal, single-vessel fMRI focuses on elucidating its vascular origin, which can be readily implemented to identify vascular changes relevant to vascular dementia or cognitive impairment. However, the limited spatial and temporal resolution of fMRI is hindered hemodynamic mapping of intracortical microvessels. Here, the radial encoding MRI scheme is implemented to measure BOLD signals of individual vessels penetrating the rat somatosensory cortex. Radial encoding MRI is employed to map cortical activation with a focal field of view (FOV), allowing vessel-specific functional mapping with 50 × 50 µm2 in-plane resolution at a 1 to 2 Hz sampling rate. Besides detecting refined hemodynamic responses of intracortical micro-venules, the radial encoding-based single-vessel fMRI enables the distinction of fMRI signals from vessel and peri-vessel voxels due to the different contribution of intravascular and extravascular effects.

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.

The temporal specificity of BOLD fMRI is systematically related to anatomical and vascular features of the human brain

The ability to detect fast responses with functional MRI depends on the speed of hemodynamic responses to neural activity, because hemodynamic responses act as a temporal low-pass filter smoothing out rapid changes. However, hemodynamic responses (their shape and timing) are highly variable across the brain and across stimuli. This heterogeneity of responses implies that the temporal specificity of fMRI signals, or the ability of fMRI to preserve fast information, should also vary substantially across the cortex. In this work we investigated how local differences in hemodynamic response timing impact the temporal specificity of fMRI. We conducted our research using ultra-high field (7T) fMRI at high spatiotemporal resolution, using the primary visual cortex (V1) as a model area for investigation. We used visual stimuli oscillating at slow and fast frequencies to probe the temporal specificity of individual voxels. As expected, we identified substantial variability in temporal specificity, with some voxels preserving their responses to fast neural activity more effectively than others. We investigated which voxels had the highest temporal specificity and related those to anatomical and vascular features of V1. We found that low temporal specificity is only weakly explained by the presence of large veins or cerebral cortical depth. Notably, however, temporal specificity depended strongly on a voxel's position along the anterior-posterior anatomical axis of V1, with voxels within the calcarine sulcus being capable of preserving close to 25% of their amplitude as the frequency of stimulation increased from 0.05-Hz to 0.20-Hz, and voxels nearest to the occipital pole preserving less than 18%. These results indicate that detection biases in high-resolution fMRI will depend on the anatomical and vascular features of the area being imaged, and that these biases will differ depending on the timing of the underlying neuronal activity. Importantly, this spatial heterogeneity of temporal specificity suggests that it could be exploited to achieve higher specificity in some locations, and that tailored data analysis strategies may help improve the detection and interpretation of fast fMRI responses.

Evaluating the effect of denoising submillimeter auditory fMRI data with NORDIC

Functional magnetic resonance imaging (fMRI) has emerged as an essential tool for exploring human brain function. Submillimeter fMRI, in particular, has emerged as a tool to study mesoscopic computations. The inherently low signal-to-noise ratio (SNR) at submillimeter resolutions warrants the use of denoising approaches tailored at reducing thermal noise - the dominant contributing noise component in high resolution fMRI. NORDIC PCA is one of such approaches, and has been benchmarked against other approaches in several applications. Here, we investigate the effects that two versions of NORDIC denoising have on auditory submillimeter data. As investigating auditory functional responses poses unique challenges, we anticipated that the benefit of this technique would be especially pronounced. Our results show that NORDIC denoising improves the detection sensitivity and the reliability of estimates in submillimeter auditory fMRI data. These effects can be explained by the reduction of the noise-induced signal variability. However, we also observed a reduction in the average response amplitude (percent signal), which may suggest that a small amount of signal was also removed. We conclude that, while evaluating the effects of the signal reduction induced by NORDIC may be necessary for each application, using NORDIC in high resolution auditory fMRI studies may be advantageous because of the large reduction in variability of the estimated responses.

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

In graph theory, "multilayer networks" represent systems involving several interconnected topological levels. A neuroscience example is the hierarchy of connections between different cortical depths or "lamina". This hierarchy 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 then 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 regions and cortical depths ("multilayer matrix"). We utilized global and local graph theory features that quantitatively characterize network attributes such as 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 aspects of the cortex dominated information transfer and deeper aspects clustering. These differences were largest in frontotemporal and limbic brain regions. fMRI functional connectivity across different cortical depths may contain neurophysiologically relevant information. Multilayer connectomics could provide a methodological framework for studies on how information flows across this hierarchy.

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

Layer-dependent functional magnetic resonance imaging (fMRI) offers a compelling avenue for investigating directed functional connectivity (FC). To construct a comprehensive map of brain-wide directed FC, several technical criteria must be met, including sub-mm spatial resolution, adequate 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 effect, particularly when utilizing blood oxygen level-dependent (BOLD) contrast. In this study, we mitigated this effect by incorporating velocity-nulling (VN) gradients into a GE-BOLD fMRI sequence, opting for a 3T magnetic field strength over 7T. We also integrated several advanced techniques, such as simultaneous multi-slice (SMS) acceleration and NORDIC denoising, to enhance temporal resolution, spatial coverage, and signal sensitivity. Collectively, the VN fMRI method exhibited notable spatial specificity, as evidenced by the identification of double-peak activation patterns within the primary motor cortex (M1) during a finger-tapping task. Additionally, the technique demonstrated BOLD sensitivity in the lateral geniculate nucleus (LGN). Furthermore, our VN fMRI technique displayed superior robustness when compared to conventional fMRI approaches across participants. Our findings of directed FC elucidate several layer-specific functional relationships between different brain regions and align closely with existing literature. Given the widespread availability of 3T scanners, this technical advancement has the potential for significant impact across multiple domains of neuroscience research.

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.

Brain-wide mapping of resting-state networks in mice using high-frame rate functional ultrasound

Functional ultrasound (fUS) imaging is a method for visualizing deep brain activity based on cerebral blood volume changes coupled with neural activity, while functional MRI (fMRI) relies on the blood-oxygenation-level-dependent signal coupled with neural activity. Low-frequency fluctuations (LFF) of fMRI signals during resting-state can be measured by resting-state fMRI (rsfMRI), which allows functional imaging of the whole brain, and the distributions of resting-state network (RSN) can then be estimated from these fluctuations using independent component analysis (ICA). This procedure provides an important method for studying cognitive and psychophysiological diseases affecting specific brain networks. The distributions of RSNs in the brain-wide area has been reported primarily by rsfMRI. RSNs using rsfMRI are generally computed from the time-course of fMRI signals for more than 5 min. However, a recent dynamic functional connectivity study revealed that RSNs are still not perfectly stable even after 10 min. Importantly, fUS has a higher temporal resolution and stronger correlation with neural activity compared with fMRI. Therefore, we hypothesized that fUS applied during the resting-state for a shorter than 5 min would provide similar RSNs compared to fMRI. High temporal resolution rsfUS data were acquired at 10 Hz in awake mice. The quality of the default mode network (DMN), a well-known RSN, was evaluated using signal-noise separation (SNS) applied to different measurement durations of rsfUS. The results showed that the SNS did not change when the measurement duration was increased to more than 210 s. Next, we measured short-duration rsfUS multi-slice measurements in the brain-wide area. The results showed that rsfUS with the short duration succeeded in detecting RSNs distributed in the brain-wide area consistent with RSNs detected by 11.7-T MRI under awake conditions (medial prefrontal cortex and cingulate cortex in the anterior DMN, retrosplenial cortex and visual cortex in the posterior DMN, somatosensory and motor cortexes in the lateral cortical network, thalamus, dorsal hippocampus, and medial cerebellum), confirming the reliability of the RSNs detected by rsfUS. However, bilateral RSNs located in the secondary somatosensory cortex, ventral hippocampus, auditory cortex, and lateral cerebellum extracted from rsfUS were different from the unilateral RSNs extracted from rsfMRI. These findings indicate the potential of rsfUS as a method for analyzing functional brain networks and should encourage future research to elucidate functional brain networks and their relationships with disease model mice.

