Search

Abstract: Recent studies have demonstrated that multivariate machine learning algorithms applied to human functional MRI data can decode information segregated in cortical columns, despite the voxel size being large relative to the width of columns. The mechanism by which low spatial resolution imaging decodes information represented in a fine-scale organization is not clear. To investigate mechanisms underlying decoding signals we employed high-resolution gradient-echo BOLD functional MRI of visual area V1. We show that in addition to the fine-scale ocular dominance columns, coarse-scale structures extending over several millimeters also convey discriminative power for decoding the stimulated eye. Discriminative power is conveyed by both macroscopic blood vessels and gray matter regions. We hypothesize that gray-matter regions which drain into specific vessels may preferentially contain ocular-dominance columns biased towards one eye; the bias of a specific region thereby causing a functionally selective ocular-dominance response in the associated vessel. Our findings indicate that coarse-scale structures and macroscopic blood vessels contribute to decoding of the stimulated eye based on low-resolution multivariate data. [Copyright &y& Elsevier]

Abstract: Cells in the mammalian brain tend to be grouped together according to their afferent and efferent connectivity, as well as their physiological properties. The columnar structures of neocortex are prominent examples of such modular organization, and have been studied extensively in anatomical and physiological experiments in rats, cats and monkeys. The importance of noninvasive study of such structures, in particular in human subjects, cannot be overemphasized. Not surprisingly, therefore, many attempts were made to map cortical columns using functional magnetic resonance imaging (fMRI). Yet, the robustness, repeatability, and generality of the hitherto used fMRI methodologies have been a subject of intensive debate. Using differential mapping in a high magnetic field magnet (7 T), we demonstrate here the ability of Hahn Spin-Echo (HSE) BOLD to map the ocular dominance columns (ODCs) of the human visual cortex reproducibly over several days with a high degree of accuracy, relative to expected spatial patterns from post-mortem data. On the other hand, the conventional Gradient-Echo (GE) blood oxygen level dependent (BOLD) signal in some cases failed to resolve ODCs uniformly across the selected gray matter region, due to the presence of non-specific signals. HSE signals uniformly resolved the ODC patterns, providing a more generalized mapping methodology (i.e. one that does not require adjusting experimental approaches based on prior knowledge or assumptions about functional organization and vascular structure in order to avoid confounding large vessel effects) to map unknown columnar systems in the human brain, potentially paving the way both for the study of the functional architecture of human sensory cortices, and of brain modules underlying specific cognitive processes. [Copyright &y& Elsevier]

Abstract: The use of functional magnetic resonance imaging (fMRI) in alert non-human primates is of great potential for research in systems neuroscience. It can be combined with invasive techniques and afford better understanding of non-invasively acquired brain imaging signals in humans. However, the difficulties in optimal application of alert monkey fMRI are multi-faceted, especially at high magnetic fields where the effects of motion and of changes in B 0 are greatly amplified. To overcome these difficulties, strict behavioral controls and elaborate animal-training are needed. Here, we introduce a number of hardware developments, quantify the effect of movements on fMRI data, and present procedures for animal training and scanning for well-controlled and artifact-reduced alert monkey fMRI at high magnetic field. In particular, we describe systems for monitoring jaw and body movements, and for accurately tracking eye movements. A link between body and jaw movement and MRI image artifacts is established, showing that relying on the immobilization of an animal’s head is not sufficient for high-quality imaging. Quantitative analysis showed that body and jaw movement events caused large instabilities in fMRI time series. On average, body movement events caused larger instabilities than jaw movement events. Residual baseline brain image position and signal amplitude shifts were observed after the jaw and body movement events ended. Based on these findings, we introduce a novel behavioral paradigm that relies on training the monkeys to stay still during long trials. A corresponding analysis method discards all data that were not obtained during the movement-free periods. The baseline position and amplitude shifts are overcome by motion correction and trial-by-trial signal normalization. The advantages of the presented method over conventional scanning and analysis are demonstrated with data obtained at 7 T. It is anticipated that the techniques presented here will prove useful for alert monkey fMRI at any magnetic field. [Copyright &y& Elsevier]

