Sex, gender diversity, and brain structure in early adolescence.

There remains little consensus about the relationship between sex and brain structure, particularly in early adolescence. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest-many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years old (N = 7195). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. Additional sensitivity analyses found that male versus female differences in gyrification and white matter were largely accounted for by total brain volume, rather than sex per se. The model with sex, but not gender diversity, was the best-fitting model in 60.1% of gray matter regions and 61.9% of white matter regions after adjusting for brain volume. The proportion of variance accounted for by sex was negligible to small in all cases. While models including felt-gender explained a greater amount of variance in a few regions, the felt-gender score alone was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

Heart rate and breathing effects on attention and memory (HeartBEAM): study protocol for a randomized controlled trial in older adults.

BACKGROUND: In healthy people, the "fight-or-flight" sympathetic system is counterbalanced by the "rest-and-digest" parasympathetic system. As we grow older, the parasympathetic system declines as the sympathetic system becomes hyperactive. In our prior heart rate variability biofeedback and emotion regulation (HRV-ER) clinical trial, we found that increasing parasympathetic activity through daily practice of slow-paced breathing significantly decreased plasma amyloid-ß (Aß) in healthy younger and older adults. In healthy adults, higher plasma Aß is associated with greater risk of Alzheimer's disease (AD). Our primary goal of this trial is to reproduce and extend our initial findings regarding effects of slow-paced breathing on Aß. Our secondary objectives are to examine the effects of daily slow-paced breathing on brain structure and the rate of learning. METHODS: Adults aged 50-70 have been randomized to practice one of two breathing protocols twice daily for 9 weeks: (1) "slow-paced breathing condition" involving daily cognitive training followed by slow-paced breathing designed to maximize heart rate oscillations or (2) "random-paced breathing condition" involving daily cognitive training followed by random-paced breathing to avoid increasing heart rate oscillations. The primary outcomes are plasma Aß40 and Aß42 levels and plasma Aß42/40 ratio. The secondary outcomes are brain perivascular space volume, hippocampal volume, and learning rates measured by cognitive training performance. Other pre-registered outcomes include plasma pTau-181/tTau ratio and urine Aß42. Recruitment began in January 2023. Interventions are ongoing and will be completed by the end of 2023. DISCUSSION: Our HRV-ER trial was groundbreaking in demonstrating that a behavioral intervention can reduce plasma Aß levels relative to a randomized control group. We aim to reproduce these findings while testing effects on brain clearance pathways and cognition. TRIAL REGISTRATION: ClinicalTrials.gov NCT05602220. Registered on January 12, 2023.

Increased perivascular space volume in white matter and basal ganglia is associated with cognition in Parkinson's Disease.

Perivascular spaces (PVS), fluid-filled compartments surrounding brain vasculature, are an essential component of the glymphatic system responsible for transport of waste and nutrients. Glymphatic system impairment may underlie cognitive deficits in Parkinson's disease (PD). Studies have focused on the role of basal ganglia PVS with cognition in PD, but the role of white matter PVS is unknown. This study examined the relationship of white matter and basal ganglia PVS with domain-specific and global cognition in individuals with PD. Fifty individuals with PD underwent 3T T1w magnetic resonance imaging (MRI) to determine PVS volume fraction, defined as PVS volume normalized to total regional volume, within (i) centrum semiovale, (ii) prefrontal white matter (medial orbitofrontal, rostral middle frontal, superior frontal), and (iii) basal ganglia. A neuropsychological battery included assessment of global cognitive function (Montreal Cognitive Assessment, and global cognitive composite score), and cognitive-specific domains (executive function, memory, visuospatial function, attention, and language). Higher white matter rostral middle frontal PVS was associated with lower scores in both global cognitive and visuospatial function. In the basal ganglia higher PVS was associated with lower scores for memory with a trend towards lower global cognitive composite score. While previous reports have shown that greater amount of PVS in the basal ganglia is associated with decline in global cognition in PD, our findings suggest that increased white matter PVS volume may also underlie changes in cognition.

Effects of sleep on brain perivascular space in a cognitively healthy population.