The Venular Side of Cerebral Amyloid Angiopathy: Proof of Concept of a Neglected Issue

Small vessel diseases (SVD) is an umbrella term including several entities affecting small arteries, arterioles, capillaries, and venules in the brain. One of the most relevant and prevalent SVDs is cerebral amyloid angiopathy (CAA), whose pathological hallmark is the deposition of amyloid fragments in the walls of small cortical and leptomeningeal vessels. CAA frequently coexists with Alzheimer's Disease (AD), and both are associated with cerebrovascular events, cognitive impairment, and dementia. CAA and AD share pathophysiological, histopathological and neuroimaging issues. The venular involvement in both diseases has been neglected, although both animal models and human histopathological studies found a deposition of amyloid beta in cortical venules. This review aimed to summarize the available information about venular involvement in CAA, starting from the biological level with the putative pathomechanisms of cerebral damage, passing through the definition of the peculiar angioarchitecture of the human cortex with the functional organization and consequences of cortical arteriolar and venular occlusion, and ending to the hypothesized links between cortical venular involvement and the main neuroimaging markers of the disease.

Ultra-High Field Imaging of Human Visual Cognition

Functional magnetic resonance imaging (fMRI), the key methodology for mapping the functions of the human brain in a noninvasive manner, is limited by low temporal and spatial resolution. Recent advances in ultra-high field (UHF) fMRI provide a mesoscopic (i.e., submillimeter resolution) tool that allows us to probe laminar and columnar circuits, distinguish bottom-up versus top-down pathways, and map small subcortical areas. We review recent work demonstrating that UHF fMRI provides a robust methodology for imaging the brain across cortical depths and columns that provides insights into the brain's organization and functions at unprecedented spatial resolution, advancing our understanding of the fine-scale computations and interareal communication that support visual cognition.

Physiological modeling of the BOLD signal and implications for effective connectivity: A primer

In this primer, I provide an overview of the physiological processes that contribute to the observed BOLD signal (i.e., the generative biophysical model), including their time course properties within the framework of the physiologically-informed dynamic causal modeling (P-DCM). The BOLD signal is primarily determined by the change in paramagnetic deoxygenated hemoglobin, which results from combination of changes in oxygen metabolism, and cerebral blood flow and volume. Specifically, the physiological origin of the so-called BOLD signal "transients" will be discussed, including the initial overshoot, steady-state activation and the post-stimulus undershoot. I argue that incorrect physiological assumptions in the generative model of the BOLD signal can lead to incorrect inferences pertaining to both local neuronal activity and effective connectivity between brain regions. In addition, I introduce the recent laminar BOLD signal model, which extends P-DCM to cortical depths-resolved BOLD signals, allowing for laminar neuronal activity to be determined using high-resolution fMRI data.

A Novel Intraoperative Mapping Device Detects the Thermodynamic Response Function

Functional activation leads to an increase in local brain temperature via an increase in local perfusion. In the intraoperative setting, these cortical surface temperature fluctuations may be imaged using infrared thermography such that the activated brain areas are inferred. While it is known that temperature increases as a result of activation, a quantitative spatiotemporal description has yet to be achieved. A novel intraoperative infrared thermography device with data collection software was developed to isolate the thermal impulse response function. Device performance was validated using data from six patients undergoing awake craniotomy who participated in motor and sensory mapping tasks during infrared imaging following standard mapping with direct electrical stimulation. Shared spatiotemporal patterns of cortical temperature changes across patients were identified using group principal component analysis. Analysis of component time series revealed a thermal activation peak present across all patients with an onset delay of five seconds and a peak duration of ten seconds. Spatial loadings were converted to a functional map which showed strong correspondence to positive stimulation results for similar tasks. This component demonstrates the presence of a previously unknown impulse response function for functional mapping with infrared thermography.

Improved sensitivity and microvascular weighting of 3T laminar fMRI with GE-BOLD using NORDIC and phase regression

INTRODUCTION

Functional MRI with spatial resolution in the submillimeter domain enables measurements of activation across cortical layers in humans. This is valuable as different types of cortical computations, e.g., feedforward versus feedback related activity, take place in different cortical layers. Laminar fMRI studies have almost exclusively employed 7T scanners to overcome the reduced signal stability associated with small voxels. However, such systems are relatively rare and only a subset of those are clinically approved. In the present study, we examined if the feasibility of laminar fMRI at 3T could be improved by use of NORDIC denoising and phase regression.

METHODS

5 healthy subjects were scanned on a Siemens MAGNETOM Prisma 3T scanner. To assess across-session reliability, each subject was scanned in 3-8 sessions on 3-4 consecutive days. A 3D gradient echo EPI (GE-EPI) sequence was used for BOLD acquisitions (voxel size 0.82 mm isotopic, TR = 2.2 s) using a block design finger tapping paradigm. NORDIC denoising was applied to the magnitude and phase time series to overcome limitations in temporal signal-to-noise ratio (tSNR) and the denoised phase time series were subsequently used to correct for large vein contamination through phase regression.

RESULTS AND CONCLUSION

NORDIC denoising resulted in tSNR values comparable to or higher than commonly observed at 7T. Layer-dependent activation profiles could thus be extracted robustly, within and across sessions, from regions of interest located in the hand knob of the primary motor cortex (M1). Phase regression led to substantially reduced superficial bias in obtained layer profiles, although residual macrovascular contribution remained. We believe the present results support an improved feasibility of laminar fMRI at 3T.

The many layers of BOLD. The effect of hypercapnic and hyperoxic stimuli on macro- and micro-vascular compartments quantified by CVR, M, and CBV across cortical depth

Ultra-high field functional magnetic resonance imaging (fMRI) offers the spatial resolution to measure neuronal activity at the scale of cortical layers. However, cortical depth dependent vascularization differences, such as a higher prevalence of macro-vascular compartments near the pial surface, have a confounding effect on depth-resolved blood-oxygen-level dependent (BOLD) fMRI signals. In the current study, we use hypercapnic and hyperoxic breathing conditions to quantify the influence of all venous vascular and micro-vascular compartments on laminar BOLD fMRI, as measured with gradient-echo (GE) and spin-echo (SE) scan sequences, respectively. We find that all venous vascular and micro-vascular compartments are capable of comparable theoretical maximum signal intensities, as represented by the M-value parameter. However, the capacity for vessel dilation, as reflected by the cerebrovascular reactivity (CVR), is approximately two and a half times larger for all venous vascular compartments combined compared to the micro-vasculature at superficial layers. Finally, there is roughly a 35% difference in estimates of CBV changes between all venous vascular and micro-vascular compartments, although this relative difference was approximately uniform across cortical depth. Thus, our results suggest that fMRI BOLD signal differences across cortical depth are likely caused by differences in dilation properties between macro- and micro-vascular compartments.