Abstract: This study investigated the spatio-temporal properties of blood-oxygenation level-dependent (BOLD) functional MRI (fMRI) signals in gray matter, excluding the confounding, inaccurate contributions of large blood vessels. We quantified the spatial specificity of the BOLD response, and we investigated whether this specificity varies as a function of time from stimulus onset. fMRI was performed at 7 Tesla (T), where mapping signals of parenchymal origin are easily detected. Two abutting visual stimuli were adjusted to elicit responses centered on a flat gray matter region in V1. fMRI signals were sampled at high-resolution orthogonal to the retinotopic boundary between the representations of the stimuli. Signals from macro-vessels were masked out. Principal component analysis revealed that the first component in space accounted for 96.2±1.6% of the variance over time. The spatial profile of this time-invariant response was fitted with a model consisting of the convolution of a step function and a Gaussian point-spread-function (PSF). The mean full-width at half-maximal-height of the fitted PSF was 2.34±0.20 mm. Based on simulations of confounding effects, we estimate that BOLD PSF in human gray matter is smaller than 2 mm. A time-point to time-point analysis revealed that the PSF obtained during the 3rd (1.52 mm) and 4th (1.99 mm) seconds of stimulation were narrower than the mean PSF obtained from the 5th second on (2.42±0.15 mm). The position of the edge of the responding region was offset (1.72±0.07 mm) from the boundary of the stimulated region, indicating a spatial non-linearity. Simulations showed that the effective contrast between active and non-active columns is reduced 25-fold when imaged using a PSF whose width is equal to the cycle of the imaged columnar organization. Thus, the PSF of the hyper-oxygenated BOLD response in human gray matter is narrower than that reported at 1.5 T, where macro-vessels dominate the mapping signals. The initial phase of this response is more spatially specific than later phases. Data acquisition methods that suppress macro-vascular signals should increase the spatial specificity of BOLD fMRI. The choice of optimal stimulus duration represents a trade-off between the spatial specificity and the overhead associated with short stimulus duration. [Copyright &y& Elsevier]

The capacity of functional MRI (fMRI) to resolve cortical columns depends on several factors. These include the spatial scale of the columnar pattern, the point-spread of the fMRI response, the voxel size, and the signal-to-noise ratio (SNR) considering thermal and physiological noise. However, it remains unknown how these factors combine, and what is the voxel size that optimizes fMRI of cortical columns. Here we combine current knowledge into a quantitative model of fMRI of realistic patterns of cortical columns with different spatial scales and degrees of irregularity. We compare different approaches for identifying patterns of cortical columns, including univariate and multivariate based detection, multi-voxel pattern analysis (MVPA) based decoding, and high-resolution imaging and reconstruction of the pattern of cortical columns. We present the dependence of the performance of each approach on the parameters of the imaged pattern as well as those of the data acquisition. In addition, we predict voxel sizes that optimize fMRI of cortical columns under various scenarios. We found that all measures associated with multivariate detection and decoding could be approximately calculated from a measure we termed “multivariate contrast-to-noise ratio” (mv-CNR), which is a function of the contrast-to-noise ratio (CNR) and number of voxels. Furthermore, mv-CNR implied that the optimal voxel width for detection and decoding is independent of changes in response amplitude, SNR and imaged volume that are not caused by changes in voxel size. For regular patterns, optimal voxel widths for detection, decoding and imaging/reconstructing the pattern of cortical columns were approximately half the main cycle length of the organization. Optimal voxel widths for irregular patterns were less dependent on the main cycle length, and differed between univariate detection, multivariate detection and decoding, and reconstruction. We compared the effects of different factors of Gradient Echo fMRI at 3 Tesla (T), Gradient Echo fMRI at 7T, and Spin-Echo fMRI at 7T on the detection, decoding, and reconstruction measures considered and found that in all cases the width of the fMRI point-spread had the most significant effect. In contrast, different response amplitudes and noise characteristics played a relatively minor role. We recommend specific voxel widths for optimal univariate detection, for multivariate detection and decoding, and for high-resolution imaging of cortical columns under these three data-acquisition scenarios. Our study supports the planning, optimization, and interpretation of high-resolution fMRI of cortical columns and the decoding of information conveyed by these columns. [ABSTRACT FROM AUTHOR]

