Vascular autorescaling of fMRI (VasA fMRI) improves sensitivity of population studies: A pilot study

Loss, gain and choice difficulty in gambling patients: Neural and behavioural processes

Impaired decision-making is often displayed by individuals suffering from gambling disorder (GD). Since there are a variety of different phenomena influencing decision-making, we focused in this study on the effects of GD on neural and behavioural processes related to loss aversion and choice difficulty. Behavioural responses as well as brain images of 23 patients with GD and 20 controls were recorded while they completed a mixed gambles task, where they had to decide to either accept or reject gambles with different amounts of potential gain and loss. We found no behavioural loss aversion in either group and no group differences regarding loss and gain-related choice behaviour, but there was a weaker relation between choice difficulty and decision time in patients with GD. Similarly, we observed no group differences in processing of losses or gains, but choice difficulty was weaker associated with brain activity in the right anterior insula and anterior cingulate cortex in patients with GD. Our results showed for the first time the effects of GD on neural processes related to choice difficulty. In addition, our findings on choice difficulty give new insights on the psychopathology of GD and on neural processes related to impaired decision-making in GD.

Breath-hold BOLD fMRI without CO2 sampling enables estimation of venous cerebral blood volume: potential use in normalization of stimulus-evoked BOLD fMRI data

BOLD fMRI signal has been used in conjunction with vasodilatory stimulation as a marker of cerebrovascular reactivity (CVR): the relative change in cerebral blood flow (CBF) arising from a unit change in the vasodilatory stimulus. Using numerical simulations, we demonstrate that the variability in the relative BOLD signal change induced by vasodilation is strongly influenced by the variability in deoxyhemoglobin-containing cerebral blood volume (CBV), as this source of variability is likely to be more prominent than that of CVR. It may, therefore, be more appropriate to describe the relative BOLD signal change induced by an isometabolic vasodilation as a proxy of deoxygenated CBV (CBVdHb) rather than CVR. With this in mind, a new method was implemented to map a marker of CBVdHb, termed BOLD-CBV, based on the normalization of voxel-wise BOLD signal variation by an estimate of the intravascular venous BOLD signal from voxels filled with venous blood. The intravascular venous BOLD signal variation, recorded during repeated breath-holding, was extracted from the superior sagittal sinus in a cohort of 27 healthy volunteers and used as a regressor across the whole brain, yielding maps of BOLD-CBV. In the same cohort, we demonstrated the potential use of BOLD-CBV for the normalization of stimulus-evoked BOLD fMRI by comparing group-level BOLD fMRI responses to a visuomotor learning task with and without the inclusion of voxel-wise vascular covariates of BOLD-CBV and the BOLD signal change per mmHg variation in end-tidal carbon dioxide (BOLD-CVR). The empirical measure of BOLD-CBV accounted for more between-subject variability in the motor task-induced BOLD responses than BOLD-CVR estimated from end-tidal carbon dioxide recordings. The new method can potentially increase the power of group fMRI studies by including a measure of vascular characteristics and has the strong practical advantage of not requiring experimental measurement of end-tidal carbon dioxide, unlike traditional methods to estimate BOLD-CVR. It also more closely represents a specific physiological characteristic of brain vasculature than BOLD-CVR, namely blood volume.

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.

Correspondence between BOLD fMRI task response and cerebrovascular reactivity across the cerebral cortex