Cerebral blood volume sensitive layer-fMRI in the human auditory cortex at 7T: Challenges and capabilities

The development of ultra high field fMRI signal readout strategies and contrasts has led to the possibility of imaging the human brain in vivo and non-invasively at increasingly higher spatial resolutions of cortical layers and columns. One emergent layer-fMRI acquisition method with increasing popularity is the cerebral blood volume sensitive sequence named vascular space occupancy (VASO). This approach has been shown to be mostly sensitive to locally-specific changes of laminar microvasculature, without unwanted biases of trans-laminar draining veins. Until now, however, VASO has not been applied in the technically challenging cortical area of the auditory cortex. Here, we describe the main challenges we encountered when developing a VASO protocol for auditory neuroscientific applications and the solutions we have adopted. With the resulting protocol, we present preliminary results of laminar responses to sounds and as a proof of concept for future investigations, we map the topographic representation of frequency preference (tonotopy) in the auditory cortex.

Cortical depth profiles of auditory and visual 7 T functional MRI responses in human superior temporal areas

Invasive neurophysiological studies in nonhuman primates have shown different laminar activation profiles to auditory vs. visual stimuli in auditory cortices and adjacent polymodal areas. Means to examine the underlying feedforward vs. feedback type influences noninvasively have been limited in humans. Here, using 1-mm isotropic resolution 3D echo-planar imaging at 7 T, we studied the intracortical depth profiles of functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) signals to brief auditory (noise bursts) and visual (checkerboard) stimuli. BOLD percent-signal-changes were estimated at 11 equally spaced intracortical depths, within regions-of-interest encompassing auditory (Heschl's gyrus, Heschl's sulcus, planum temporale, and posterior superior temporal gyrus) and polymodal (middle and posterior superior temporal sulcus) areas. Effects of differing BOLD signal strengths for auditory and visual stimuli were controlled via normalization and statistical modeling. The BOLD depth profile shapes, modeled with quadratic regression, were significantly different for auditory vs. visual stimuli in auditory cortices, but not in polymodal areas. The different depth profiles could reflect sensory-specific feedforward versus cross-sensory feedback influences, previously shown in laminar recordings in nonhuman primates. The results suggest that intracortical BOLD profiles can help distinguish between feedforward and feedback type influences in the human brain. Further experimental studies are still needed to clarify how underlying signal strength influences BOLD depth profiles under different stimulus conditions.

Layer-specific correlates of detected and undetected auditory targets during attention

In everyday life, the processing of acoustic information allows us to react to subtle changes in the auditory scene. Yet even when closely attending to sounds in the context of a task, we occasionally miss task-relevant features. The neural computations that underlie our ability to detect behavioral relevant sound changes are thought to be grounded in both feedforward and feedback processes within the auditory hierarchy. Here, we assessed the role of feedforward and feedback contributions in primary and non-primary auditory areas during behavioral detection of target sounds using submillimeter spatial resolution functional magnetic resonance imaging (fMRI) at high-fields (7 T) in humans. We demonstrate that the successful detection of subtle temporal shifts in target sounds leads to a selective increase of activation in superficial layers of primary auditory cortex (PAC). These results indicate that feedback signals reaching as far back as PAC may be relevant to the detection of targets in the auditory scene.

Improved Selectivity in 7 T Digit Mapping Using VASO-CBV

Functional magnetic resonance imaging (fMRI) at Ultra-high field (UHF, ≥ 7 T) benefits from significant gains in the BOLD contrast-to-noise ratio (CNR) and temporal signal-to-noise ratio (tSNR) compared to conventional field strengths (3 T). Although these improvements enabled researchers to study the human brain to unprecedented spatial resolution, the blood pooling effect reduces the spatial specificity of the widely-used gradient-echo BOLD acquisitions. In this context, vascular space occupancy (VASO-CBV) imaging may be advantageous since it is proposed to have a higher spatial specificity than BOLD. We hypothesized that the assumed higher specificity of VASO-CBV imaging would translate to reduced overlap in fine-scale digit representation maps compared to BOLD-based digit maps. We used sub-millimeter resolution VASO fMRI at 7 T to map VASO-CBV and BOLD responses simultaneously in the motor and somatosensory cortices during individual finger movement tasks. We assessed the cortical overlap in different ways, first by calculating similarity coefficient metrics (DICE and Jaccard) and second by calculating selectivity measures. In addition, we demonstrate a consistent topographical organization of the targeted digit representations (thumb-index-little finger) in the motor areas. We show that the VASO-CBV responses yielded less overlap between the digit clusters than BOLD, and other selectivity measures were higher for VASO-CBV too. In summary, these results were consistent across metrics and participants, confirming the higher spatial specificity of VASO-CBV compared to BOLD.

Improved laminar specificity and sensitivity by combining SE and GE BOLD signals

The most widely used gradient-echo (GE) blood oxygenation level-dependent (BOLD) contrast has high sensitivity, but low specificity due to draining vein contributions, while spin-echo (SE) BOLD approach at ultra-high magnetic fields is highly specific to neural active sites but has lower sensitivity. To obtain high specificity and sensitivity, we propose to utilize a vessel-size-sensitive filter to the GE-BOLD signal, which suppresses macrovascular contributions and to combine selectively retained microvascular GE-BOLD signals with the SE-BOLD signals. To investigate our proposed idea, fMRI with 0.8 mm isotropic resolution was performed on the primary motor and sensory cortices in humans at 7 T by implementing spin- and gradient-echo (SAGE) echo planar imaging (EPI) acquisition. Microvascular-passed sigmoidal filters were designed based upon the vessel-size-sensitive ΔR₂*/ΔR₂ value for retaining GE-BOLD signals originating from venous vessels with ≤ 45 μm and ≤ 65 μm diameter. Unlike GE-BOLD fMRI, the laminar profile of SAGE-BOLD fMRI with the vessel-size-sensitive filter peaked at ∼ 1.0 mm from the surface of the primary motor and sensory cortices, demonstrating an improvement of laminar specificity over GE-BOLD fMRI. Also, the functional sensitivity of SAGE BOLD at middle layers (0.75-1.5 mm) was improved by ∼ 80% to ∼100% when compared with SE BOLD. In summary, we showed that combined GE- and SE-BOLD fMRI with the vessel-size-sensitive filter indeed yielded improved laminar specificity and sensitivity and is therefore an excellent tool for high spatial resolution ultra-high filed (UHF)-fMRI studies for resolving mesoscopic functional units.

Mesoscopic in vivo human T2* dataset acquired using quantitative MRI at 7 Tesla

Mesoscopic (0.1-0.5 mm) interrogation of the living human brain is critical for advancing neuroscience and bridging the resolution gap with animal models. Despite the variety of MRI contrasts measured in recent years at the mesoscopic scale, in vivo quantitative imaging of T₂^* has not been performed. Here we provide a dataset containing empirical T₂^* measurements acquired at 0.35 × 0.35 × 0.35 mm³ voxel resolution using 7 Tesla MRI. To demonstrate unique features and high quality of this dataset, we generate flat map visualizations that reveal fine-scale cortical substructures such as layers and vessels, and we report quantitative depth-dependent T₂^* (as well as R₂^*) values in primary visual cortex and auditory cortex that are highly consistent across subjects. This dataset is freely available at https://doi.org/10.17605/OSF.IO/N5BJ7, and may prove useful for anatomical investigations of the human brain, as well as for improving our understanding of the basis of the T₂^*-weighted (f)MRI signal.