The task-evoked positive BOLD response (PBR) to a unilateral visual hemi-field stimulation is often accompanied by robust and sustained contralateral as well as ipsilateral negative BOLD responses (NBRs) in the visual cortex. The signal characteristics and the neural and/or vascular mechanisms that underlie these two types of NBRs are not completely understood. In this paper, we investigated the properties of these two types of NBRs. We first demonstrated the linearity of both NBRs with respect to stimulus duration. Next, we showed that the hemodynamic response functions (HRFs) of the two NBRs were similar to each other, but significantly different from that of the PBR. Moreover, the subject-wise expressions of the two NBRs were tightly coupled to the degree that the correlation between the two NBRs was significantly higher than the correlation between each NBR and the PBR. However, the activation patterns of the two NBRs did not show a high level of interhemispheric spatial similarity, and the functional connectivity between them was not different than the interhemispheric functional connectivity between the NBRs and PBR. Finally, while attention did modulate both NBRs, the attention-related changes in their HRFs were similar. Our findings suggest that the two NBRs might be generated through common neural and/or vascular mechanisms involving distal/deep brain regions that project to the two hemispheres. [ABSTRACT FROM AUTHOR]

• Seven brain regions show both reduced cortical thickness and abnormal QSM levels in AD patients. • We observed significant correlations across AD patients between region-specific cortical thickness and network topology. • Decreased correlation between QSM value and structural network efficiency in AD patients at individual level across brain regions with reduced cortical thickness and aberrant QSM value. Aberrant susceptibility due to iron level abnormality and brain network disconnections are observed in Alzheimer's disease (AD), with disrupted iron homeostasis hypothesized to be linked to AD pathology and neuronal loss. However, whether associations exist between abnormal quantitative susceptibility mapping (QSM), brain atrophy, and altered brain connectome in AD remains unclear. Based on multi-parametric brain imaging data from 30 AD patients and 26 healthy controls enrolled at the China-Japan Friendship Hospital, we investigated the abnormality of the QSM signal and volumetric measure across 246 brain regions in AD patients. The structural and functional connectomes were constructed based on diffusion MRI tractography and functional connectivity, respectively. The network topology was quantified using graph theory analyses. We identified seven brain regions with both reduced cortical thickness and abnormal QSM (p < 0.05) in AD, including the right superior frontal gyrus, left superior temporal gyrus, right fusiform gyrus, left superior parietal lobule, right superior parietal lobule, left inferior parietal lobule, and left precuneus. Correlations between cortical thickness and network topology computed across patients in the AD group resulted in statistically significant correlations in five of these regions, with higher correlations in functional compared to structural topology. We computed the correlation between network topological metrics, QSM value and cortical thickness across regions at both individual and group-averaged levels, resulting in a measure we call spatial correlations. We found a decrease in the spatial correlation of QSM and the global efficiency of the structural network in AD patients at the individual level. These findings may provide insights into the complex relationships among QSM, brain atrophy, and brain connectome in AD. [ABSTRACT FROM AUTHOR]

Abstract: At very high magnetic fields, GE BOLD fMRI is expected to contain nonspecific contributions and behave differently than HSE fMRI data. Similarly, the two approaches can conceivably suffer from different contributions to temporal instabilities in a times series that ultimately determine the contrast-to-noise ratio (CNR). We investigate the signal and signal fluctuation characteristics in GE and HSE fMRI data with the imaging parameters separately optimized for each contrast at 7 T. In HSE fMRI, activation-induced fractional signal change (ΔS/S) decreased rapidly, and the ratio of standard deviations of image-to-image fluctuations due to physiological processes (σ Phys) to thermal noise (σ Therm) remained constant with increasing voxel volume. In contrast, ΔS/S as well as volume of activated voxels was virtually independent of voxel size for GE BOLD, and σ Phys/σ Therm increased with increasing voxel size. The ratio of BOLD signal changes (GE/HSE) was much closer to 1 in tissue areas compared to vessel areas. These observations led to the conclusions that the spatial extent of the activation-induced ΔS/S was much broader in the GE data, and that the physiological processes that give rise to the temporal fluctuations lost coherence over millimeter distances in HSE compared to GE fMRI data. While further studies are needed to characterize it fully, σ Phys in HSE data was clearly different than in GE data. It was concluded that HSE imaging yields a significantly reduced amount of nonspecific signals compared to GE imaging, and, would be the method of choice (over GE) for high-resolution applications in humans. [Copyright &y& Elsevier]

