White Matter fMRI Research Articles

Automatic Preprocessing Pipeline for White Matter Functional Analyses of Large-Scale Databases.

Recently, increasing evidence suggests that fMRI signals in white matter (WM), conventionally ignored as nuisance, are robustly detectable using appropriate processing methods and are related to neural activity, while changes in WM with aging and degeneration are also well documented. These findings suggest variations in patterns of BOLD signals in WM should be investigated. However, existing fMRI analysis tools, which were designed for processing gray matter signals, are not well suited for large-scale processing of WM signals in fMRI data. We developed an automatic pipeline for high-performance preprocessing of fMRI images with emphasis on quantifying changes in BOLD signals in WM in an aging population. At the image processing level, the pipeline integrated existing software modules with fine parameter tunings and modifications to better extract weaker WM signals. The preprocessing results primarily included whole-brain time-courses, functional connectivity, maps and tissue masks in a common space. At the job execution level, this pipeline exploited a local XNAT to store datasets and results, while using DAX tool to automatic distribute batch jobs that run on high-performance computing clusters. Through the pipeline, 5,034 fMRI/T1 scans were preprocessed. The intraclass correlation coefficient (ICC) of test-retest experiment based on the preprocessed data is 0.52 - 0.86 (N=1000), indicating a high reliability of our pipeline, comparable to previously reported ICC in gray matter experiments. This preprocessing pipeline highly facilitates our future analyses on WM functional alterations in aging and may be of benefit to a larger community interested in WM fMRI studies.

White Matter Functional Connectivity in Resting-State fMRI: Robustness, Reliability, and Relationships to Gray Matter.

A comprehensive characterization of the spatiotemporal organization in the whole brain is critical to understand both the function and dysfunction of the human brain. Resting-state functional connectivity (FC) of gray matter (GM) has helped in uncovering the inherent baseline networks of brain. However, the white matter (WM), which composes almost half of brain, has been largely ignored in this characterization despite studies indicating that FC in WM does change during task and rest functional magnetic resonance imaging (fMRI). In this study, we identify 9 white matter functional networks (WM-FNs) and 9 gray matter functional networks (GM-FNs) of resting fMRI. Intraclass correlation coefficient (ICC) was calculated on multirun fMRI data to estimate the reliability of static functional connectivity (SFC) and dynamic functional connectivity (DFC). Associations between SFC, DFC, and their respective ICCs are estimated for GM-FNs, WM-FNs, and GM-WM-FNs. SFC of GM-FNs were stronger than that of WM-FNs, but the corresponding DFC of GM-FNs was lower, indicating that WM-FNs were more dynamic. Associations between SFC, DFC, and their ICCs were similar in both GM- and WM-FNs. These findings suggest that WM fMRI signal contains rich spatiotemporal information similar to that of GM and may hold important cues to better establish the functional organization of the whole brain.

Research progress of brain white matter based on functional magnetic resonance imaging

<p indent=0mm>Functional magnetic resonance imaging (fMRI), a noninvasive imaging technology, measures metabolism and hemodynamics during brain activity based on blood oxygen level-dependent (BOLD) signals that indirectly reflect neural activity. Since the technique was proposed, it has been widely used in studies of cognitive neuroscience and clinical neuropsychiatry. The finding that BOLD signals between the bilateral sensorimotor cortices and other brain regions in the resting state had high temporal correlations led to the concept of functional connectivity being proposed. The functional connectivity method measures the degree of connection between different brain regions, revealing the functional integration of the brain, and has vigorously promoted the development of fMRI research. To date, however, fMRI applications usually focus on the cortical gray matter of the brain, in which blood vessels are relatively dense, rather than the deep white matter regions. The reasons are mainly attributed to the following two points. First, the vascular density, blood flow and blood volume are lower in white matter than in gray matter; thus, BOLD signal changes are much weaker. Second, white matter contains fewer postsynaptic potentials, which is the main source of BOLD signals. As a result, the reliability and biophysical origin of the white matter BOLD signal have always been controversial, and the BOLD signals from white matter have often been treated as noise in previous fMRI studies. In recent years, with the revelation of the physiological significance of BOLD signals in white matter, researchers have gradually turned their attention to fMRI studies of white matter. Through analysis, these studies have found that BOLD signals in white matter are generated by neural activity rather than by noise or artifacts and that white matter and gray matter have similar physiological origins and significance. It was demonstrated that external stimulation could activate white matter regions and that the white matter had functional networks similar to the gray matter cortex. Therefore, future studies should explore more activation patterns of white matter under tasks to further reveal the potential relationship between white matter function and individual behavior and cognition. In addition, the study of functional connectivity between white matter and gray matter further revealed functional interactions between them. Subsequent clinical studies found that patients generally showed abnormal white matter activity in the brain and pathological changes in its functional networks and that the dysfunctions in patients may also be related to abnormal communication between white matter and gray matter. Although white matter fMRI provides a direct method to investigate and evaluate white matter function, this research is still at a preliminary exploratory stage. At present, the function of deep brain white matter is rarely studied due to the limitations of analytic methods. Hence, future studies on white matter fMRI need to provide a set of normative and appropriate analytic methods to facilitate the in-depth development of related research.