BOLD sensitivity to baseline perfusion and blood volume is a well-acknowledged fMRI confound. Vascular correction techniques based on cerebrovascular reactivity (CVR) might reduce variance due to baseline cerebral blood volume, however this is predicated on an invariant linear relationship between CVR and BOLD signal magnitude. Cognitive paradigms have relatively low signal, high variance and involve spatially heterogenous cortical regions; it is therefore unclear whether the BOLD response magnitude to complex paradigms can be predicted by CVR. The feasibility of predicting BOLD signal magnitude from CVR was explored in the present work across two experiments using different CVR approaches. The first utilized a large database containing breath-hold BOLD responses and 3 different cognitive tasks. The second experiment, in an independent sample, calculated CVR using the delivery of a fixed concentration of carbon dioxide and a different cognitive task. An atlas-based regression approach was implemented for both experiments to evaluate the shared variance between task-invoked BOLD responses and CVR across the cerebral cortex. Both experiments found significant relationships between CVR and task-based BOLD magnitude, with activation in the right cuneus (R ² = 0.64) and paracentral gyrus (R ² = 0.71), and the left pars opercularis (R ² = 0.67), superior frontal gyrus (R ² = 0.62) and inferior parietal cortex (R ² = 0.63) strongly predicted by CVR. The parietal regions bilaterally were highly consistent, with linear regressions significant in these regions for all four tasks. Group analyses showed that CVR correction increased BOLD sensitivity. Overall, this work suggests that BOLD signal response magnitudes to cognitive tasks are predicted by CVR across different regions of the cerebral cortex, providing support for the use of correction based on baseline vascular physiology.

Comparing end-tidal CO2, respiration volume per time (RVT), and average gray matter signal for mapping cerebrovascular reactivity amplitude and delay with breath-hold task BOLD fMRI

Cerebrovascular reactivity (CVR), defined as the cerebral blood flow response to a vasoactive stimulus, is an imaging biomarker with demonstrated utility in a range of diseases and in typical development and aging processes. A robust and widely implemented method to map CVR involves using a breath-hold task during a BOLD fMRI scan. Recording end-tidal CO₂ (P_ETCO₂) changes during the breath-hold task is recommended to be used as a reference signal for modeling CVR amplitude in standard units (%BOLD/mmHg) and CVR delay in seconds. However, obtaining reliable P_ETCO₂ recordings requires equipment and task compliance that may not be achievable in all settings. To address this challenge, we investigated two alternative reference signals to map CVR amplitude and delay in a lagged general linear model (lagged-GLM) framework: respiration volume per time (RVT) and average gray matter BOLD response (GM-BOLD). In 8 healthy adults with multiple scan sessions, we compare spatial agreement of CVR maps from RVT and GM-BOLD to those generated with P_ETCO₂. We define a threshold to determine whether a P_ETCO₂ recording has "sufficient" quality for CVR mapping and perform these comparisons in 16 datasets with sufficient P_ETCO₂ and 6 datasets with insufficient P_ETCO₂. When P_ETCO₂ quality is sufficient, both RVT and GM-BOLD produce CVR amplitude maps that are nearly identical to those from P_ETCO₂ (after accounting for differences in scale), with the caveat they are not in standard units to facilitate between-group comparisons. CVR delays are comparable to P_ETCO₂ with an RVT regressor but may be underestimated with the average GM-BOLD regressor. Importantly, when P_ETCO₂ quality is insufficient, RVT and GM-BOLD CVR recover reasonable CVR amplitude and delay maps, provided the participant attempted the breath-hold task. Therefore, our framework offers a solution for achieving high quality CVR maps in both retrospective and prospective studies where sufficient P_ETCO₂ recordings are not available and especially in populations where obtaining reliable measurements is a known challenge (e.g., children). Our results have the potential to improve the accessibility of CVR mapping and to increase the prevalence of this promising metric of vascular health.

Non-Neural Factors Influencing BOLD Response Magnitudes within Individual Subjects

To what extent is the size of the BOLD response influenced by factors other than neural activity? In a reanalysis of three neuroimaging datasets (male and female human participants), we find large systematic inhomogeneities in the BOLD response magnitude in primary visual cortex (V1): stimulus-evoked BOLD responses, expressed in units of percent signal change, are up to 50% larger along the representation of the horizontal meridian than the vertical meridian. To assess whether this surprising effect can be interpreted as differences in local neural activity, we quantified several factors that potentially contribute to the size of the BOLD response. We find relationships between BOLD response magnitude and cortical thickness, curvature, depth, and macrovasculature. These relationships are consistently found across subjects and datasets and suggest that variation in BOLD response magnitudes across cortical locations reflects, in part, differences in anatomy and vascularization. To compensate for these factors, we implement a regression-based correction method and show that, after correction, BOLD responses become more homogeneous across V1. The correction reduces the horizontal/vertical difference by about half, indicating that some of the difference is likely not because of neural activity differences. We conclude that interpretation of variation in BOLD response magnitude across cortical locations should consider the influence of the potential confounding factors of thickness, curvature, depth, and vascularization.SIGNIFICANCE STATEMENT The magnitude of the BOLD signal is often used as a surrogate of neural activity, but the exact factors that contribute to its strength have not been studied on a voxel-wise level. Here, we examined several anatomical and measurement-related factors to assess their relationship with BOLD signal magnitude. We find that BOLD magnitude correlates with cortical anatomy, depth, and macrovasculature. To remove the contribution of these factors, we propose a simple, data-driven correction method that can be used in any fMRI experiment. After accounting for the confounding factors, BOLD magnitude becomes more spatially homogeneous. Our correction method improves the ability to make more accurate inferences about local neural activity from fMRI data.