• QQ-CCTV mapping of oxygen extraction fraction and cerebral metabolic rate of oxygen consumption is a new approach to noninvasively quantify cerebral oxygen metabolism. • Typical parieto-temporal hypoperfusion and hypometabolism patterns were observed in Alzheimer's disease. • Cerebral blood flow and cerebral metabolic rate of oxygen consumption values in hippocampus were correlated with cognition scores. The objective of this study was to evaluate the whole-brain pattern of oxygen extraction fraction (OEF), cerebral blood flow (CBF), and cerebral metabolic rate of oxygen consumption (CMRO 2) perturbation in Alzheimer's disease (AD) and investigate the relationship between regional cerebral oxygen metabolism and global cognition. Twenty-six AD patients and 25 age-matched healthy controls (HC) were prospectively recruited in this study. Mini-Mental State Examination (MMSE) was used to evaluate cognitive status. We applied the QQ-CCTV algorithm which combines quantitative susceptibility mapping and quantitative blood oxygen level-dependent models (QQ) for OEF calculation. CBF map was computed from arterial spin labeling and CMRO 2 was generated based on Fick's principle. Whole-brain and regional OEF, CBF, and CMRO 2 analyses were performed. The associations between these measures in substructures of deep brain gray matter and MMSE scores were assessed. Whole brain voxel-wise analysis showed that CBF and CMRO 2 values significantly decreased in AD predominantly in the bilateral angular gyrus, precuneus gyrus and parieto-temporal regions. Regional analysis showed that CBF value decreased in the bilateral caudal hippocampus and left rostral hippocampus and CMRO 2 value decreased in left caudal and rostral hippocampus in AD patients. Considering all subjects in the AD and HC groups combined, the mean CBF and CMRO 2 values in the bilateral hippocampus positively correlated with the MMSE score. CMRO 2 mapping with the QQ-CCTV method - which is readily available in MR systems for clinical practice - can be a potential biomarker for AD. In addition, CMRO 2 in the hippocampus may be a useful tool for monitoring cognitive impairment. [ABSTRACT FROM AUTHOR]

Previous attempts at characterizing the spatial specificity of the blood oxygenation level dependent functional MRI (BOLD fMRI) response by estimating its point-spread function (PSF) have conventionally relied on retinotopic spatial representations of visual stimuli in area V1. Consequently, their estimates were confounded by the width and scatter of receptive fields of V1 neurons. Here, we circumvent these limits by instead using the inherent cortical spatial organization of ocular dominance columns (ODCs) to determine the PSF for both Gradient Echo (GE) and Spin Echo (SE) BOLD imaging at 7 Tesla. By applying Markov chain Monte Carlo sampling on a probabilistic generative model of imaging ODCs, we quantified the PSFs that best predict the spatial structure and magnitude of differential ODCs' responses. Prior distributions for the ODC model parameters were determined by analyzing published data of cytochrome oxidase patterns from post-mortem histology of human V1 and of neurophysiological ocular dominance indices. The average PSF full-widths at half-maximum obtained from differential ODCs’ responses following the removal of voxels influenced by contributions from macroscopic blood vessels were 0.86 mm (SE) and 0.99 mm (GE). Our results provide a quantitative basis for the spatial specificity of BOLD fMRI at ultra-high fields, which can be used for planning and interpretation of high-resolution differential fMRI of fine-scale cortical organizations. [ABSTRACT FROM AUTHOR]