CHARACTERIZATION OF SPATIAL DYNAMICS OF FMRI DATA IN WHITE MATTER USING DIFFUSION-INFORMED WHITE MATTER HARMONICS.

In this work, we leverage the Laplacian eigenbasis of voxel-wise white matter (WM) graphs derived from diffusion-weighted MRI data, dubbed WM harmonics, to characterize the spatial structure of WM fMRI data. Our motivation for such a characterization is based on studies that show WM fMRI data exhibit a spatial correlational anisotropy that coincides with underlying fiber patterns. By quantifying the energy content of WM fMRI data associated with subsets of WM harmonics across multiple spectral bands, we show that the data exhibits notable subtle spatial modulations under functional load that are not manifested during rest. WM harmonics provide a novel means to study the spatial dynamics of WM fMRI data, in such way that the analysis is informed by the underlying anatomical structure.

White Matter fMRI Activation Cannot Be Treated as a Nuisance Regressor: Overcoming a Historical Blind Spot

Despite past controversies, increasing evidence has led to acceptance that white matter activity is detectable using functional magnetic resonance imaging (fMRI). In spite of this, advanced analytic methods continue to be published that reinforce a historic bias against white matter activation by using it as a nuisance regressor. It is important that contemporary analyses overcome this blind spot in whole brain functional imaging, both to ensure that newly developed noise regression techniques are accurate, and to ensure that white matter, a vital and understudied part of the brain, is not ignored in functional neuroimaging studies.

Evaluation of different cerebrospinal fluid and white matter fMRI filtering strategies-Quantifying noise removal and neural signal preservation.

This study examines the impact of using different cerebrospinal fluid (CSF) and white matter (WM) nuisance signals for data-driven filtering of functional magnetic resonance imaging (fMRI) data as a cleanup method before analyzing intrinsic brain fluctuations. The routinely used temporal signal-to-noise ratio metric is inappropriate for assessing fMRI filtering suitability, as it evaluates only the reduction of data variability and does not assess the preservation of signals of interest. We defined a new metric that evaluates the preservation of selected neural signal correlates, and we compared its performance with a recently published signal-noise separation metric. These two methods provided converging evidence of the unfavorable impact of commonly used filtering approaches that exploit higher numbers of principal components from CSF and WM compartments (typically 5 + 5 for CSF and WM, respectively). When using only the principal components as nuisance signals, using a lower number of signals results in a better performance (i.e., 1 + 1 performed best). However, there was evidence that this routinely used approach consisting of 1 + 1 principal components may not be optimal for filtering resting-state (RS) fMRI data, especially when RETROICOR filtering is applied during the data preprocessing. The evaluation of task data indicated the appropriateness of 1 + 1 principal components, but when RETROICOR was applied, there was a change in the optimal filtering strategy. The suggested change for extracting WM (and also CSF in RETROICOR-corrected RS data) is using local signals instead of extracting signals from a large mask using principal component analysis.