The magnetic resonance imaging (MRI) visible perivascular space (PVS) reportedly clears amyloid-ß and metabolic waste during sleep. Previous studies reported an association between sleep and the PVS in small vessel disease, traumatic brain injury, and Alzheimer's disease. However, this relationship in a healthy cohort is still unclear. Here, we used the Human Connectome Project Aging dataset to analyze the relationship between sleep and the PVS in cognitively healthy adults across the aging continuum. We measured sleep parameters using the self-reported Pittsburgh Sleep Quality Index questionnaire. We found that older adults who had better sleep quality and sleep efficiency presented with a larger PVS volume fraction in the basal ganglia (BG). However, sleep measures were not associated with PVS volume fraction in the centrum semiovale (CSO). In addition, we found that body mass index (BMI) influenced the BG-PVS across middle-aged and older participants. In the entire cognitively healthy cohort, the effect of sleep quality on PVS volume fraction was mediated by BMI. However, BMI did not influence this effect in the older cohort. Furthermore, there are significant differences in PVS volume fraction across racial/ethnic cohorts. In summary, the effect of sleep on the PVS volume alteration was different in the middle-aged adults and older adults.

Sex, gender diversity, and brain structure in children ages 9 to 11 years old.

There remains little consensus about the relationship between sex and brain structure, particularly in childhood. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest - many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years-old (N=7693). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. The model with sex, but not gender diversity, was the best-fitting model in 75% of gray matter regions and 79% of white matter regions examined. The addition of gender to the sex model explained significantly more variance than sex alone with regard to bilateral cerebellum volume, left precentral cortical thickness, as well as gyrification in the right superior frontal gyrus, right parahippocampal gyrus, and several regions in the left parietal lobe. For mean diffusivity in the left uncinate fasciculus, the model with sex, gender, and their interaction captured the most variance. Nonetheless, the magnitude of variance accounted for by sex was small in all cases and felt-gender score was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years-old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

Perivascular spaces in Alzheimer's disease are associated with inflammatory, stress-related, and hypertension biomarkers.

Perivascular spaces (PVS) are fluid-filled spaces surrounding the brain vasculature. Literature suggests that PVS may play a significant role in aging and neurological disorders, including Alzheimer's disease (AD). Cortisol, a stress hormone, has been implicated in the development and progression of AD. Hypertension, a common condition in older adults, has been found to be a risk factor for AD. Hypertension may contribute to PVS enlargement, impairing the clearance of waste products from the brain and promoting neuroinflammation. This study aims to understand the potential interactions between PVS, cortisol, hypertension, and inflammation in the context of cognitive impairment. Using MRI scans acquired at 1.5T, PVS were quantified in a cohort of 465 individuals with cognitive impairment. PVS was calculated in the basal ganglia and centrum semiovale using an automated segmentation approach. Levels of cortisol and angiotensin-converting enzyme (ACE) (an indicator of hypertension) were measured from plasma. Inflammatory biomarkers, such as cytokines and matrix metalloproteinases, were analyzed using advanced laboratory techniques. Main effect and interaction analyses were performed to examine the associations between PVS severity, cortisol levels, hypertension, and inflammatory biomarkers. In the centrum semiovale, higher levels of inflammation reduced cortisol associations with PVS volume fraction. For ACE, an inverse association with PVS was seen only when interacting with TNFr2 (a transmembrane receptor of TNF). There was also a significant inverse main effect of TNFr2. In the PVS basal ganglia, a significant positive association was found with TRAIL (a TNF receptor inducing apoptosis). These findings show for the first time the intricate relationships between PVS structure and the levels of stress-related, hypertension, and inflammatory biomarkers. This research could potentially guide future studies regarding the underlying mechanisms of AD pathogenesis and the potential development of novel therapeutic strategies targeting these inflammation factors.

Brain perivascular space imaging across the human lifespan.