LayNii: A software suite for layer-fMRI

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

The effects of age on resting-state BOLD signal variability is explained by cardiovascular and cerebrovascular factors

Accurate identification of brain function is necessary to understand neurocognitive aging, and thereby promote health and well-being. Many studies of neurocognitive aging have investigated brain function with the blood-oxygen level-dependent (BOLD) signal measured by functional magnetic resonance imaging. However, the BOLD signal is a composite of neural and vascular signals, which are differentially affected by aging. It is, therefore, essential to distinguish the age effects on vascular versus neural function. The BOLD signal variability at rest (known as resting state fluctuation amplitude, RSFA), is a safe, scalable, and robust means to calibrate vascular responsivity, as an alternative to breath-holding and hypercapnia. However, the use of RSFA for normalization of BOLD imaging assumes that age differences in RSFA reflecting only vascular factors, rather than age-related differences in neural function (activity) or neuronal loss (atrophy). Previous studies indicate that two vascular factors, cardiovascular health (CVH) and cerebrovascular function, are insufficient when used alone to fully explain age-related differences in RSFA. It remains possible that their joint consideration is required to fully capture age differences in RSFA. We tested the hypothesis that RSFA no longer varies with age after adjusting for a combination of cardiovascular and cerebrovascular measures. We also tested the hypothesis that RSFA variation with age is not associated with atrophy. We used data from the population-based, lifespan Cam-CAN cohort. After controlling for cardiovascular and cerebrovascular estimates alone, the residual variance in RSFA across individuals was significantly associated with age. However, when controlling for both cardiovascular and cerebrovascular estimates, the variance in RSFA was no longer associated with age. Grey matter volumes did not explain age differences in RSFA, after controlling for CVH. The results were consistent between voxel-level analysis and independent component analysis. Our findings indicate that cardiovascular and cerebrovascular signals are together sufficient predictors of age differences in RSFA. We suggest that RSFA can be used to separate vascular from neuronal factors, to characterize neurocognitive aging. We discuss the implications and make recommendations for the use of RSFA in the research of aging.

Cerebrovascular Reactivity Mapping Without Gas Challenges: A Methodological Guide

Cerebrovascular reactivity (CVR) is defined as the ability of vessels to alter their caliber in response to vasoactive factors, by means of dilating or constricting, in order to increase or decrease regional cerebral blood flow (CBF). Importantly, CVR may provide a sensitive biomarker for pathologies where vasculature is compromised. Furthermore, the spatiotemporal dynamics of CVR observed in healthy subjects, reflecting regional differences in cerebral vascular tone and response, may also be important in functional MRI studies based on neurovascular coupling mechanisms. Assessment of CVR is usually based on the use of a vasoactive stimulus combined with a CBF measurement technique. Although transcranial Doppler ultrasound has been frequently used to obtain global flow velocity measurements, MRI techniques are being increasingly employed for obtaining CBF maps. For the vasoactive stimulus, vasodilatory hypercapnia is usually induced through the manipulation of respiratory gases, including the inhalation of increased concentrations of carbon dioxide. However, most of these methods require an additional apparatus and complex setups, which not only may not be well-tolerated by some populations but are also not widely available. For these reasons, strategies based on voluntary breathing fluctuations without the need for external gas challenges have been proposed. These include the task-based methodologies of breath holding and paced deep breathing, as well as a new generation of methods based on spontaneous breathing fluctuations during resting-state. Despite the multitude of alternatives to gas challenges, existing literature lacks definitive conclusions regarding the best practices for the vasoactive modulation and associated analysis protocols. In this work, we perform an extensive review of CVR mapping techniques based on MRI and CO2 variations without gas challenges, focusing on the methodological aspects of the breathing protocols and corresponding data analysis. Finally, we outline a set of practical guidelines based on generally accepted practices and available data, extending previous reports and encouraging the wider application of CVR mapping methodologies in both clinical and academic MRI settings.