Characterization of the blood oxygen level dependent hemodynamic response function in human subcortical regions with high spatiotemporal resolution

Subcortical brain regions are absolutely essential for normal human function. These phylogenetically early brain regions play critical roles in human behaviors such as the orientation of attention, arousal, and the modulation of sensory signals to cerebral cortex. Despite the critical health importance of subcortical brain regions, there has been a dearth of research on their neurovascular responses. Blood oxygen level dependent (BOLD) functional MRI (fMRI) experiments can help fill this gap in our understanding. The BOLD hemodynamic response function (HRF) evoked by brief (<4 s) neural activation is crucial for the interpretation of fMRI results because linear analysis between neural activity and the BOLD response relies on the HRF. Moreover, the HRF is a consequence of underlying local blood flow and oxygen metabolism, so characterization of the HRF enables understanding of neurovascular and neurometabolic coupling. We measured the subcortical HRF at 9.4T and 3T with high spatiotemporal resolution using protocols that enabled reliable delineation of HRFs in individual subjects. These results were compared with the HRF in visual cortex. The HRF was faster in subcortical regions than cortical regions at both field strengths. There was no significant undershoot in subcortical areas while there was a significant post-stimulus undershoot that was tightly coupled with its peak amplitude in cortex. The different BOLD temporal dynamics indicate different vascular dynamics and neurometabolic responses between cortex and subcortical nuclei.

Modelling the depth-dependent VASO and BOLD responses in human primary visual cortex

Functional magnetic resonance imaging (fMRI) using a blood-oxygenation-level-dependent (BOLD) contrast is a common method for studying human brain function noninvasively. Gradient-echo (GRE) BOLD is highly sensitive to the blood oxygenation change in blood vessels; however, the spatial signal specificity can be degraded due to signal leakage from activated lower layers to superficial layers in depth-dependent (also called laminar or layer-specific) fMRI. Alternatively, physiological variables such as cerebral blood volume using the VAscular-Space-Occupancy (VASO) contrast have shown higher spatial specificity compared to BOLD. To better understand the physiological mechanisms such as blood volume and oxygenation changes and to interpret the measured depth-dependent responses, models are needed which reflect vascular properties at this scale. For this purpose, we extended and modified the "cortical vascular model" previously developed to predict layer-specific BOLD signal changes in human primary visual cortex to also predict a layer-specific VASO response. To evaluate the model, we compared the predictions with experimental results of simultaneous VASO and BOLD measurements in a group of healthy participants. Fitting the model to our experimental data provided an estimate of CBV change in different vascular compartments upon neural activity. We found that stimulus-evoked CBV change mainly occurs in small arterioles, capillaries, and intracortical arteries and that the contribution from venules and ICVs is smaller. Our results confirm that VASO is less susceptible to large vessel effects compared to BOLD, as blood volume changes in intracortical arteries did not substantially affect the resulting depth-dependent VASO profiles, whereas depth-dependent BOLD profiles showed a bias towards signal contributions from intracortical veins.

Functional Parcellation of Human Brain Using Localized Topo-Connectivity Mapping

The analysis of connectivity between parcellated regions of cortex provides insights into the functional architecture of the brain at a systems level. However, the derivation of functional structures from voxel-wise analyses at finer scales remains a challenge. We propose a novel method, called localized topo-connectivity mapping with singular-value-decomposition-informed filtering (or filtered LTM), to identify and characterize voxel-wise functional structures in the human brain from resting-state fMRI data. Here we describe its mathematical formulation and provide a proof-of-concept using simulated data that allow an intuitive interpretation of the results of filtered LTM. The algorithm has also been applied to 7T fMRI data acquired as part of the Human Connectome Project to generate group-average LTM images. Generally, most of the functional structures revealed by LTM images agree in the boundaries with anatomical structures identified by T1-weighted images and fractional anisotropy maps derived from diffusion MRI. In addition, the LTM images also reveal subtle functional variations that are not apparent in the anatomical structures. To assess the performance of LTM images, the subcortical region and occipital white matter were separately parcellated. Statistical tests were performed to demonstrate that the synchronies of fMRI signals in LTM-derived functional parcels are significantly larger than those with geometric perturbations. Overall, the filtered LTM approach can serve as a tool to investigate the functional organization of the brain at the scale of individual voxels as measured in fMRI.

Detection of functional activity in brain white matter using fiber architecture informed synchrony mapping

A general linear model is widely used for analyzing fMRI data, in which the blood oxygenation-level dependent (BOLD) signals in gray matter (GM) evoked in response to neural stimulation are modeled by convolving the time course of the expected neural activity with a canonical hemodynamic response function (HRF) obtained a priori. The maps of brain activity produced reflect the magnitude of local BOLD responses. However, detecting BOLD signals in white matter (WM) is more challenging as the BOLD signals are weaker and the HRF is different, and may vary more across the brain. Here we propose a model-free approach to detect changes in BOLD signals in WM by measuring task-evoked increases of BOLD signal synchrony in WM fibers. The proposed approach relies on a simple assumption that, in response to a functional task, BOLD signals in relevant fibers are modulated by stimulus-evoked neural activity and thereby show greater synchrony than when measured in a resting state, even if their magnitudes do not change substantially. This approach is implemented in two technical stages. First, for each voxel a fiber-architecture-informed spatial window is created with orientation distribution functions constructed from diffusion imaging data. This provides the basis for defining neighborhoods in WM that share similar local fiber architectures. Second, a modified principal component analysis (PCA) is used to estimate the synchrony of BOLD signals in each spatial window. The proposed approach is validated using a 3T fMRI dataset from the Human Connectome Project (HCP) at a group level. The results demonstrate that neural activity can be reliably detected as increases in fMRI signal synchrony within WM fibers that are engaged in a task with high sensitivities and reproducibility.

Temporal stability of the hemodynamic response function across the majority of human cerebral cortex

The hemodynamic response function (HRF) measured with functional magnetic resonance imaging is generated by vascular and metabolic responses evoked by brief (<4 s) stimuli. It is known that the human HRF varies across cortex, between subjects, with stimulus paradigms, and even between different measurements in the same cortical location. However, our results demonstrate that strong HRFs are remarkably repeatable across sessions separated by time intervals up to 3 months. In this study, a multisensory stimulus was used to activate and measure the HRF across the majority of cortex (>70%, with lesser reliability observed in some areas of prefrontal cortex). HRFs were measured with high spatial resolution (2‐mm voxels) in central gray matter to minimize variations caused by partial‐volume effects. HRF amplitudes and temporal dynamics were highly repeatable across four sessions in 20 subjects. Positive and negative HRFs were consistently observed across sessions and subjects. Negative HRFs were generally weaker and, thus, more variable than positive HRFs. Statistical measurements showed that across‐session variability is highly correlated to the variability across events within a session; these measurements also indicated a normal distribution of variability across cortex. The overall repeatability of the HRFs over long time scales generally supports the long‐term use of event‐related functional magnetic resonance imaging protocols.