Enlarged perivascular spaces (PVS) are considered a biomarker for vascular pathology and are observed in normal aging and neurological conditions; however, research on the role of PVS in health and disease are hindered by the lack of knowledge regarding the normative time course of PVS alterations with age. To this end, we characterized the influence of age, sex and cognitive performance on PVS anatomical characteristics in a large cross-sectional cohort (∼1400) of healthy subjects between 8 and 90 years of age using multimodal structural MRI data. Our results show age is associated with wider and more numerous MRI-visible PVS over the course of the lifetime with spatially-varying patterns of PVS enlargement trajectories. In particular, regions with low PVS volume fraction in childhood are associated with rapid age-related PVS enlargement (e.g., temporal regions), while regions with high PVS volume fraction in childhood are associated with minimal age-related PVS alterations (e.g., limbic regions). PVS burden was significantly elevated in males compared to females with differing morphological time courses with age. Together, these findings contribute to our understanding of perivascular physiology across the healthy lifespan and provide a normative reference for the spatial distribution of PVS enlargement patterns to which pathological alterations can be compared.

The association between white matter hyperintensities and amyloid and tau deposition.

White matter hyperintensities (WMHs) frequently occur in Alzheimer's Disease (AD) and have a contribution from ischemia, though their relationship with ß-amyloid and cardiovascular risk factors (CVRFs) is not completely understood. We used AT classification to categorize individuals based on their ß-amyloid and tau pathologies, then assessed the effects of ß-amyloid and tau on WMH volume and number. We then determined regions in which ß-amyloid and WMH accumulation were related. Last, we analyzed the effects of various CVRFs on WMHs. As secondary analyses, we observed effects of age and sex differences, atrophy, cognitive scores, and APOE genotype. PET, MRI, FLAIR, demographic, and cardiovascular health data was collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI-3) (N = 287, 48 % male). Participants were categorized as A + and T + if their Florbetapir SUVR and Flortaucipir SUVR were above 0.79 and 1.25, respectively. WMHs were mapped on MRI using a deep convolutional neural network (Sepehrband et al., 2020). CVRF scores were based on history of hypertension, systolic and diastolic blood pressure, pulse rate, respiration rate, BMI, and a cumulative score with 6 being the maximum score. Regression models and Pearson correlations were used to test associations and correlations between variables, respectively, with age, sex, years of education, and scanner manufacturer as covariates of no interest. WMH volume percent was significantly associated with global ß-amyloid (r = 0.28, p < 0.001), but not tau (r = 0.05, p = 0.25). WMH volume percent was higher in individuals with either A + or T + pathology compared to controls, particularly within in the A+/T + group (p = 0.007, Cohen's d = 0.4, t = -2.5). Individual CVRFs nor cumulative CVRF scores were associated with increased WMH volume. Finally, the regions where ß-amyloid and WMH count were most positively associated were the middle temporal region in the right hemisphere (r = 0.18, p = 0.002) and the fusiform region in the left hemisphere (r = 0.017, p = 0.005). ß-amyloid and WMH have a clear association, though the mechanism facilitating this association is still not fully understood. The associations found between ß-amyloid and WMH burden emphasizes the relationship between ß-amyloid and vascular lesion formation while factors like CVRFs, age, and sex affect AD development through various mechanisms. These findings highlight potential causes and mechanisms of AD as targets for future preventions and treatments. Going forward, a larger emphasis may be placed on ß-amyloid's vascular effects and the implications of impaired brain clearance in AD.

Weakly supervised perivascular spaces segmentation with salient guidance of Frangi filter.

PURPOSE: To develop a weakly supervised 3D perivascular spaces (PVS) segmentation model that combines the filter-based image processing algorithm and the convolutional neural network. METHODS: We present a weakly supervised learning method for PVS segmentation by combing a rule-based image processing approach Frangi filter with a canonical deep learning algorithm Unet using conditional random field theory. The weighted cross entropy loss function and the training patch selection were implemented for the optimization and to alleviate the class imbalance issue. The performance of the model was evaluated on the Human Connectome Project data. RESULTS: The proposed method increases the true positive rate compared to the rule-based method and reduces the false positive rate by 36% in the weakly supervised training experiment and 39.4% in the supervised training experiment compared to Unet, which results in superior overall performance. In addition, by training the model on manually quality controlled and annotated data which includes the subjects with the presence of white matter hyperintensities, the proposed method differentiates between PVS and white matter hyperintensities, which reduces the false positive rate by 78.5% compared to weakly supervised trained model. CONCLUSIONS: Combing the filter-based image processing algorithm and the convolutional neural network algorithm could improve the model's segmentation accuracy, while reducing the training dependence on the large scale annotated PVS mask data by the trained physician. Compared to the filter-based image processing algorithm, the data driven PVS segmentation model using quality-controlled data as the training target could differentiate the white matter hyperintensity from PVS resulting low false positive rate.