0137 Bold fMRI Correlates Of Intermittent Sympathetic Vasoconstriction During Light Sleep

Variations in sympathetic and parasympathetic activity during sleep can lead to fluctuations in heart rate and vascular tone, potentially confounding fMRI measurements of brain activity that rely on hemodynamic signals. To investigate this, photo-plethysmography (PPG) based measurements of peripheral vasoconstriction were correlated with fMRI signals acquired during an overnight sleep study. BOLD fMRI data was obtained at 3T with gradient-echo-EPI (flip-angle=900, repeatition-time=3s, echo-time=36ms, voxel-size=2.5x2.5x2mm3, matrix-size=96x70x50, acceleration-factor=2). EEG and ECG were acquired concurrently with the fMRI with a 64-channel recorder (61 EEG scalp, 2 electro-oculography, and 1 ECG electrodes), synchronized to the MRI system-clock. Heart rate (HR), vascular tone inferred from PPG signal amplitude (AMP), and respiratory volume (RV) were derived from the PPG and chest belt signals. Initial inspection of all data (n=16) showed, primarily during N1/N2 sleep, striking variations in AMP, consisting of intermittently occurring 10-15s drops accompanied by a biphasic change in HR. Based on this a subset of data was selected (~20% of the scans) that had a high incidence of AMP drops and fMRI without motion artifacts. AMP drops had a strong correlate in the fMRI signal in both grey-matter (GM) and white-matter (WM). The covariation of fMRI signal and PPG-AMP often exceeded that with the more conventional physiological measures of HR and RV. Voxel-vise correlations between PPG-AMP and fMRI signals showed a striking negative correlation in central WM and around medullary-veins at 0-lag, turning positive after about 3-6s. In GM, maximum positive correlation was observed at around 6s time-lags. Intermittent AMP drops are interpreted as systemic vasoconstrictive events, possibly relating to correlations between EEG measures of arousal and AMP drops, as previously observed during sleep (Ackner et al., 1957). The fMRI effects suggest that this vasoconstriction also involves the central-nervous-system vasculature. The lag-dependent characteristic of the WM signal can be explained by a temporal mismatch between blood-volume and blood-oxygenation effects originating from vascular transit delays. A similar mechanism may explain previous findings of WM fMRI signals during both task- and resting-state fMRI. Intramural Research Program of the NINDS.

Contribution of systemic vascular effects to fMRI activity in white matter

To investigate a potential contribution of systemic physiology to recently reported BOLD fMRI signals in white matter, we compared photo-plethysmography (PPG) and whole-brain fMRI signals recorded simultaneously during long resting-state scans from an overnight sleep study. We found that intermittent drops in the amplitude of the PPG signal exhibited strong and widespread correlations with the fMRI signal, both in white matter (WM) and in gray matter (GM). The WM signal pattern resembled that seen in previous resting-state fMRI studies and closely tracked the location of medullary veins. Its temporal cross-correlation with the PPG amplitude was bipolar, with an early negative value. In GM, the correlation was consistently positive. Consistent with previous studies comparing physiological signals with fMRI, these findings point to a systemic vascular contribution to WM fMRI signals. The PPG drops are interpreted as systemic vasoconstrictive events, possibly related to intermittent increases in sympathetic tone related to fluctuations in arousal state. The counter-intuitive polarity of the WM signal is explained by long blood transit times in the medullary vasculature of WM, which cause blood oxygenation loss and a substantial timing mismatch between blood volume and blood oxygenation effects. A similar mechanism may explain previous findings of negative WM signals around large draining veins during both task- and resting-state fMRI.

Detecting white matter activity using conventional 3 Tesla fMRI: An evaluation of standard field strength and hemodynamic response function

Detection of functional magnetic resonance imaging (fMRI) activation in white matter has been increasingly reported despite historically being controversial. Much of the development work to-date has used high-field 4 T MRI and specialized pulse sequences. In the current study, we utilized conventional 3 T MRI and a commonly applied gradient-echo-planar imaging sequence to evaluate white matter (WM) fMRI sensitivity within a common framework. Functional WM activity was replicated in target regions of interest within the corpus callosum, at the group and individual levels. As expected there was a reduction in overall WM activation sensitivity. Individual analyses revealed that 8 of the 13 individuals showed white matter activation, showing a lower percentage of individuals with WM activation detected. Importantly, WM activation results were sensitive to analyses that applied alternate hemodynamic response functions, with an increase in the group level cluster when hemodynamic response function (HRF) onset slope was reduced. The findings supported the growing evidence that WM activation is detectable, with activation levels are closer to thresholds used for routine 3T MRI studies. Optimization factors, such as the HRF model, appear to be important to further enhance the characterization of WM activity in fMRI.

Does functional MRI detect activation in white matter? A review of emerging evidence, issues, and future directions.