The Spatiotemporal Dynamics of Cerebral Autoregulation in Functional Magnetic Resonance Imaging

The thigh-cuff release (TCR) maneuver is a physiological challenge that is widely used to assess dynamic cerebral autoregulation (dCA). It is often applied in conjunction with Transcranial Doppler ultrasound (TCD), which provides temporal information of the global flow response in the brain. This established method can only yield very limited insights into the regional variability of dCA, whereas functional MRI (fMRI) has the ability to reveal the spatial distribution of flow responses in the brain with high spatial resolution. The aim of this study was to use whole-brain blood-oxygenation-level-dependent (BOLD) fMRI to characterize the spatiotemporal dynamics of the flow response to the TCR challenge, and thus pave the way toward mapping dCA in the brain. We used a data driven approach to derive a novel basis set that was then used to provide a voxel-wise estimate of the TCR associated haemodynamic response function (HRF TCR ). We found that the HRF TCR evolves with a specific spatiotemporal pattern, with gray and white matter showing an asynchronous response, which likely reflects the anatomical structure of cerebral blood supply. Thus, we propose that TCR challenge fMRI is a promising method for mapping spatial variability in dCA, which will likely prove to be clinically advantageous.

Cortical layer-specific differences in stimulus selectivity revealed with high-field fMRI and single-vessel resolution optical imaging of the primary visual cortex

The mammalian neocortex exhibits a stereotypical laminar organization, with feedforward inputs arriving primarily into layer 4, local computations shaping response selectivity in layers 2/3, and outputs to other brain areas emanating via layers 2/3, 5 and 6. It cannot be assumed a priori that these signatures of laminar differences in neuronal circuitry are reflected in hemodynamic signals that form the basis of functional magnetic resonance imaging (fMRI). Indeed, optical imaging of single-vessel functional responses has highlighted the potential limits of using vascular signals as surrogates for mapping the selectivity of neural responses. Therefore, before fMRI can be employed as an effective tool for studying critical aspects of laminar processing, validation with single-vessel resolution is needed. The primary visual cortex (V1) in cats, with its precise neuronal functional micro-architecture, offers an ideal model system to examine laminar differences in stimulus selectivity across imaging modalities. Here we used cerebral blood volume weighted (wCBV) fMRI to examine if layer-specific orientation-selective responses could be detected in cat V1. We found orientation preference maps organized tangential to the cortical surface that typically extended across depth in a columnar fashion. We then examined arterial dilation and blood velocity responses to identical visual stimuli by using two- and three- photon optical imaging at single-vessel resolution-which provides a measure of the hemodynamic signals with the highest spatial resolution. Both fMRI and optical imaging revealed a consistent laminar response pattern in which orientation selectivity in cortical layer 4 was significantly lower compared to layer 2/3. This systematic change in selectivity across cortical layers has a clear underpinning in neural circuitry, particularly when comparing layer 4 to other cortical layers.

Hemodynamic and metabolic correspondence of resting-state voxel-based physiological metrics in healthy adults

Voxel-based physiological (VBP) variables derived from blood oxygen level dependent (BOLD) fMRI time-course variations include: amplitude of low frequency fluctuations (ALFF), fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity (ReHo). Although these BOLD-derived variables can detect between-group (e.g. disease vs control) spatial pattern differences, physiological interpretations are not well established. The primary objective of this study was to quantify spatial correspondences between BOLD VBP variables and PET measurements of cerebral metabolic rate and hemodynamics, being well-validated physiological standards. To this end, quantitative, whole-brain PET images of metabolic rate of glucose (MRGlu; 18FDG) and oxygen (MRO2; 15OO), blood flow (BF; H215O) and blood volume (BV; C15O) were obtained in 16 healthy controls. In the same subjects, BOLD time-courses were obtained for computation of ALFF, fALFF and ReHo images. PET variables were compared pair-wise with BOLD variables. In group-averaged, across-region analyses, ALFF corresponded significantly only with BV (R = 0.64; p < 0.0001). fALFF corresponded most strongly with MRGlu (R = 0.79; p < 0.0001), but also significantly (p < 0.0001) with MRO2 (R = 0.68), BF (R = 0.68) and BV (R=0.68). ReHo performed similarly to fALFF, with significant strong correspondence (p < 0.0001) with MRGlu (R = 0.78), MRO2 (R = 0.54), and, but less strongly with BF (R = 0.50) and BV (R=0.50). Mutual information analyses further clarified these physiological interpretations. When conditioned by BV, ALFF retained no significant MRGlu, MRO2 or BF information. When conditioned by MRGlu, fALFF and ReHo retained no significant MRO2, BF or BV information. Of concern, however, the strength of PET-BOLD correspondences varied markedly by brain region, which calls for future investigation on physiological interpretations at a regional and per-subject basis.

Medullary vein architecture modulates the white matter BOLD cerebrovascular reactivity signal response to CO2: Observations from high-resolution T2* weighted imaging at 7T

Brain stress testing using blood oxygenation level-dependent (BOLD) MRI to evaluate changes in cerebrovascular reactivity (CVR) is of growing interest for evaluating white matter integrity. However, even under healthy conditions, the white matter BOLD-CVR response differs notably from that observed in the gray matter. In addition to actual arterial vascular control, the venous draining topology may influence the WM-CVR response leading to signal delays and dispersions. These types of alterations in hemodynamic parameters are sometimes linked with pathology, but may also arise from differences in normal venous architecture. In this work, high-resolution T2*weighted anatomical images combined with BOLD imaging during a hypercapnic breathing protocol were acquired using a 7 tesla MRI system. Hemodynamic parameters including base CVR, hemodynamic lag, lag-corrected CVR, response onset and signal dispersion, and finally ΔCVR (corrected CVR minus base CVR) were calculated in 8 subjects. Parameter maps were spatially normalized and correlated against an MNI-registered white matter medullary vein atlas. Moderate correlations (Pearson's rho) were observed between medullary vessel frequency (MVF) and ΔCVR (0.52; 0.58 for total WM), MVF and hemodynamic lag (0.42; 0.54 for total WM), MVF and signal dispersion (0.44; 0.53 for total WM), and finally MVF and signal onset (0.43; 0.52 for total WM). Results indicate that, when assessed in the context of the WM venous architecture, changes in the response shape may only be partially reflective of the actual vascular reactivity response occurring further upstream by control vessels. This finding may have implications when attributing diseases mechanisms and/or progression to presumed impaired WM BOLD-CVR.

Imaging faster neural dynamics with fast fMRI: A need for updated models of the hemodynamic response

Fast fMRI enables the detection of neural dynamics over timescales of hundreds of milliseconds, suggesting it may provide a new avenue for studying subsecond neural processes in the human brain. The magnitudes of these fast fMRI dynamics are far greater than predicted by canonical models of the hemodynamic response. Several studies have established nonlinear properties of the hemodynamic response that have significant implications for fast fMRI. We first review nonlinear properties of the hemodynamic response function that may underlie fast fMRI signals. We then illustrate the breakdown of canonical hemodynamic response models in the context of fast neural dynamics. We will then argue that the canonical hemodynamic response function is not likely to reflect the BOLD response to neuronal activity driven by sparse or naturalistic stimuli or perhaps to spontaneous neuronal fluctuations in the resting state. These properties suggest that fast fMRI is capable of tracking surprisingly fast neuronal dynamics, and we discuss the neuroscientific questions that could be addressed using this approach.