Separating vascular and neuronal effects of age on fMRI BOLD signals

Accurate identification of brain function is necessary to understand the neurobiology of cognitive ageing, and thereby promote well-being across the lifespan. A common tool used to investigate neurocognitive ageing is functional magnetic resonance imaging (fMRI). However, although fMRI data are often interpreted in terms of neuronal activity, the blood oxygenation level-dependent (BOLD) signal measured by fMRI includes contributions of both vascular and neuronal factors, which change differentially with age. While some studies investigate vascular ageing factors, the results of these studies are not well known within the field of neurocognitive ageing and therefore vascular confounds in neurocognitive fMRI studies are common. Despite over 10 000 BOLD-fMRI papers on ageing, fewer than 20 have applied techniques to correct for vascular effects. However, neurovascular ageing is not only a confound in fMRI, but an important feature in its own right, to be assessed alongside measures of neuronal ageing. We review current approaches to dissociate neuronal and vascular components of BOLD-fMRI of regional activity and functional connectivity. We highlight emerging evidence that vascular mechanisms in the brain do not simply control blood flow to support the metabolic needs of neurons, but form complex neurovascular interactions that influence neuronal function in health and disease. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.

Neurologic Factors in Patients with Vascular Mild Cognitive Impairment Based on fMRI

This study focused on the application of functional magnetic resonance imaging and neuropsychology in diagnosis of vascular mild cognitive impairment (MCI) and the exploration of its relevant factors. The study enrolled 28 patients with vascular MCI in an observation group and 30 healthy individuals in a control group. All patients underwent magnetic resonance imaging. An automatic segmentation algorithm based on graph theory was adopted to process the images. Age, sex, disease course, Montreal Cognitive Assessment score, regional homogeneity, and amplitude of low-frequency fluctuation levels were recorded. There were no significant differences in age, gender, and course of disease between the observation group and the control group (P > 0.05). The level of regional homogeneity in the left posterior cerebellum in the observation group was significantly higher than that in the control group (P < 0.05).The regional homogeneity level of bilateral cingulate cortex was negatively correlated with Montreal Cognitive Assessment score (P < 0.05). The amplitude of low-frequency fluctuation of bilateral inferior parietal lobe, parietal lobe, and prefrontal lobe in the observation group was significantly lower than that in the control group, and the amplitude of low-frequency fluctuation of bilateral anterior cingulate gyrus, superior medial frontal gyrus, orbital frontal gyrus, right middle frontal gyrus, and right auxiliary motor area was higher than that in the control group (P < 0.05). Heart disease, such as myocardial infarction and atrial fibrillation, is a high risk factor for vascular MCI. Functional magnetic resonance imaging combined with an automatic segmentation algorithm can noninvasively observe the changes of a patient's brain tissue, which can be used in the recognition of vascular MCI. The global network attributes of patients with depression tend to be more randomized and have stronger resilience under targeted attacks.

