Enhanced amygdala-cingulate connectivity associates with better mood in both healthy and depressive individuals after sleep deprivation.

Sleep loss robustly disrupts mood and emotion regulation in healthy individuals but can have a transient antidepressant effect in a subset of patients with depression. The neural mechanisms underlying this paradoxical effect remain unclear. Previous studies suggest that the amygdala and dorsal nexus (DN) play key roles in depressive mood regulation. Here, we used functional MRI to examine associations between amygdala- and DN-related resting-state connectivity alterations and mood changes after one night of total sleep deprivation (TSD) in both healthy adults and patients with major depressive disorder using strictly controlled in-laboratory studies. Behavioral data showed that TSD increased negative mood in healthy participants but reduced depressive symptoms in 43% of patients. Imaging data showed that TSD enhanced both amygdala- and DN-related connectivity in healthy participants. Moreover, enhanced amygdala connectivity to the anterior cingulate cortex (ACC) after TSD associated with better mood in healthy participants and antidepressant effects in depressed patients. These findings support the key role of the amygdala-cingulate circuit in mood regulation in both healthy and depressed populations and suggest that rapid antidepressant treatment may target the enhancement of amygdala-ACC connectivity.

ASLPrep: a platform for processing of arterial spin labeled MRI and quantification of regional brain perfusion.

Arterial spin labeled (ASL) magnetic resonance imaging (MRI) is the primary method for noninvasively measuring regional brain perfusion in humans. We introduce ASLPrep, a suite of software pipelines that ensure the reproducible and generalizable processing of ASL MRI data.

Sleep-stage-dependent alterations in cerebral oxygen metabolism quantified by magnetic resonance.

A key function of sleep is to provide a regular period of reduced brain metabolism, which is critical for maintenance of healthy brain function. The purpose of this work was to quantify the sleep-stage-dependent changes in brain energetics in terms of cerebral metabolic rate of oxygen (CMRO2 ) as a function of sleep stage using quantitative magnetic resonance imaging (MRI) with concurrent electroencephalography (EEG) during sleep in the scanner. Twenty-two young and older subjects with regular sleep hygiene and Pittsburgh Sleep Quality Index (PSQI) in the normal range were recruited for the study. Cerebral blood flow (CBF) and venous oxygen saturation (SvO2 ) were obtained simultaneously at 3 Tesla field strength and 2.7-s temporal resolution during an 80-min time series using OxFlow, an in-house developed imaging sequence. The method yields whole-brain CMRO2 in absolute physiologic units via Fick's Principle. Nineteen subjects yielded evaluable data free of subject motion artifacts. Among these subjects, 10 achieved slow-wave (N3) sleep, 16 achieved N2 sleep, and 19 achieved N1 sleep while undergoing the MRI protocol during scanning. Mean CMRO2 was 98 ± 7(µmol min-1 )/100 g awake, declining progressively toward deepest sleep stage: 94 ± 10.8 (N1), 91 ± 11.4 (N2), and 76 ± 9.0 µmol min-1 /100 g (N3), with each level differing significantly from the wake state. The technology described is able to quantify cerebral oxygen metabolism in absolute physiologic units along with non-REM sleep stage, indicating brain oxygen consumption to be closely associated with depth of sleep, with deeper sleep stages exhibiting progressively lower CMRO2 levels.

QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data.

Diffusion-weighted magnetic resonance imaging (dMRI) is the primary method for noninvasively studying the organization of white matter in the human brain. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing on a diverse set of software suites to capitalize on their complementary strengths, QSIPrep facilitates the implementation of best practices for processing of diffusion images.

In vivo B 1 + enhancement of calf MRI at 7 T via optimized flexible metasurfaces.