Abstract: The ratio of the changes in cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2) during brain activation is a critical determinant of the magnitude of the blood oxygenation level dependent (BOLD) response measured with functional magnetic resonance imaging (fMRI). Cytochrome oxidase (CO), a key component of oxidative metabolism in the mitochondria, is non-uniformly distributed in visual area V1 in distinct blob and interblob regions, suggesting significant spatial variation in the capacity for oxygen metabolism. The goal of this study was to test whether CBF/CMRO2 coupling differed when these subpopulations of neurons were preferentially stimulated, using chromatic and luminance stimuli to preferentially stimulate either the blob or interblob regions. A dual-echo spiral arterial spin labeling (ASL) technique was used to measure CBF and BOLD responses simultaneously in 7 healthy human subjects. When the stimulus contrast levels were adjusted to evoke similar CBF responses (mean 65.4%±19.0% and 64.6%±19.9%, respectively for chromatic and luminance contrast), the BOLD responses were remarkably similar (1.57%±0.39% and 1.59%±0.35%) for both types of stimuli. We conclude that CBF–CMRO2 coupling is conserved for the chromatic and luminance stimuli used, suggesting a consistent coupling for blob and inter-blob neuronal populations despite the difference in CO concentration. [Copyright &y& Elsevier]

Abstract: Recent studies have identified large scale brain networks based on the spatio-temporal structure of spontaneous fluctuations in resting-state fMRI data. It is expected that functional connectivity based on resting-state data is reflective of — but not identical to — the underlying anatomical connectivity. However, which functional connectivity analysis methods reliably predict the network structure remains unclear. Here we tested and compared network connectivity analysis methods by applying them to fMRI resting-state time-series obtained from the human visual cortex. The methods evaluated here are those previously tested against simulated data in Smith et al. (Neuroimage, 2011). To this end, we defined regions within retinotopic visual areas V1, V2, and V3 according to their eccentricity in the visual field, delineating central, intermediate, and peripheral eccentricity regions of interest (ROIs). These ROIs served as nodes in the models we study. We based our evaluation on the “ground-truth”, thoroughly studied retinotopically-organized anatomical connectivity in the monkey visual cortex. For each evaluated method, we computed the fractional rate of detecting connections known to exist (“c-sensitivity”), while using a threshold of the 95th percentile of the distribution of interaction magnitudes of those connections not expected to exist. Under optimal conditions — including session duration of 68min, a relatively small network consisting of 9 nodes and artifact-free regression of the global effect — each of the top methods predicted the expected connections with 67–85% c-sensitivity. Correlation methods, including Correlation (Corr; 85%), Regularized Inverse Covariance (ICOV; 84%) and Partial Correlation (PCorr; 81%) performed best, followed by Patel''s Kappa (80%), Bayesian Network method PC (BayesNet; 77%), General Synchronization measures (67–77%), and Coherence (CohB; 74%). With decreased session duration, these top methods saw decreases in c-sensitivities, achieving 59–76% for 17min sessions. With a short resting-state fMRI scan of 8.5min, none of the methods predicted the real network well, with Corr (65%) performing best. With increased complexity of the network from 9 to 36 nodes, multivariate methods including PCorr and BayesNet saw a decrease in performance. Artifact-free regression of the global effect increased the c-sensitivity of the top-performing methods. In an overall evaluation across all tests we performed, correlation methods (Corr, ICOV, and PCorr), Patel''s Kappa, and BayesNet method PC set themselves somewhat above all other methods. We propose that data-based calibration based on known anatomical connections be integrated into future network studies, in order to maximize sensitivity and reduce false positives. [Copyright &y& Elsevier]

Abstract: Multivariate machine learning algorithms applied to human functional MRI (fMRI) data can decode information conveyed by cortical columns, despite the voxel-size being large relative to the width of columns. Several mechanisms have been proposed to underlie decoding of stimulus orientation or the stimulated eye. These include: (I) aliasing of high spatial-frequency components, including the main frequency component of the columnar organization, (II) contributions from local irregularities in the columnar organization, (III) contributions from large-scale non-columnar organizations, (IV) functionally selective veins with biased draining regions, and (V) complex spatio-temporal filtering of neuronal activity by fMRI voxels. Here we sought to assess the plausibility of two of the suggested mechanisms: (I) aliasing and (II) local irregularities, using a naive model of BOLD as blurring and MRI voxel sampling. To this end, we formulated a mathematical model that encompasses both the processes of imaging ocular dominance (OD) columns and the subsequent linear classification analysis. Through numerical simulations of the model, we evaluated the distribution of functional differential contrasts that can be expected when considering the pattern of cortical columns, the hemodynamic point spread function, the voxel size, and the noise. We found that with data acquisition parameters used at 3 Tesla, sub-voxel supra-Nyquist frequencies, including frequencies near the main frequency of the OD organization (0.5 cycles per mm), cannot contribute to the differential contrast. The differential functional contrast of local origin is dominated by low-amplitude contributions from low frequencies, associated with irregularities of the cortical pattern. Realizations of the model with parameters that reflected best-case scenario and the reported BOLD point-spread at 3 Tesla (3.5mm) predicted decoding performances lower than those that have been previously obtained at this magnetic field strength. We conclude that low frequency components that underlie local irregularities in the columnar organization are likely to play a role in decoding. We further expect that fMRI-based decoding relies, in part, on signal contributions from large-scale, non-columnar functional organizations, and from complex spatio-temporal filtering of neuronal activity by fMRI voxels, involving biased venous responses. Our model can potentially be used for evaluating and optimizing data-acquisition parameters for decoding information conveyed by cortical columns. [Copyright &y& Elsevier]