Sight restoration reverses blindness-induced cross-modal functional connectivity changes between the visual and somatosensory cortex at rest.

Resting-state functional connectivity (rsFC) has been used to assess the effect of vision loss on brain plasticity. With the emergence of vision restoration therapies, rsFC analysis provides a means to assess the functional changes following sight restoration. Our study demonstrates a partial reversal of blindness-induced rsFC changes in Argus II retinal prosthesis patients compared to those with severe retinitis pigmentosa (RP). For 10 healthy control (HC), 10 RP, and 7 Argus II subjects, four runs of resting-state functional magnetic resonance imaging (fMRI) per subject were included in our study. rsFC maps were created with the primary visual cortex (V1) as the seed. The rsFC group contrast maps for RP > HC, Argus II > RP, and Argus II > HC revealed regions in the post-central gyrus (PostCG) with significant reduction, significant enhancement, and no significant changes in rsFC to V1 for the three contrasts, respectively. These findings were also confirmed by the respective V1-PostCG ROI-ROI analyses between test groups. Finally, the extent of significant rsFC to V1 in the PostCG region was 5,961 in HC, 0 in RP, and 842 mm3 in Argus II groups. Our results showed a reduction of visual-somatosensory rsFC following blindness, consistent with previous findings. This connectivity was enhanced following sight recovery with Argus II, representing a reversal of changes in cross-modal functional plasticity as manifested during rest, despite the rudimentary vision obtained by Argus II patients. Future investigation with a larger number of test subjects into this rare condition can further unveil the profound ability of our brain to reorganize in response to vision restoration.

Magnetic resonance spectroscopy shows associations between neurometabolite levels and perivascular space volume in Parkinson's disease: a pilot and feasibility study.

OBJECTIVE: Higher volume fraction of perivascular space (PVS) has recently been reported in Parkinson's disease (PD) and related disorders. Both elevated PVS and altered levels of neurometabolites, assayed by proton magnetic resonance spectroscopy (MRS), are suspected indicators of neuroinflammation, but no published reports have concurrently examined PVS and MRS neurometabolites. METHODS: In an exploratory pilot study, we acquired multivoxel 3-T MRS using a semi-Localization by Adiabatic SElective Refocusing (sLASER) pulse-sequence (repetition time/echo time = 2810/60 ms, voxels 10 × 10 × 10 mm3) from a 2D slab sampling bilateral frontal white matter (FWM) and anterior middle cingulate cortex (aMCC). PVS maps obtained from high-resolution (0.8 × 0.8 × 0.8 mm3) T1-weighted MRI were co-registered with MRS. In each MRS voxel, PVS volume and neurometabolite levels were measured. RESULTS: Linear regression accounting for age, sex, and BMI found greater PVS volume for higher levels of choline-containing compounds (Cho; P = 0.047) in FWM and lower PVS volume for higher levels of N-acetyl compounds (NAA; P = 0.012) in aMCC. Since (putatively) higher Cho is associated with inflammation while NAA has anti-inflammatory properties, these observations add to evidence that higher PVS load is a sign of inflammation. Additionally, lower Montreal Cognitive Assessment scores were associated with lower NAA in aMCC (P = 0.002), suggesting that local neuronal dysfunction and inflammation contribute to cognitive impairment in PD. CONCLUSION: These exploratory findings indicate that co-analysis of PVS and MRS is feasible and may help elucidate the cellular and metabolic substrates of glymphatic and inflammatory processes in PD.

Imaging perivascular space structure and function using brain MRI.