PURPOSE: Ultrahigh field (≥7 T) MRI is at the cutting edge of medical imaging, enabling enhanced spatial and spectral resolution as well as enhanced susceptibility contrast. However, transmit ( B 1 + $$ {\mathrm{B}}_1^{+} $$ ) field inhomogeneity due to standing wave effects caused by the shortened RF wavelengths at 7 T is still a challenge to overcome. Novel hardware methods such as dielectric pads have been shown to improve the B 1 + $$ {\mathrm{B}}_1^{+} $$ field inhomogeneity but are currently limited in their corrective effect by the range of high-permittivity materials available and have a fixed shelf life. In this work, an optimized metasurface design is presented that demonstrates in vivo enhancement of the B 1 + $$ {\mathrm{B}}_1^{+} $$ field. METHODS: A prototype metasurface was optimized by an empirical capacitor sweep and by varying the period size. Phantom temperature experiments were performed to evaluate potential metasurface heating effects during scanning. Lastly, in vivo gradient echo images and B 1 + $$ {\mathrm{B}}_1^{+} $$ maps were acquired on five healthy subjects on a 7 T system. Dielectric pads were also used as a comparison throughout the work as a standard comparison. RESULTS: The metasurfaces presented here enhanced the average relative SNR of the gradient echo images by a factor of 2.26 compared to the dielectric pads factor of 1.61. Average B 1 + $$ {\mathrm{B}}_1^{+} $$ values reflected a similar enhancement of 27.6% with the metasurfaces present versus 8.9% with the dielectric pads. CONCLUSION: The results demonstrate that metasurfaces provide superior performance to dielectric padding as shown by B 1 + $$ {\mathrm{B}}_1^{+} $$ maps reflecting their direct effects and resulting enhancements in image SNR at 7 T.

Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications.

Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi-timepoint data can be acquired in the same scan time as single-PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single-PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi-timepoint ASL and provides robust recommendations for acquiring high-quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi-timepoint ASL data. Furthermore, we review the potential clinical applications where multi-timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article.

Automated Quality Evaluation Index for Arterial Spin Labeling Derived Cerebral Blood Flow Maps.

BACKGROUND: Arterial spin labeling (ASL) derived cerebral blood flow (CBF) maps are prone to artifacts and noise that can degrade image quality. PURPOSE: To develop an automated and objective quality evaluation index (QEI) for ASL CBF maps. STUDY TYPE: Retrospective. POPULATION: Data from N = 221 adults, including patients with Alzheimer's disease (AD), Parkinson's disease, and traumatic brain injury. FIELD STRENGTH/SEQUENCE: Pulsed or pseudocontinuous ASL acquired at 3 T using non-background suppressed 2D gradient-echo echoplanar imaging or background suppressed 3D spiral spin-echo readouts. ASSESSMENT: The QEI was developed using N = 101 2D CBF maps rated as unacceptable, poor, average, or excellent by two neuroradiologists and validated by 1) leave-one-out cross validation, 2) assessing if CBF reproducibility in N = 53 cognitively normal adults correlates inversely with QEI, 3) if iterative discarding of low QEI data improves the Cohen's d effect size for CBF differences between preclinical AD (N = 27) and controls (N = 53), 4) comparing the QEI with manual ratings for N = 50 3D CBF maps, and 5) comparing the QEI with another automated quality metric. STATISTICAL TESTS: Inter-rater reliability and manual vs. automated QEI were quantified using Pearson's correlation. P < 0.05 was considered significant. RESULTS: The correlation between QEI and manual ratings (R = 0.83, CI: 0.76-0.88) was similar (P = 0.56) to inter-rater correlation (R = 0.81, CI: 0.73-0.87) for the 2D data. CBF reproducibility correlated negatively (R = -0.74, CI: -0.84 to -0.59) with QEI. The effect size comparing patients and controls improved (R = 0.72, CI: 0.59-0.82) as low QEI data was discarded iteratively. The correlation between QEI and manual ratings (R = 0.86, CI: 0.77-0.92) of 3D ASL was similar (P = 0.09) to inter-rater correlation (R = 0.78, CI: 0.64-0.87). The QEI correlated (R = 0.87, CI: 0.77-0.92) significantly better with manual ratings than did an existing approach (R = 0.54, CI: 0.30-0.72). DATA CONCLUSION: Automated QEI performed similarly to manual ratings and can provide scalable ASL quality control. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Sleep deprivation attenuates neural responses to outcomes from risky decision-making.