Functional magnetic resonance imaging (fMRI) is a non-invasive technique that allows for visualization of activated brain regions. Until recently, fMRI studies have focused on gray matter. There are two main reasons white matter fMRI remains controversial: (1) the blood oxygen level dependent (BOLD) fMRI signal depends on cerebral blood flow and volume, which are lower in white matter than gray matter and (2) fMRI signal has been associated with post-synaptic potentials (mainly localized in gray matter) as opposed to action potentials (the primary type of neural activity in white matter). Despite these observations, there is no direct evidence against measuring fMRI activation in white matter and reports of fMRI activation in white matter continue to increase. The questions underlying white matter fMRI activation are important. White matter fMRI activation has the potential to greatly expand the breadth of brain connectivity research, as well as improve the assessment and diagnosis of white matter and connectivity disorders. The current review provides an overview of the motivation to investigate white matter fMRI activation, as well as the published evidence of this phenomenon. We speculate on possible neurophysiologic bases of white matter fMRI signals, and discuss potential explanations for why reports of white matter fMRI activation are relatively scarce. We end with a discussion of future basic and clinical research directions in the study of white matter fMRI.

Sensitivity to white matter FMRI activation increases with field strength.

Functional magnetic resonance imaging (fMRI) activation in white matter is controversial. Given that many of the studies that report fMRI activation in white matter used high field MRI systems, we investigated the field strength dependence of sensitivity to white matter fMRI activation. In addition, we evaluated the temporal signal to noise ratio (tSNR) of the different tissue types as a function of field strength. Data were acquired during a motor task (finger tapping) at 1.5 T and 4 T. Group and individual level activation results were considered in both the sensorimotor cortex and the posterior limb of the internal capsule. We found that sensitivity increases associated with field strength were greater for white matter than gray matter. The analysis of tSNR suggested that white matter might be less susceptible to increases in physiological noise related to increased field strength. We therefore conclude that high field MRI may be particularly advantageous for fMRI studies aimed at investigating activation in both gray and white matter.

White versus gray matter: fMRI hemodynamic responses show similar characteristics, but differ in peak amplitude

BackgroundThere is growing evidence for the idea of fMRI activation in white matter. In the current study, we compared hemodynamic response functions (HRF) in white matter and gray matter using 4 T fMRI. White matter fMRI activation was elicited in the isthmus of the corpus callosum at both the group and individual levels (using an established interhemispheric transfer task). Callosal HRFs were compared to HRFs from cingulate and parietal activation.ResultsExamination of the raw HRF revealed similar overall response characteristics. Finite impulse response modeling confirmed that the WM HRF characteristics were comparable to those of the GM HRF, but had significantly decreased peak response amplitudes.ConclusionsOverall, the results matched a priori expectations of smaller HRF responses in white matter due to the relative drop in cerebral blood flow (CBF) and cerebral blood volume (CBV). Importantly, the findings demonstrate that despite lower CBF and CBV, white matter fMRI activation remained within detectable ranges at 4 T.

Comparing gray and white matter fMRI activation using asymmetric spin echo spiral

Recent developments have shown that it is possible to detect functional magnetic resonance imaging (fMRI) activation in white matter (WM). Enhanced sensitivity to WM fMRI signals has been associated with the asymmetric spin echo (ASE) spiral sequence. The ASE spiral sequence produces three consecutive images that have equal blood-oxygen level-dependent (BOLD) contrast but increasing T2 contrast. The current study evaluated whether ASE spiral sensitivity differed between white and gray matter in the corpus callosum, superior parietal lobes, cingulate gyrus, and inferior frontal lobes. Contrast and noise were compared across the three images for each region. Results showed increasing gains in functional contrast in both white and gray matter as a function of T2 contrast. The third image, with the most T2 contrast, showed the largest increase in contrast, while changes in noise were maintained. The results suggest that ASE spiral increases fMRI sensitivity globally through the addition of T2 weighted contrast.

Investigation of fMRI activation in the internal capsule

BackgroundFunctional magnetic resonance imaging (fMRI) in white matter has long been considered controversial. Recently, this viewpoint has been challenged by an emerging body of evidence demonstrating white matter activation in the corpus callosum. The current study aimed to determine whether white matter activation could be detected outside of the corpus callosum, in the internal capsule. Data were acquired from a 4 T MRI using a specialized asymmetric spin echo spiral sequence. A motor task was selected to elicit activation in the posterior limb of the internal capsule.ResultsWhite matter fMRI activation was examined at the individual and group levels. Analyses revealed that activation was present in the posterior limb of the internal capsule in 80% of participants. These results provide further support for white matter fMRI activation.ConclusionsThe ability to visualize functionally active tracts has strong implications for the basic scientific study of connectivity and the clinical assessment of white matter disease.