Activity in the fronto-parietal multiple-demand network is robustly associated with individual differences in working memory and fluid intelligence

Numerous brain lesion and fMRI studies have linked individual differences in executive abilities and fluid intelligence to brain regions of the fronto-parietal "multiple-demand" (MD) network. Yet, fMRI studies have yielded conflicting evidence as to whether better executive abilities are associated with stronger or weaker MD activations and whether this relationship is restricted to the MD network. Here, in a large-sample (n = 216) fMRI investigation, we found that stronger activity in MD regions - functionally defined in individual participants - was robustly associated with more accurate and faster responses on a spatial working memory task performed in the scanner, as well as fluid intelligence measured independently (n = 114). In line with some prior claims about a relationship between language and fluid intelligence, we also found a weak association between activity in the brain regions of the left fronto-temporal language network during an independent passive reading task, and performance on the working memory task. However, controlling for the level of MD activity abolished this relationship, whereas the MD activity-behavior association remained highly reliable after controlling for the level of activity in the language network. Finally, we demonstrate how unreliable MD activity measures, coupled with small sample sizes, could falsely lead to the opposite, negative, association that has been reported in some prior studies. Taken together, these results demonstrate that a core component of individual differences variance in executive abilities and fluid intelligence is selectively and robustly positively associated with the level of activity in the MD network, a result that aligns well with lesion studies.

Cerebrovascular reactivity mapping using intermittent breath modulation

Cerebrovascular reactivity (CVR), an index of brain vessel's dilatory capacity, is typically measured using hypercapnic gas inhalation or breath-holding as a vasoactive challenge. However, these methods require considerable subject cooperation and could be challenging in clinical studies. More recently, there have been attempts to use resting-state BOLD data to map CVR by utilizing spontaneous changes in breathing pattern. However, in subjects who have small fluctuations in their spontaneous breathing pattern, the CVR results could be noisy and unreliable. In this study, we aim to develop a new method for CVR mapping that does not require gas-inhalation yet provides substantially higher sensitivity than resting-state CVR mapping. This new method is largely based on resting-state scan, but introduces intermittent modulation of breathing pattern in the subject to enhance fluctuations in their end-tidal CO2 (EtCO2) level. Here we examined the comfort level, sensitivity, and accuracy of this method in two studies. First, in 8 healthy young subjects, we developed the intermittent breath-modulation method using two different modulation frequencies, 6 ​s per breath and 12 ​s per breath, respectively, and compared the results to three existing CVR methods, specifically hypercapnic gas inhalation, breath-holding, and resting-state. Our results showed that the comfort level of the 6-s breath-modulation method was significantly higher than breath-holding (p ​= ​0.007) and CO2-inhalation (p ​= ​0.015) methods, while not different from the resting-state, i.e. free breathing method (p ​= ​0.52). When comparing the sensitivity of CVR methods, the breath-modulation methods revealed higher Z-statistics compared to the resting-state scan (p ​< ​0.008) and was comparable to breath-holding results. Next, we tested the feasibility of breath-modulation CVR mapping (6 ​s per breath) in 21 cognitively normal elderly participants and compared quantitative CVR values to that obtained with the CO2-inhalation method. Whole-brain CVR was found to be 0.150 ​± ​0.055 and 0.154 ​± ​0.032 %ΔBOLD/mmHg for the breath-modulation and CO2-inhalation method, respectively, with a significant correlation between them (y ​= ​0.97x, p ​= ​0.007). CVR mapping with intermittent breath modulation may be a useful method that combines the advantages of resting-state and CO2-inhalation based approaches.

Reduced spontaneous perspective taking in schizophrenia

Judgments about another person's visual perspective are impaired when the self-perspective is inconsistent with the other-perspective. This is a robust finding in healthy samples as well as in schizophrenia (SZ). Studies show evidence for the existence of a reverse effect, where an inconsistent other-perspective impairs the self-perspective. Such spontaneous perspective taking processes are not yet explored in SZ. In the current fMRI experiment, 24 healthy and 24 schizophrenic participants performed a visual perspective taking task in the scanner. Either a social or a non-social stimulus was presented and their visual perspectives were consistent or inconsistent with the self-perspective of the participant. We replicated previous findings showing that healthy participants show increased reaction times when the human avatar's perspective is inconsistent to the self-perspective. Patients with SZ, however, did not show this effect, neither in the social nor in the non-social condition. BOLD responses revealed similar patterns in occipital areas and group differences were identified in the middle occipital gyrus. These findings suggest that patients with SZ are less likely to spontaneously compute the visual perspectives of others.