Sleep loss impacts a broad range of brain and cognitive functions. However, how sleep deprivation affects risky decision-making remains inconclusive. This study used functional MRI to examine the impact of one night of total sleep deprivation (TSD) on risky decision-making behavior and the underlying brain responses in healthy adults. In this study, we analyzed data from N = 56 participants in a strictly controlled 5-day and 4-night in-laboratory study using a modified Balloon Analogue Risk Task. Participants completed two scan sessions in counter-balanced order, including one scan during rested wakefulness (RW) and another scan after one night of TSD. Results showed no differences in participants' risk-taking propensity and risk-induced activation between RW and TSD. However, participants showed significantly reduced neural activity in the anterior cingulate cortex and bilateral insula for loss outcomes, and in bilateral putamen for win outcomes during TSD compared with RW. Moreover, risk-induced activation in the insula negatively correlated with participants' risk-taking propensity during RW, while no such correlations were observed after TSD. These findings suggest that sleep loss may impact risky decision-making by attenuating neural responses to decision outcomes and impairing brain-behavior associations.

Medial temporal lobe gray matter microstructure in preclinical Alzheimer's disease.

INTRODUCTION: Typical MRI measures of neurodegeneration have limited sensitivity in early disease stages. Diffusion MRI (dMRI) microstructural measures may allow for detection in preclinical stages. METHODS: Participants had dMRI and either beta-amyloid PET or plasma biomarkers of Alzheimer's pathology within 18 months of MRI. Microstructure was measured in portions of the medial temporal lobe (MTL) with high neurofibrillary tangle (NFT) burden based on a previously developed post mortem 3D-map. Regressions examined relationships between microstructure and markers of Alzheimer's pathology in preclinical disease and then across disease stages. RESULTS: There was higher isometric volume fraction in amyloid-positive compared to amyloid-negative cognitively unimpaired individuals in high tangle MTL regions. Similarly, plasma biomarkers and 18F-flortaucipir were associated with microstructural changes in preclinical disease. Additional microstructural effects were seen across disease stages. DISCUSSION: Combining a post mortem atlas of NFT pathology with microstructural measures allows for detection of neurodegeneration in preclinical Alzheimer's disease. Highlights Typical markers of neurodegeneration are not sensitive in preclinical Alzheimer's. dMRI measured microstructure in regions with high NFT. Microstructural changes occur in medial temporal regions in preclinical disease. Microstructural changes occur in other typical Alzheimer's regions in later stages. Combining post mortem pathology atlases with in vivo MRI is a powerful framework.

Mapping hippocampal glutamate in mesial temporal lobe epilepsy with glutamate weighted CEST (GluCEST) imaging.

Temporal lobe epilepsy (TLE) is one of the most common subtypes of focal epilepsy, with mesial temporal sclerosis (MTS) being a common radiological and histopathological finding. Accurate identification of MTS during presurgical evaluation confers an increased chance of good surgical outcome. Here we propose the use of glutamate-weighted chemical exchange saturation transfer (GluCEST) magnetic resonance imaging (MRI) at 7 Tesla for mapping hippocampal glutamate distribution in epilepsy, allowing to differentiate lesional from non-lesional mesial TLE. We demonstrate that a directional asymmetry index, which quantifies the relative difference between GluCEST contrast in hippocampi ipsilateral and contralateral to the seizure onset zone, can differentiate between sclerotic and non-sclerotic hippocampi, even in instances where traditional presurgical MRI assessments did not provide evidence of sclerosis. Overall, our results suggest that hippocampal glutamate mapping through GluCEST imaging is a valuable addition to the presurgical epilepsy evaluation toolbox.

Young versus older subject diffusion magnetic resonance imaging data for virtual white matter lesion tractography.

White matter hyperintensity (WMH) lesions on T2 fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and changes in adjacent normal-appearing white matter can disrupt computerized tract reconstruction and result in inaccurate measures of structural brain connectivity. The virtual lesion approach provides an alternative strategy for estimating structural connectivity changes due to WMH. To assess the impact of using young versus older subject diffusion MRI data for virtual lesion tractography, we leveraged recently available diffusion MRI data from the Human Connectome Project (HCP) Lifespan database. Neuroimaging data from 50 healthy young (39.2 ± 1.6 years) and 46 healthy older (74.2 ± 2.5 years) subjects were obtained from the publicly available HCP-Aging database. Three WMH masks with low, moderate, and high lesion burdens were extracted from the WMH lesion frequency map of locally acquired FLAIR MRI data. Deterministic tractography was conducted to extract streamlines in 21 WM bundles with and without the WMH masks as regions of avoidance in both young and older cohorts. For intact tractography without virtual lesion masks, 7 out of 21 WM pathways showed a significantly lower number of streamlines in older subjects compared to young subjects. A decrease in streamline count with higher native lesion burden was found in corpus callosum, corticostriatal tract, and fornix pathways. Comparable percentages of affected streamlines were obtained in young and older groups with virtual lesion tractography using the three WMH lesion masks of increasing severity. We conclude that using normative diffusion MRI data from young subjects for virtual lesion tractography of WMH is, in most cases, preferable to using age-matched normative data.