Functional mapping in the corpus callosum: A 4 T fMRI study of white matter

IntroductionThe idea of fMRI activation in white matter (WM) is controversial. Our recent work has used two different approaches to investigate whether there is evidence for WM fMRI. The first approach used words and faces to elicit interhemispheric transfer activation in the posterior corpus callosum (Sperry task). The second approach used checkerboard stimuli to elicit similar activation in the anterior corpus callosum (Poffenberger task). Using these different tasks, it has been possible to detect WM activation in different regions. In the current study, we report the results of a critical experiment: demonstrating that callosal activation can be experimentally manipulated within the same set of individuals. MethodsAll subjects completed both the Sperry and Poffenberger tasks. Functional MRI data were acquired at 4T, using an asymmetric spin echo spiral sequence. Data were analyzed with FSL using a model-based approach. Analyses focused on group and individual activations in WM. Results and discussionCorpus callosum activation was elicited for both tasks, with activation varying according to task type. A statistical contrast of the two tasks revealed posterior callosal activation for the Sperry task and anterior callosal activation for the Poffenberger task. The Sperry task showed activation in the isthmus and middle body of the corpus callosum at the group level and in 100% of subjects. The Poffenberger task showed activation in the genu and middle body of the corpus callosum at the group level and in 94% of subjects. The WM activation replicated prior results, with the additional strength of functional mapping within the same group of individuals.

Confirming white matter fMRI activation in the corpus callosum: Co-localization with DTI tractography

Recently, functional magnetic resonance imaging (fMRI) activation has been detected in white matter, despite the widely-held belief that fMRI activation is restricted to gray matter. The objective of the current study was to determine whether the regions of white matter fMRI activation were structurally connected to the functional network in gray matter. To do this, we used fMRI-guided tractography to evaluate whether tracts connecting regions of gray matter fMRI activation were co-localized with white matter fMRI activation. An established interhemispheric transfer task was employed to elicit activation in the corpus callosum. Diffusion tensor imaging (DTI) tractography was used to determine the existence of tracts that connected regions of gray matter fMRI activation to regions of activation in the corpus callosum. Corpus callosum activation was detected in the majority of participants. While there was individual variability in the location of corpus callosum activation, activation was commonly observed in the callosal mid-body, isthmus/splenium, or both. Despite the variability, gray matter fMRI-guided tractography identified tracts that were co-localized with corpus callosum fMRI activation in all instances. In addition, callosal activation had tracts to bilateral gray matter fMRI activation for 7/8 participants. The results confirmed that the activated regions of the corpus callosum were structurally connected to the functional network of gray matter regions involved in the task. These findings are an important step towards establishing the functional significance of white matter fMRI, and provide the foundation for future work combining white matter fMRI and DTI tractography to study brain connectivity.

Co-localization of white matter fMRI activation and tractography in the corpus callosum

Co-localization of white matter fMRI activation and tractography in the corpus callosum

Optimizing the detection of white matter fMRI using asymmetric spin echo spiral

The majority of functional magnetic resonance imaging (fMRI) studies restrict their focus to gray matter regions because this tissue is highly perfused relative to white matter. However, an increasing number of studies are reporting fMRI activation in white matter. The current study had two objectives: 1) to evaluate whether it is possible to detect white matter fMRI activation and 2) to determine whether certain MRI contrast mechanisms are more sensitive to white matter activation (i.e., BOLD contrast- versus T(2)-weighting). Data were acquired from a 4 T MRI using an asymmetric spin echo spiral sequence (ASE spiral). This technique collected three images with equal BOLD contrast weighting and increasing T(2)-weighting. An interhemispheric transfer task was used to elicit activation in the corpus callosum. White matter fMRI activation was examined for the averaged ASE spiral data and for each image separately. Callosal activation was present in all subjects as well as in the group analysis. Analyses revealed that increasing T(2) contrast improved sensitivity as measured by percent signal change. The results suggest that it is possible to detect white matter activation in fMRI and that ASE spiral showed increasing sensitivity to this activation as a function of T(2)-weighting. The findings provide further support for the investigation of white matter fMRI.