On the Origin of Individual Functional Connectivity Variability: The Role of White Matter Architecture

Fingerprint patterns derived from functional connectivity (FC) can be used to identify subjects across groups and sessions, indicating that the topology of the brain substantially differs between individuals. However, the source of FC variability inferred from resting-state functional magnetic resonance imaging remains unclear. One possibility is that these variations are related to individual differences in white matter structural connectivity (SC). However, directly comparing FC with SC is challenging given the many potential biases associated with quantifying their respective strengths. In an attempt to circumvent this, we employed a recently proposed test-retest approach that better quantifies inter-subject variability by first correcting for intra-subject nuisance variability (i.e., head motion, physiological differences in brain state, etc.) that can artificially influence FC and SC measures. Therefore, rather than directly comparing the strength of FC with SC, we asked whether brain regions with, for example, low inter-subject FC variability also exhibited low SC variability. From this, we report two main findings: First, at the whole-brain level, SC variability was significantly lower than FC variability, indicating that an individual's structural connectome is far more similar to another relative to their functional counterpart even after correcting for noise. Second, although FC and SC variability were mutually low in some brain areas (e.g., primary somatosensory cortex) and high in others (e.g., memory and language areas), the two were not significantly correlated across all cortical and sub-cortical regions. Taken together, these results indicate that even after correcting for factors that may differently affect FC and SC, the two, nonetheless, remain largely independent of one another. Further work is needed to understand the role that direct anatomical pathways play in supporting vascular-based measures of FC and to what extent these measures are dictated by anatomical connectivity.

Schizophrenia and Category-Selectivity in the Brain: Normal for Faces but Abnormal for Houses

Face processing is regularly found to be impaired in schizophrenia (SZ), thus suggesting that social malfunctioning might be caused by dysfunctional face processing. Most studies focused on emotional face processes, whereas non-emotional face processing received less attention. While current reports on abnormal face processing in SZ are mixed, examinations of non-emotional face processing compared to adequate control stimuli may clarify whether SZ is characterized by a face-processing deficit. Patients with SZ (n = 28) and healthy controls (n = 30) engaged in an fMRI scan where images of non-emotional faces and houses were presented. A simple inverted-picture detection task warranted the participants' attention. Region of interest (ROI) analyses were conducted on face-sensitive regions including the fusiform face area, the occipital face area, and the superior temporal sulcus. Scene-sensitivity was assessed in the parahippocampal place area (PPA) and served as control condition. Patients did not show aberrant face-related neural processes in face-sensitive regions. This finding was also evident when analyses were done on individually defined ROIs or on in-house-localizer ROIs. Patients revealed a decreased specificity toward house stimuli as reflected in decreased neural response toward houses in the PPA. Again, this result was supported by supplementary analyses. Neural activation toward neutral faces was not found to be impaired in SZ, therefore speaking against an overall face-processing deficit. Aberrant activation in scene-sensitive PPA is also found in assessments of memory processes in SZ. It is up to future studies to show how impairments in PPA relate to functional outcome in SZ.

Monitoring cardiac and respiratory physiology during FMRI

This article will consider how physiological monitoring can be used both as an intrinsic part of an experiment, or for removing unwanted physiological signals from the FMRI time series. As functional MRI is used for a wide variety of applications beyond the identification of regions involved in a task, different sources of noise in the time series become important. The use of arterial spin labelling sequences, either in isolation or combined with BOLD imaging, means that temporal noise must be dealt with differently. Moreover, when these are combined with global cerebrovascular stimuli, such as respiratory challenges, the standard analysis tools must be employed with great care so as not to detrimentally distort the data. Acquiring and analysing physiological data is sometimes more art than science, and this article attempts to provide some insight into common techniques as well as advice on identifying and correcting some of the problems that may be encountered.