In vivo assessment of ß-hydroxybutyrate metabolism in mouse brain using deuterium (2 H) MRS.

PURPOSE: To monitor the metabolic turnover of ß-hydroxybutyrate (BHB) oxidation using 2 H-MRS in conjunction with intravenous administration of 2 H labeled BHB. METHODS: Nine-month-old mice were infused with [3,4,4,4]-2 H4 -BHB (d4 -BHB; 3.11 g/kg) through the tail vein using a bolus variable infusion rate for a period of 90 min. The labeling of downstream cerebral metabolites from the oxidative metabolism of d4 -BHB was monitored using 2 H-MRS spectra acquired with a home-built 2 H surface coil on a 9.4T preclinical MR scanner with a temporal resolution of 6.25 min. An exponential model was fit to the BHB and glutamate/glutamine (Glx) turnover curves to determine rate constants of metabolite turnover and to aid in the visualization of metabolite time courses. RESULTS: Deuterium label was incorporated into Glx from BHB metabolism through the tricarboxylic acid (TCA) cycle, with an increase in the level of [4,4]-2 H2 -Glx (d2 -Glx) over time and reaching a quasi-steady state concentration of ∼0.6 ± 0.1 mM following 30 min of infusion. Complete oxidative metabolic breakdown of d4 -BHB also resulted in the formation of semi-heavy water (HDO), with a four-fold (10.1 to ∼42.1 ± 7.3 mM) linear (R2  = 0.998) increase in its concentration by the end of infusion. The rate constant of Glx turnover from d4 -BHB metabolism was determined to be 0.034 ± 0.004 min-1 . CONCLUSION: 2 H-MRS can be used to monitor the cerebral metabolism of BHB with its deuterated form by measuring the downstream labeling of Glx. The integration of 2 H-MRS with deuterated BHB substrate provides an alternative and clinically promising MRS tool to detect neurometabolic fluxes in healthy and disease conditions.

B 1 + $$ {\mathrm{B}}_1

PURPOSE: Nuclear Overhauser effect magnetization transfer ratio (NOEMTR ) is a technique used to investigate brain lipids and macromolecules in greater detail than other techniques and benefits from increased contrast at 7 T. However, this contrast can become degraded because of B 1 + $$ {\mathrm{B}}_1^{+} $$ inhomogeneities present at ultra-high field strengths. High-permittivity dielectric pads (DP) have been used to correct for these inhomogeneities via displacement currents generating secondary magnetic fields. The purpose of this work is to demonstrate that dielectric pads can be used to mitigate B 1 + $$ {\mathrm{B}}_1^{+} $$ inhomogeneities and improve NOEMTR contrast in the temporal lobes at 7 T. METHODS: Partial 3D NOEMTR contrast images and whole brain B 1 + $$ {\mathrm{B}}_1^{+} $$ field maps were acquired on a 7 T MRI across six healthy subjects. Calcium titanate DP, having a relative permittivity of 110, was placed next to the subject's head near the temporal lobes. Pad corrected NOEMTR images had a separate postprocessing linear correction applied. RESULTS: DP provided supplemental B 1 + $$ {\mathrm{B}}_1^{+} $$ to the temporal lobes while also reducing the B 1 + $$ {\mathrm{B}}_1^{+} $$ magnitude across the posterior and superior regions of the brain. This resulted in a statistically significant increase in NOEMTR contrast in substructures of the temporal lobes both with and without linear correction. The padding also produced a convergence in NOEMTR contrast toward approximately equal mean values. CONCLUSION: NOEMTR images showed significant improvement in temporal lobe contrast when DP were used, which resulted from an increase in B 1 + $$ {\mathrm{B}}_1^{+} $$ homogeneity across the entire brain slab. DP-derived improvements in NOEMTR are expected to increase the robustness of the brain substructural measures both in healthy and pathological conditions.

Current state and guidance on arterial spin labeling perfusion MRI in clinical neuroimaging.