Quantification of cerebral blood volume changes caused by visual stimulation at 3 T using DANTE-prepared dual-echo EPI

PURPOSE

We investigate the influence of moving blood-attenuation effects when using "delay alternating with nutation for tailored excitation" (DANTE) pulses in conjunction with blood oxygen level dependent (BOLD) of functional MRI (fMRI) at 3 T. Based on the effects of including DANTE pulses, we propose quantification of cerebral blood volume (CBV) changes following functional stimulation.

METHODS

Eighteen volunteers in total underwent fMRI scans at 3 T. Seven volunteers were scanned to investigate the effects of DANTE pulses on the fMRI signal. CBV changes in response to visual stimulation were quantified in 11 volunteers using a DANTE-prepared dual-echo EPI sequence.

RESULTS

The inflow effects from flowing blood in arteries and draining vein effects from flowing blood in large veins can be suppressed by use of a DANTE preparation module. Using DANTE-prepared dual-echo EPI, we quantitatively measured intravascular-weighted microvascular CBV changes of 25.4%, 29.8%, and 32.6% evoked by 1, 5, and 10 Hz visual stimulation, respectively. The extravascular fraction (∆S/S)_extra at TE = 30 ms in total BOLD signal was determined to be 64.8 ± 3.4%, which is in line with previous extravascular component estimation at 3 T. Results show that the microvascular CBV changes are linearly dependent on total BOLD changes at TE = 30 ms with a slope of 0.113, and this relation is independent of stimulation frequency and subject.

CONCLUSION

The DANTE preparation pulses can be incorporated into a standard EPI fMRI sequence for the purpose of minimizing inflow effects and reducing draining veins effects in large vessels. Additionally, the DANTE-prepared dual-echo EPI sequence is a promising fast imaging tool for quantification of intravascular-weighted CBV change in the microvascular space at 3 T.

Point-spread function of the BOLD response across columns and cortical depth in human extra-striate cortex

Columns and layers are fundamental organizational units of the brain. Well known examples of cortical columns are the ocular dominance columns (ODCs) in primary visual cortex and the column-like stripe-based arrangement in the second visual area V2. The spatial scale of columns and layers is beyond the reach of conventional neuroimaging, but the advent of high field magnetic resonance imaging (MRI) scanners (UHF, 7 Tesla and above) has opened the possibility to acquire data at this spatial scale, in-vivo and non-invasively in humans. The most prominent non-invasive technique to measure brain function is blood oxygen level dependent (BOLD) fMRI, measuring brain activity indirectly, via changes in hemodynamics. A key determinant of the ability of high-resolution BOLD fMRI to accurately resolve columns and layers is the point-spread function (PSF) of the BOLD response in relation to the spatial extent of neuronal activity. In this study we take advantage of the stripe-based arrangement present in visual area V2, coupled with sub-millimetre anatomical and gradient-echo BOLD (GE BOLD) acquisition at 7 T to obtain PSF estimates and along cortical depth in human participants. Results show that the BOLD PSF is maximal in the superficial part of the cortex (1.78 mm), and it decreases with increasing cortical depth (0.83 mm close to white matter).

Size of the spatial correlation between ECoG and fMRI activity

Electrocorticography (ECoG) is typically employed to accurately identify the seizure focus as well as the location of brain functions to be spared during surgical resection in participants with drug-resistant epilepsy. Increasingly, this technique has become a powerful tool to map cognitive functions onto brain regions. Cortical mapping is more commonly investigated with functional MRI (fMRI), which measures blood-oxygen level dependent (BOLD) changes induced by neuronal activity. The multimodal integration between typical 3T fMRI activity maps and ECoG measurements can provide unique insight into the spatiotemporal aspects of cognition. However, the optimal integration of fMRI and ECoG requires fundamental insight into the spatial smoothness of the BOLD signal under each electrode. Here we use ECoG as ground truth for the extent of activity, as each electrode is thought to record from the cortical tissue directly underneath the contact, to estimate the spatial smoothness of the associated BOLD response at 3T fMRI. We compared the high-frequency broadband (HFB) activity recorded with ECoG while participants performed a motor task. Activity maps were obtained with fMRI at 3T for the same task in the same participant prior to surgery. We then correlated HFB power with the fMRI BOLD signal change in the area around each electrode. This latter measure was quantified by applying a 3D Gaussian kernel of varying width (sigma between 1 mm and 20 mm) to the fMRI maps including only gray-matter. We found that the correlation between HFB and BOLD activity increased sharply up to the point when the kernel width was set to 4 mm, which we defined as the kernel width of maximal spatial specificity. After this point, as the kernel width increased, the highest level of explained variance was reached at a kernel width of 9 mm for most participants. Intriguingly, maximal specificity was also limited to 4 mm for low-frequency bands, such as alpha and beta, but the kernel width with the highest explained variance was less spatially limited than the HFB. In summary, spatial specificity is limited to a kernel width of 4 mm but explained variance keeps on increasing as you average over more and more voxels containing the relatively noisy BOLD signal. Future multimodal studies should choose the kernel width based on their research goal. For maximal spatial specificity, ECoG electrodes are best compared to 3T fMRI with a kernel width of 4 mm. When optimizing the correlation between modalities, highest explained variance can be obtained at larger kernel widths of 9 mm, at the expense of spatial specificity. Finally, we release the complete pipeline so that researchers can estimate the most appropriate kernel width from their multimodal datasets.

Reliability of task-specific neuronal activation assessed with functional PET, ASL and BOLD imaging

Mapping the neuronal response during cognitive processing is of crucial importance to gain new insights into human brain function. BOLD imaging and ASL are established MRI methods in this endeavor. Recently, the novel approach of functional PET (fPET) was introduced, enabling absolute quantification of glucose metabolism at rest and during task execution in a single measurement. Here, we report test-retest reliability of fPET in direct comparison to BOLD imaging and ASL. Twenty healthy subjects underwent two PET/MRI measurements, providing estimates of glucose metabolism, cerebral blood flow (CBF) and blood oxygenation. A cognitive task was employed with different levels of difficulty requiring visual-motor coordination. Task-specific neuronal activation was robustly detected with all three imaging approaches. The highest reliability was obtained for glucose metabolism at rest. Although this dropped during task performance it was still comparable to that of CBF. In contrast, BOLD imaging yielded high performance only for qualitative spatial overlap of task effects but not for quantitative comparison. Hence, the combined assessment of fPET and ASL offers reliable and simultaneous absolute quantification of glucose metabolism and CBF at rest and task.