Cerebrovascular reactivity mapping without gas challenges

Cerebrovascular reactivity (CVR), the ability of cerebral vessels to dilate or constrict, has been shown to provide valuable information in the diagnosis and treatment evaluation of patients with various cerebrovascular conditions. CVR mapping is typically performed using hypercapnic gas inhalation as a vasoactive challenge while collecting BOLD images, but the inherent need of gas inhalation and the associated apparatus setup present a practical obstacle in applying it in routine clinical use. Therefore, we aimed to develop a new method to map CVR using resting-state BOLD data without the need of gas inhalation. This approach exploits the natural variation in respiration and measures its influence on BOLD MRI signal. In this work, we first identified a surrogate of the arterial CO₂ fluctuation during spontaneous breathing from the global BOLD signal. Second, we tested the feasibility and reproducibility of the proposed approach to use the above-mentioned surrogate as a regressor to estimate voxel-wise CVR. Third, we validated the "resting-state CVR map" with a conventional CVR map obtained with hypercapnic gas inhalation in healthy volunteers. Finally, we tested the utility of this new approach in detecting abnormal CVR in a group of patients with Moyamoya disease, and again validated the results using the conventional gas inhalation method. Our results showed that global BOLD signal fluctuation in the frequency range of 0.02-0.04Hz contains the most prominent contribution from natural variation in arterial CO₂. The CVR map calculated using this signal as a regressor is reproducible across runs (ICC=0.91±0.06), and manifests a strong spatial correlation with results measured with a conventional hypercapnia-based method in healthy subjects (r=0.88, p<0.001). We also found that resting-state CVR was able to identify vasodilatory deficit in patients with steno-occlusive disease, the spatial pattern of which matches that obtained using the conventional gas method (r=0.71±0.18). These results suggest that CVR obtained with resting-state BOLD may be a useful alternative in detecting vascular deficits in clinical applications when gas challenge is not feasible.

Techniques for blood volume fMRI with VASO: From low-resolution mapping towards sub-millimeter layer-dependent applications

Quantitative cerebral blood volume (CBV) fMRI has the potential to overcome several specific limitations of BOLD fMRI. It provides direct physiological interpretability and promises superior localization specificity in applications of sub-millimeter resolution fMRI applications at ultra-high magnetic fields (7T and higher). Non-invasive CBV fMRI using VASO (vascular space occupancy), however, is inherently limited with respect to its data acquisition efficiency, restricting its imaging coverage and achievable spatial and temporal resolution. This limitation may be reduced with recent advanced acceleration and reconstruction strategies that allow two-dimensional acceleration, such as in simultaneous multi-slice (SMS) 2D-EPI or 3D-EPI in combination with CAIPIRINHA field-of-view shifting. In this study, we sought to determine the functional sensitivity and specificity of these readout strategies with VASO over a broad range of spatial resolutions; spanning from low spatial resolution (3mm) whole-cortex to sub-millimeter (0.75mm) slab-of-cortex (for cortical layer-dependent applications). In the thermal-noise-dominated regime of sub-millimeter resolutions, 3D-EPI-VASO provides higher temporal stability and sensitivity to detect changes in CBV compared to 2D-EPI-VASO. In this regime, 3D-EPI-VASO unveils task activation located in the cortical laminae with little contamination from surface veins, in contrast to the cortical surface weighting of GE-BOLD fMRI. In the physiological-noise-dominated regime of lower resolutions, however, 2D-SMS-VASO shows superior performance compared to 3D-EPI-VASO. Due to its superior sensitivity at a layer-dependent level, 3D-EPI VASO promises to play an important role in future neuroscientific applications of layer-dependent fMRI.

Physiological basis of vascular autocalibration (VasA): Comparison to hypercapnia calibration methods

Purpose

The statistical power of functional MRI (fMRI) group studies is significantly hampered by high intersubject spatial and magnitude variance. We recently presented a vascular autocalibration method (VasA) to account for vascularization differences between subjects and hence improve the sensitivity in group studies. Here, we validate the novel calibration method by means of direct comparisons of VasA with more established measures of baseline venous blood volume (and indirectly vascular reactivity), the M‐value.

Methods

Seven healthy volunteers participated in two 7 T (T) fMRI experiments to compare M‐values with VasA estimates: (i) a hypercapnia experiment to estimate voxelwise M‐value maps, and (ii) an fMRI experiment using visual stimulation to estimate voxelwise VasA maps.

Results

We show that VasA and M‐value calibration maps show the same spatial profile, providing strong evidence that VasA is driven by local variations in vascular reactivity as reflected in the M‐value.