In this article, we provide an overview of current neuroimaging methods for studying perivascular spaces (PVS) in humans using brain MRI. In recent years, an increasing number of studies highlighted the role of PVS in cerebrospinal/interstial fluid circulation and clearance of cerebral waste products and their association with neurological diseases. Novel strategies and techniques have been introduced to improve the quantification of PVS and to investigate their function and morphological features in physiological and pathological conditions. After a brief introduction on the anatomy and physiology of PVS, we examine the latest technological developments to quantitatively analyze the structure and function of PVS in humans with MRI. We describe the applications, advantages, and limitations of these methods, providing guidance and suggestions on the acquisition protocols and analysis techniques that can be applied to study PVS in vivo. Finally, we review the human neuroimaging studies on PVS across the normative lifespan and in the context of neurological disorders.

Volumetric distribution of perivascular space in relation to mild cognitive impairment.

Vascular contributions to early cognitive decline are increasingly recognized, prompting further investigation into the nature of related changes in perivascular spaces (PVS). Using magnetic resonance imaging, we show that, compared to a cognitively normal sample, individuals with early cognitive dysfunction have altered PVS presence and distribution, irrespective of Amyloid-ß. Surprisingly, we noted lower PVS presence in the anterosuperior medial temporal lobe (asMTL) (1.29 times lower PVS volume fraction in cognitively impaired individuals, p < 0.0001), which was associated with entorhinal neurofibrillary tau tangle deposition (beta (standard error) = -0.98 (0.4); p = 0.014), one of the hallmarks of early Alzheimer's disease pathology. We also observed higher PVS volume fraction in centrum semi-ovale of the white matter, but only in female participants (1.47 times higher PVS volume fraction in cognitively impaired individuals, p = 0.0011). We also observed PVS changes in participants with history of hypertension (higher in the white matter and lower in the asMTL). Our results suggest that anatomically specific alteration of the PVS is an early neuroimaging feature of cognitive impairment in aging adults, which is differentially manifested in female.

Temporal embedding and spatiotemporal feature selection boost multi-voxel pattern analysis decoding accuracy.

BACKGROUND: In fMRI decoding, temporal embedding of spatial features of the brain allows the incorporation of brain activity dynamics into the multivariate pattern classification process, and provides enriched information about stimulus-specific response patterns and potentially improved prediction accuracy. NEW METHOD: This study investigates the possibility of enhancing the classification performance by exploring temporal embedding, to identify the optimum combination of spatiotemporal features based on their classification performance. We investigated the importance of spatiotemporal feature selection using a slow event-related design adapted from the classic Haxby study (Haxby et al., 2001). Data were collected using a multiband fMRI sequence with temporal resolution of 0.568 s. COMPARISON WITH EXISTING METHODS: A wide range of spatiotemporal observations were created as various combinations of spatiotemporal features. Using both random forest, and support vector machine, classifiers prediction accuracies for these combinations were then compared with the single spatial multivariate pattern approach that uses only a single temporal observation. RESULTS: Our findings showed that, on average, spatiotemporal feature selection improved prediction accuracy. Moreover, the random forest algorithm outperformed the support vector machine and benefitted from temporal information to a greater extent. CONCLUSIONS: As expected, the most influential temporal durations were found to be around the peak of the hemodynamic response function, a few seconds after the stimuli onset until -4 s after the peak of the hemodynamic response function. The superiority of spatiotemporal feature selection over single time-point spatial approaches invites future work to design optimal approaches that incorporate spatiotemporal dependencies into feature selection for decoding.

Image processing approaches to enhance perivascular space visibility and quantification using MRI.

Imaging the perivascular spaces (PVS), also known as Virchow-Robin space, has significant clinical value, but there remains a need for neuroimaging techniques to improve mapping and quantification of the PVS. Current technique for PVS evaluation is a scoring system based on visual reading of visible PVS in regions of interest, and often limited to large caliber PVS. Enhancing the visibility of the PVS could support medical diagnosis and enable novel neuroscientific investigations. Increasing the MRI resolution is one approach to enhance the visibility of PVS but is limited by acquisition time and physical constraints. Alternatively, image processing approaches can be utilized to improve the contrast ratio between PVS and surrounding tissue. Here we combine T1- and T2-weighted images to enhance PVS contrast, intensifying the visibility of PVS. The Enhanced PVS Contrast (EPC) was achieved by combining T1- and T2-weighted images that were adaptively filtered to remove non-structured high-frequency spatial noise. EPC was evaluated on healthy young adults by presenting them to two expert readers and also through automated quantification. We found that EPC improves the conspicuity of the PVS and aid resolving a larger number of PVS. We also present a highly reliable automated PVS quantification approach, which was optimized using expert readings.