Contribution of animal models toward understanding resting state functional connectivity

Functional connectivity, which reflects the spatial and temporal organization of intrinsic activity throughout the brain, is one of the most studied measures in human neuroimaging research. The noninvasive acquisition of resting state functional magnetic resonance imaging (rs-fMRI) allows the characterization of features designated as functional networks, functional connectivity gradients, and time-varying activity patterns that provide insight into the intrinsic functional organization of the brain and potential alterations related to brain dysfunction. Functional connectivity, hence, captures dimensions of the brain's activity that have enormous potential for both clinical and preclinical research. However, the mechanisms underlying functional connectivity have yet to be fully characterized, hindering interpretation of rs-fMRI studies. As in other branches of neuroscience, the identification of the neurophysiological processes that contribute to functional connectivity largely depends on research conducted on laboratory animals, which provide a platform where specific, multi-dimensional investigations that involve invasive measurements can be carried out. These highly controlled experiments facilitate the interpretation of the temporal correlations observed across the brain. Indeed, information obtained from animal experimentation to date is the basis for our current understanding of the underlying basis for functional brain connectivity. This review presents a compendium of some of the most critical advances in the field based on the efforts made by the animal neuroimaging community.

Advances in resting state fMRI acquisitions for functional connectomics

Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously in different brain regions, without the subject performing an explicit task. The low-frequency oscillations of the rs-fMRI signal demonstrate an intrinsic spatiotemporal organization in the brain (brain networks) that may relate to the underlying neural activity. In this review article, we briefly describe the current acquisition techniques for rs-fMRI data, from the most common approaches for resting state acquisition strategies, to more recent investigations with dedicated hardware and ultra-high fields. Specific sequences that allow very fast acquisitions, or multiple echoes, are discussed next. We then consider how acquisition methods weighted towards specific parts of the BOLD signal, like the Cerebral Blood Flow (CBF) or Volume (CBV), can provide more spatially specific network information. These approaches are being developed alongside the commonly used BOLD-weighted acquisitions. Finally, specific applications of rs-fMRI to challenging regions such as the laminae in the neocortex, and the networks within the large areas of subcortical white matter regions are discussed. We finish the review with recommendations for acquisition strategies for a range of typical applications of resting state fMRI.

Origins of 1/f-like tissue oxygenation fluctuations in the murine cortex

The concentration of oxygen in the brain spontaneously fluctuates, and the distribution of power in these fluctuations has a 1/f-like spectra, where the power present at low frequencies of the power spectrum is orders of magnitude higher than at higher frequencies. Though these oscillations have been interpreted as being driven by neural activity, the origin of these 1/f-like oscillations is not well understood. Here, to gain insight of the origin of the 1/f-like oxygen fluctuations, we investigated the dynamics of tissue oxygenation and neural activity in awake behaving mice. We found that oxygen signal recorded from the cortex of mice had 1/f-like spectra. However, band-limited power in the local field potential did not show corresponding 1/f-like fluctuations. When local neural activity was suppressed, the 1/f-like fluctuations in oxygen concentration persisted. Two-photon measurements of erythrocyte spacing fluctuations and mathematical modeling show that stochastic fluctuations in erythrocyte flow could underlie 1/f-like dynamics in oxygenation. These results suggest that the discrete nature of erythrocytes and their irregular flow, rather than fluctuations in neural activity, could drive 1/f-like fluctuations in tissue oxygenation.

Validating layer-specific VASO across species

Cerebral blood volume (CBV) has been shown to be a robust and important physiological parameter for quantitative interpretation of functional (f)MRI, capable of delivering highly localized mapping of neural activity. Indeed, with recent advances in ultra-high-field (≥7T) MRI hardware and associated sequence libraries, it has become possible to capture non-invasive CBV weighted fMRI signals across cortical layers. One of the most widely used approaches to achieve this (in humans) is through vascular-space-occupancy (VASO) fMRI. Unfortunately, the exact contrast mechanisms of layer-dependent VASO fMRI have not been validated for human fMRI and thus interpretation of such data is confounded. Here we validate the signal source of layer-dependent SS-SI VASO fMRI using multi-modal imaging in a rat model in response to neuronal activation (somatosensory cortex) and respiratory challenge (hypercapnia). In particular VASO derived CBV measures are directly compared to concurrent measures of total haemoglobin changes from high resolution intrinsic optical imaging spectroscopy (OIS). Quantified cortical layer profiling is demonstrated to be in agreement between VASO and contrast enhanced fMRI (using monocrystalline iron oxide nanoparticles, MION). Responses show high spatial localisation to layers of cortical processing independent of confounding large draining veins which can hamper BOLD fMRI studies, (depending on slice positioning). Thus, a cross species comparison is enabled using VASO as a common measure. We find increased VASO based CBV reactivity (3.1 ± 1.2 fold increase) in humans compared to rats. Together, our findings confirm that the VASO contrast is indeed a reliable estimate of layer-specific CBV changes. This validation study increases the neuronal interpretability of human layer-dependent VASO fMRI as an appropriate method in neuroscience application studies, in which the presence of large draining intracortical and pial veins limits neuroscientific inference with BOLD fMRI.

Laminar fMRI using T2-prepared multi-echo FLASH

Functional magnetic resonance imaging (fMRI) using blood oxygenation level dependent (BOLD) contrast at a sub-millimeter scale is a promising technique to probe neural activity at the level of cortical layers. While gradient echo (GRE) BOLD sequences exhibit the highest sensitivity, their signal is confounded by unspecific extravascular (EV) and intravascular (IV) effects of large intracortical ascending veins and pial veins leading to a downstream blurring effect of local signal changes. In contrast, spin echo (SE) fMRI promises higher specificity towards signal changes near the microvascular compartment. However, the T₂-weighted signal is typically sampled with a gradient echo readout imposing additional T₂'-weighting. In this work, we used a T₂-prepared (T₂-prep) sequence with short GRE readouts to investigate its capability to acquire laminar fMRI data during a visual task in humans at 7 T. By varying the T₂-prep echo time (TE_prep) and acquiring multiple gradient echoes (TE_GRE) per excitation, we studied the specificity of the sequence and the influence of possible confounding contributions to the shape of laminar fMRI profiles. By fitting and extrapolating the multi-echo GRE data to a TE_GRE = 0 ms condition, we show for the first time laminar profiles free of T₂'-pollution, confined to gray matter. This finding is independent of TE_prep, except for the shortest one (31 ms) where hints of a remaining intravascular component can be seen. For TE_GRE > 0 ms a prominent peak at the pial surface is observed that increases with longer TE_GRE and dominates the shape of the profiles independent of the amount of T₂-weighting. Simulations show that the peak at the pial surface is a result of static EV dephasing around pial vessels in CSF visible in GM due to partial voluming. Additionally, another, weaker, static dephasing effect is observed throughout all layers of the cortex, which is particularly obvious in the data with shortest T₂-prep echo time. Our simulations show that this cannot be explained by intravascular dephasing but that it is likely caused by extravascular effects of the intracortical and pial veins. We conclude that even for TE_GRE as short as 2.3 ms, the T₂'-weighting added to the T₂-weighting is enough to dramatically affect the laminar specificity of the BOLD signal change. However, the bulk of this corruption stems from CSF partial volume effects which can in principle be addressed by increasing the spatial resolution of the acquisition.