Functional neuroimaging in the human brain using noninvasive magnetic resonance methods has the potential of providing highly resolved maps of neuronal activation. Decreasing the voxel size and obtaining simultaneously high temporal resolution is a major challenge and is mainly limited by sensitivity. Here, signal-to-noise gains at high magnetic fields (7 Tesla) and an optimized surface coil setup are combined with a novel approach for zoomed functional imaging in the visual cortex. For echoplanar imaging, the acquisition time and segmentation was shortened fourfold by using a reduced field-of-view. An adiabatic outer-volume suppression method, BISTRO, was used to obliterate signal outside the area-of-interest achieving effective suppression even for inhomogeneous B1-fields. A single-shot acquisition was performed at submillimeter resolution in the human brain, while simultaneously maintaining a high temporal resolution of 125 ms. Functional studies with and without field-of-view reduction were performed. Activation and percent change maps were compared with respect to spatial extent, t values and percentage changes of the BOLD contrast. The detection of functional activation was found to be equal within the inter-series variability for the two acquisition schemes. Thus, single-trial BOLD responses were detected for the first time robustly at a 500 × 500 μm2 in plane and 250 ms temporal resolution, significantly expanding the possibilities of event-related functional imaging in the human brain. The magnetization transfer effect induced by the outer-volume suppression pulses was investigated and found to be increased during neuronal activity. [Copyright &y& Elsevier]

The poly- δ- d -glutamic acid capsule of Bacillus anthracis plays a major role in this bacterium pathogenicity. Capsule synthesis relies on a 5 gene operon; capB, C, A, D and E that are regulated by acpA and acpB , that respond to the major virulence regulator – atxA. We took a genetic approach to examine the involvement of acpA and acpB in capsule production in vitro and on B. anthracis virulence in vivo. To complement the effect of the mutations on capsule accumulation in vitro, we applied our toxin independent systemic infection method to study their effects in vivo. We found that though the roles of acpA and axpB are redundant in vitro , deleting acpA had a significant effect on pathogenicity, mainly on the time to death. As expected, deletion of both acpA and acpB resulted in loss of capsule accumulation in vitro and full attenuation in vivo , indicating that capsule production depends exclusively on acpA/B regulation. To identify additional effects of acpA and acpB on pathogenicity via non-capsule related virulence pathways, we bypassed acpA/B regulation by inserting the pagA promotor upstream to the cap operon, diverting regulation directly to atxA. This resulted in restoration of capsule accumulation in vitro and virulence (in intravenous or subcutaneous inoculation) in vivo. To test for additional pXO2-based genes involved in capsule production, we cloned the pagA prom- capA-E into the chromosome of VollumΔpXO2, which restored capsule accumulation. These results indicate that of the pXO2 genes, only capA-E and acpA are required for capsule production. • AcpA and AcpB were previously shown to regulate Bacillus anthrcis capsule production. • acpA and acpB are mutually redundant in regulating capsule biosynthesis in virto and in vivo. • acpA plays a prominent role in this regulation. • Other than regulating capsule production, acpA or acpB are not involved in any major virulence pathway. • acpA, acpB and the CAP operon are the only pXO2 encoded genes necessary for capsule production. [ABSTRACT FROM AUTHOR]