This article focuses on clinical applications of arterial spin labeling (ASL) and is part of a wider effort from the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group to update and expand on the recommendations provided in the 2015 ASL consensus paper. Although the 2015 consensus paper provided general guidelines for clinical applications of ASL MRI, there was a lack of guidance on disease-specific parameters. Since that time, the clinical availability and clinical demand for ASL MRI has increased. This position paper provides guidance on using ASL in specific clinical scenarios, including acute ischemic stroke and steno-occlusive disease, arteriovenous malformations and fistulas, brain tumors, neurodegenerative disease, seizures/epilepsy, and pediatric neuroradiology applications, focusing on disease-specific considerations for sequence optimization and interpretation. We present several neuroradiological applications in which ASL provides unique information essential for making the diagnosis. This guidance is intended for anyone interested in using ASL in a routine clinical setting (i.e., on a single-subject basis rather than in cohort studies) building on the previous ASL consensus review.

Associations of phosphorylated tau pathology with whole-hemisphere ex vivo morphometry in 7 tesla MRI.

INTRODUCTION: Neurodegenerative disorders are associated with different pathologies that often co-occur but cannot be measured specifically with in vivo methods. METHODS: Thirty-three brain hemispheres from donors with an Alzheimer's disease (AD) spectrum diagnosis underwent T2-weighted magnetic resonance imaging (MRI). Gray matter thickness was paired with histopathology from the closest anatomic region in the contralateral hemisphere. RESULTS: Partial Spearman correlation of phosphorylated tau and cortical thickness with TAR DNA-binding protein 43 (TDP-43) and α-synuclein scores, age, sex, and postmortem interval as covariates showed significant relationships in entorhinal and primary visual cortices, temporal pole, and insular and posterior cingulate gyri. Linear models including Braak stages, TDP-43 and α-synuclein scores, age, sex, and postmortem interval showed significant correlation between Braak stage and thickness in the parahippocampal gyrus, entorhinal cortex, and Broadman area 35. CONCLUSION: We demonstrated an association of measures of AD pathology with tissue loss in several AD regions despite a limited range of pathology in these cases. HIGHLIGHTS: Neurodegenerative disorders are associated with co-occurring pathologies that cannot be measured specifically with in vivo methods. Identification of the topographic patterns of these pathologies in structural magnetic resonance imaging (MRI) may provide probabilistic biomarkers. We demonstrated the correlation of the specific patterns of tissue loss from ex vivo brain MRI with underlying pathologies detected in postmortem brain hemispheres in patients with Alzheimer's disease (AD) spectrum disorders. The results provide insight into the interpretation of in vivo structural MRI studies in patients with AD spectrum disorders.

Integrating 1H MRS and deuterium labeled glucose for mapping the dynamics of neural metabolism in humans.

In the technique presented here, dubbed 'qMRS', we quantify the change in 1H MRS signal following administration of 2H-labeled glucose. As in recent human DMRS studies, we administer [6,6'-2H2]-glucose orally to healthy subjects. Since 2H is not detectable by 1H MRS, the transfer of the 2H label from glucose to a downstream metabolite leads to a reduction in the corresponding 1H MRS resonance of the metabolite, even if the total concentration of both isoforms remains constant. Moreover, introduction of the deuterium label alters the splitting pattern of the proton resonances, making indirect detection of the deuterated forms- as well as the direct detection of the decrease in unlabeled form- possible even without a 2H coil. Because qMRS requires only standard 1H MRS acquisition methods, it can be performed using commonly implemented single voxel spectroscopy (SVS) and chemical shift imaging (CSI) sequences. In this work, we implement qMRS in semi-LASER based CSI, generating dynamic maps arising from the fitted spectra, and demonstrating the feasibility of using qMRS and qCSI to monitor dynamic metabolism in the human brain using a 7T scanner with no auxiliary hardware.

Cerebellum anatomy predicts individual risk-taking behavior and risk tolerance.