Determining laminar neuronal activity from BOLD fMRI using a generative model

Laminar fMRI using the BOLD contrast enables the non-invasive investigation of mesoscopic functional circuits in the human brain. However, the laminar neuronal activity is spatiotemporally biased in the observed cortical depth profiles of the BOLD signal. In this study, we propose a generative fMRI signal model, comprehensively covering the relationship between cortical depth-dependent changes in excitatory and inhibitory neuronal activity with the sampling of the BOLD signal with finite voxels. The generative model allowed us to investigate pertinent questions regarding the accuracy of the laminar BOLD signal relative to the neuronal activity, and we found that: a) condition differences in laminar BOLD signals may be more reflective of neuronal activity than single condition BOLD signal depth profiles; b) angular dependence of the BOLD signal induces significant signal variability, which can mask underlying activity profiles; c) even if only three neuronal depths are of interest, more BOLD signal depths should be considered in the analysis. In addition, we recommend that the laminar BOLD data should be displayed using the centroid method to appreciate its spatial distribution in the original resolution. Finally, we showed that Bayesian model inversion of the generative model can improve sensitivity and specificity of assessing depth-dependent neuronal changes both for steady-state and dynamically.

Sub-millimetre resolution laminar fMRI using Arterial Spin Labelling in humans at 7 T

Laminar fMRI at ultra-high magnetic field strength is typically carried out using the Blood Oxygenation Level-Dependent (BOLD) contrast. Despite its unrivalled sensitivity to detecting activation, the BOLD contrast is limited in its spatial specificity due to signals stemming from intra-cortical ascending and pial veins. Alternatively, regional changes in perfusion (i.e., cerebral blood flow through tissue) are colocalised to neuronal activation, which can be non-invasively measured using Arterial Spin Labelling (ASL) MRI. In addition, ASL provides a quantitative marker of neuronal activation in terms of perfusion signal, which is simultaneously acquired along with the BOLD signal. However, ASL for laminar imaging is challenging due to the lower SNR of the perfusion signal and higher RF power deposition i.e., specific absorption rate (SAR) of ASL sequences. In the present study, we present for the first time in humans, isotropic sub-millimetre spatial resolution functional perfusion images using Flow-sensitive Alternating Inversion Recovery (FAIR) ASL with a 3D-EPI readout at 7 T. We show that robust statistical activation maps can be obtained with perfusion-weighting in a single session. We observed the characteristic BOLD amplitude increase towards the superficial laminae, and, in apparent discrepancy, the relative perfusion profile shows a decrease of the amplitude and the absolute perfusion profile a much smaller increase towards the cortical surface. Considering the draining vein effect on the BOLD signal using model-based spatial “convolution”, we show that the empirically measured perfusion and BOLD profiles are, in fact, consistent with each other. This study demonstrates that laminar perfusion fMRI in humans is feasible at 7 T and that caution must be exercised when interpreting BOLD signal laminar profiles as direct representation of the cortical distribution of neuronal activity.

Early fMRI responses to somatosensory and optogenetic stimulation reflect neural information flow

fMRI has revolutionized how neuroscientists investigate human brain functions and networks. To further advance understanding of brain functions, identifying the direction of information flow, such as thalamocortical versus corticothalamic projections, is critical. Because the early hemodynamic response at microvessels near active neurons can be detected by ultrahigh field fMRI, we propose using the onset times of fMRI responses to discern the information flow. This approach was confirmed by observing the ultrahigh spatiotemporal resolution BOLD fMRI responses to bottom-up somatosensory stimulation and top-down optogenetic stimulation of the primary motor cortex in anesthetized mice. Because ultrahigh field MRI is increasingly available, ultrahigh spatiotemporal fMRI will significantly facilitate the investigation of functional circuits in humans.

Blood oxygenation level–dependent (BOLD) functional magnetic resonance imaging (fMRI) has been widely used to localize brain functions. To further advance understanding of brain functions, it is critical to understand the direction of information flow, such as thalamocortical versus corticothalamic projections. For this work, we performed ultrahigh spatiotemporal resolution fMRI at 15.2 T of the mouse somatosensory network during forepaw somatosensory stimulation and optogenetic stimulation of the primary motor cortex (M1). Somatosensory stimulation induced the earliest BOLD response in the ventral posterolateral nucleus (VPL), followed by the primary somatosensory cortex (S1) and then M1 and posterior thalamic nucleus. Optogenetic stimulation of excitatory neurons in M1 induced the earliest BOLD response in M1, followed by S1 and then VPL. Within S1, the middle cortical layers responded to somatosensory stimulation earlier than the upper or lower layers, whereas the upper cortical layers responded earlier than the other two layers to optogenetic stimulation in M1. The order of early BOLD responses was consistent with the canonical understanding of somatosensory network connections and cannot be explained by regional variabilities in the hemodynamic response functions measured using hypercapnic stimulation. Our data demonstrate that early BOLD responses reflect the information flow in the mouse somatosensory network, suggesting that high-field fMRI can be used for systems-level network analyses.

Point-spread function of the BOLD response across columns and cortical depth in human extra-striate cortex

Columns and layers are fundamental organizational units of the brain. Well known examples of cortical columns are the ocular dominance columns (ODCs) in primary visual cortex and the column-like stripe-based arrangement in the second visual area V2. The spatial scale of columns and layers is beyond the reach of conventional neuroimaging, but the advent of high field magnetic resonance imaging (MRI) scanners (UHF, 7 T and above) has opened the possibility to acquire data at this spatial scale, in-vivo and non-invasively in humans. The most prominent non-invasive technique to measure brain function is blood oxygen level dependent (BOLD) fMRI, measuring brain activity indirectly, via changes in hemodynamics. A key determinant of the ability of high-resolution BOLD fMRI to accurately resolve columns and layers is the point-spread function (PSF) of the BOLD response in relation to the spatial extent of neuronal activity. In this study we take advantage of the stripe-based arrangement present in visual area V2, coupled with sub-millimetre anatomical and gradient-echo BOLD (GE BOLD) acquisition at 7 T to obtain PSF estimates and along cortical depth in human participants. Results show that the BOLD PSF is maximal in the superficial part of the cortex (1.78 mm), and it decreases with increasing cortical depth (0.83 mm close to white matter).

Validating Linear Systems Analysis for Laminar fMRI: Temporal Additivity for Stimulus Duration Manipulations

Advancements in ultra-high field (7 T and higher) magnetic resonance imaging (MRI) scanners have made it possible to investigate both the structure and function of the human brain at a sub-millimeter scale. As neuronal feedforward and feedback information arrives in different layers, sub-millimeter functional MRI has the potential to uncover information processing between cortical micro-circuits across cortical depth, i.e. laminar fMRI. For nearly all conventional fMRI analyses, the main assumption is that the relationship between local neuronal activity and the blood oxygenation level dependent (BOLD) signal adheres to the principles of linear systems theory. For laminar fMRI, however, directional blood pooling across cortical depth stemming from the anatomy of the cortical vasculature, potentially violates these linear system assumptions, thereby complicating analysis and interpretation. Here we assess whether the temporal additivity requirement of linear systems theory holds for laminar fMRI. We measured responses elicited by viewing stimuli presented for different durations and evaluated how well the responses to shorter durations predicted those elicited by longer durations. We find that BOLD response predictions are consistently good predictors for observed responses, across all cortical depths, and in all measured visual field maps (V1, V2, and V3). Our results suggest that the temporal additivity assumption for linear systems theory holds for laminar fMRI. We thus show that the temporal additivity assumption holds across cortical depth for sub-millimeter gradient-echo BOLD fMRI in early visual cortex.