Conclusion

The agreement of vascular reactivity maps obtained with VasA when compared with M‐value maps confirms empirically the hypothesis that the VasA method is an adequate tool to account for variations in fMRI response amplitudes caused by vascular reactivity differences in healthy volunteers. VasA can therefore directly account for them and increase the statistical power of group studies. The VasA toolbox is available as a statistical parametric mapping (SPM) toolbox, facilitating its general application. Magn Reson Med 78:1168–1173, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Influence of Resting Venous Blood Volume Fraction on Dynamic Causal Modeling and System Identifiability

Changes in BOLD signals are sensitive to the regional blood content associated with the vasculature, which is known as V₀ in hemodynamic models. In previous studies involving dynamic causal modeling (DCM) which embodies the hemodynamic model to invert the functional magnetic resonance imaging signals into neuronal activity, V₀ was arbitrarily set to a physiolog-ically plausible value to overcome the ill-posedness of the inverse problem. It is interesting to investigate how the V₀ value influences DCM. In this study we addressed this issue by using both synthetic and real experiments. The results show that the ability of DCM analysis to reveal information about brain causality depends critically on the assumed V₀ value used in the analysis procedure. The choice of V₀ value not only directly affects the strength of system connections, but more importantly also affects the inferences about the network architecture. Our analyses speak to a possible refinement of how the hemody-namic process is parameterized (i.e., by making V₀ a free parameter); however, the conditional dependencies induced by a more complex model may create more problems than they solve. Obtaining more realistic V₀ information in DCM can improve the identifiability of the system and would provide more reliable inferences about the properties of brain connectivity.

Building a Science of Individual Differences from fMRI

To date, fMRI research has been concerned primarily with evincing generic principles of brain function through averaging data from multiple subjects. Given rapid developments in both hardware and analysis tools, the field is now poised to study fMRI-derived measures in individual subjects, and to relate these to psychological traits or genetic variations. We discuss issues of validity, reliability and statistical assessment that arise when the focus shifts to individual subjects and that are applicable also to other imaging modalities. We emphasize that individual assessment of neural function with fMRI presents specific challenges and necessitates careful consideration of anatomical and vascular between-subject variability as well as sources of within-subject variability.

The quest for the best: The impact of different EPI sequences on the sensitivity of random effect fMRI group analyses

We compared the sensitivity of standard single-shot 2D echo planar imaging (EPI) to three advanced EPI sequences, i.e., 2D multi-echo EPI, 3D high resolution EPI and 3D dual-echo fast EPI in fixed effect and random effects group level fMRI analyses at 3 T. The study focused on how well the variance reduction in fixed effect analyses achieved by advanced EPI sequences translates into increased sensitivity in the random effects group level analysis. The sensitivity was estimated in a functional MRI experiment of an emotional learning and a reward based learning tasks in a group of 24 volunteers. Each experiment was acquired with the four different sequences. The task-related response amplitude, contrast level and respective t-value were proxies for the functional sensitivity across the brain. All three advanced EPI methods increased the sensitivity in the fixed effects analyses, but standard single-shot 2D EPI provided a comparable performance in random effects group analysis when whole brain coverage and moderate resolution are required. In this experiment inter-subject variability determined the sensitivity of the random effects analysis for most brain regions, making the impact of EPI pulse sequence improvements less relevant or even negligible for random effects analyses. An exception concerns the optimization of EPI reducing susceptibility-related signal loss that translates into an enhanced sensitivity e.g. in the orbitofrontal cortex for multi-echo EPI. Thus, future optimization strategies may best aim at reducing inter-subject variability for higher sensitivity in standard fMRI group studies at moderate spatial resolution.

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We compared the sensitivity of standard and three advanced EPI sequences in group level fMRI analysis.

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Advanced EPI methods increased the sensitivity in the fixed effect group analyses.

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All EPI methods provided similar sensitivity in random effect group analysis.

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Inter-subject variance determined the sensitivity of the random effect analysis.

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Future sequence optimization best aim at reducing inter-subject rather then intra-subject variance.