Human risk tolerance is highly idiosyncratic and individuals often show distinctive preferences when faced with similar risky situations. However, the neural underpinnings of individual differences in risk-taking remain unclear. Here we combined structural and perfusion MRI and examined the associations between brain anatomy and individual risk-taking behavior/risk tolerance in a sample of 115 healthy participants during the Balloon Analogue Risk Task, a well-established sequential risky decision paradigm. Both whole brain and region-of-interest analyses showed that the left cerebellum gray matter volume (GMV) has a strong association with individual risk-taking behavior and risk tolerance, outperforming the previously reported associations with the amygdala and right posterior parietal cortex (PPC) GMV. Left cerebellum GMV also accounted for risk tolerance and risk-taking behavior changes with aging. However, regional cerebral blood flow (CBF) provided no additional predictive power. These findings suggest a novel cerebellar anatomical contribution to individual differences in risk tolerance. Further studies are necessary to elucidate the underestimated important role of cerebellum in risk-taking.

Spatially-enhanced clusterwise inference for testing and localizing intermodal correspondence.

With the increasing availability of neuroimaging data from multiple modalities-each providing a different lens through which to study brain structure or function-new techniques for comparing, integrating, and interpreting information within and across modalities have emerged. Recent developments include hypothesis tests of associations between neuroimaging modalities, which can be used to determine the statistical significance of intermodal associations either throughout the entire brain or within anatomical subregions or functional networks. While these methods provide a crucial foundation for inference on intermodal relationships, they cannot be used to answer questions about where in the brain these associations are most pronounced. In this paper, we introduce a new method, called CLEAN-R, that can be used both to test intermodal correspondence throughout the brain and also to localize this correspondence. Our method involves first adjusting for the underlying spatial autocorrelation structure within each modality before aggregating information within small clusters to construct a map of enhanced test statistics. Using structural and functional magnetic resonance imaging data from a subsample of children and adolescents from the Philadelphia Neurodevelopmental Cohort, we conduct simulations and data analyses where we illustrate the high statistical power and nominal type I error levels of our method. By constructing an interpretable map of group-level correspondence using spatially-enhanced test statistics, our method offers insights beyond those provided by earlier methods.

Associations of white matter hyperintensities with networks of gray matter blood flow and volume in midlife adults: A coronary artery risk development in young adults magnetic resonance imaging substudy.

White matter hyperintensities (WMHs) are emblematic of cerebral small vessel disease, yet effects on the brain have not been well characterized at midlife. Here, we investigated whether WMH volume is associated with brain network alterations in midlife adults. Two hundred and fifty-four participants from the Coronary Artery Risk Development in Young Adults study were selected and stratified by WMH burden into Lo-WMH (mean age = 50 ± 3.5 years) and Hi-WMH (mean age = 51 ± 3.7 years) groups of equal size. We constructed group-level covariance networks based on cerebral blood flow (CBF) and gray matter volume (GMV) maps across 74 gray matter regions. Through consensus clustering, we found that both CBF and GMV covariance networks partitioned into modules that were largely consistent between groups. Next, CBF and GMV covariance network topologies were compared between Lo- and Hi-WMH groups at global (clustering coefficient, characteristic path length, global efficiency) and regional (degree, betweenness centrality, local efficiency) levels. At the global level, there were no between-group differences in either CBF or GMV covariance networks. In contrast, we found between-group differences in the regional degree, betweenness centrality, and local efficiency of several brain regions in both CBF and GMV covariance networks. Overall, CBF and GMV covariance analyses provide evidence that WMH-related network alterations are present at midlife.

Voxel-wise intermodal coupling analysis of two or more modalities using local covariance decomposition.

When individual subjects are imaged with multiple modalities, biological information is present not only within each modality, but also between modalities - that is, in how modalities covary at the voxel level. Previous studies have shown that local covariance structures between modalities, or intermodal coupling (IMCo), can be summarized for two modalities, and that two-modality IMCo reveals otherwise undiscovered patterns in neurodevelopment and certain diseases. However, previous IMCo methods are based on the slopes of local weighted linear regression lines, which are inherently asymmetric and limited to the two-modality setting. Here, we present a generalization of IMCo estimation which uses local covariance decompositions to define a symmetric, voxel-wise coupling coefficient that is valid for two or more modalities. We use this method to study coupling between cerebral blood flow, amplitude of low frequency fluctuations, and local connectivity in 803 subjects ages 8 through 22. We demonstrate that coupling is spatially heterogeneous, varies with respect to age and sex in neurodevelopment, and reveals patterns that are not present in individual modalities. As availability of multi-modal data continues to increase, principal-component-based IMCo (pIMCo) offers a powerful approach for summarizing relationships between multiple aspects of brain structure and function. An R package for estimating pIMCo is available at: https://github.com/hufengling/pIMCo.