Nonparenchymal fluid is the source of increased mean diffusivity in preclinical Alzheimer's disease.

INTRODUCTION: Although increased mean diffusivity of the white matter has been repeatedly linked to Alzheimer's disease pathology, the underlying mechanism is not known. METHODS: Here, we used ADNI-3 multishell diffusion magnetic resonance imaging data to separate the diffusion signal of the parenchyma from less hindered fluid pools within the white matter such as perivascular space fluid and fluid-filled cavities. RESULTS: We found that the source of the pathological increase of the mean diffusivity is the increased nonparenchymal fluid, often found in lacunes and perivascular spaces. In this cohort, the cognitive decline was significantly associated with the fluid increase and not with the microstructural changes of the white matter parenchyma itself. The white matter fluid increase was dominantly observed in the sagittal stratum and anterior thalamic radiation. DISCUSSION: These findings are positive steps toward understanding the pathophysiology of white matter alteration and its role in the cognitive decline.

Perivascular space fluid contributes to diffusion tensor imaging changes in white matter.

Diffusion tensor imaging (DTI) has been extensively used to map changes in brain tissue related to neurological disorders. Among the most widespread DTI findings are increased mean diffusivity and decreased fractional anisotropy of white matter tissue in neurodegenerative diseases. Here we utilize multi-shell diffusion imaging to separate diffusion signal of the brain parenchyma from non-parenchymal fluid within the white matter. We show that unincorporated anisotropic water in perivascular space (PVS) significantly, and systematically, biases DTI measures, casting new light on the biological validity of many previously reported findings. Despite the challenge this poses for interpreting these past findings, our results suggest that multi-shell diffusion MRI provides a new opportunity for incorporating the PVS contribution, ultimately strengthening the clinical and scientific value of diffusion MRI.

Lateralization of Temporal Lobe Epilepsy Based on Resting-State Functional Magnetic Resonance Imaging and Machine Learning.

Lateralization of temporal lobe epilepsy (TLE) is critical for successful outcome of surgery to relieve seizures. TLE affects brain regions beyond the temporal lobes and has been associated with aberrant brain networks, based on evidence from functional magnetic resonance imaging. We present here a machine learning-based method for determining the laterality of TLE, using features extracted from resting-state functional connectivity of the brain. A comprehensive feature space was constructed to include network properties within local brain regions, between brain regions, and across the whole network. Feature selection was performed based on random forest and a support vector machine was employed to train a linear model to predict the laterality of TLE on unseen patients. A leave-one-patient-out cross validation was carried out on 12 patients and a prediction accuracy of 83% was achieved. The importance of selected features was analyzed to demonstrate the contribution of resting-state connectivity attributes at voxel, region, and network levels to TLE lateralization.

The relation of structural integrity and task-related functional connectivity in the aging brain.

The relations among structural integrity, functional connectivity (FC), and cognitive performance in the aging brain are still understudied. Here, we used multimodal and multivariate approaches to specifically examine age-related changes in task-related FC, gray-matter volumetrics, white-matter integrity, and performance. Our results are two-fold, showing (i) age-related differences in FC of the working memory network and (ii) age-related recruitment of a compensatory network associated with better accuracy on the task. Increased connectivity in the compensatory network correlates positively with preserved white-matter integrity in bilateral frontoparietal tracks and with larger gray-matter volume of right inferior parietal lobule. These findings demonstrate the importance of structural integrity and FC in working memory performance associated with healthy aging.

lop-DWI: A Novel Scheme for Pre-Processing of Diffusion-Weighted Images in the Gradient Direction Domain.

We describe and evaluate a pre-processing method based on a periodic spiral sampling of diffusion-gradient directions for high angular resolution diffusion magnetic resonance imaging. Our pre-processing method incorporates prior knowledge about the acquired diffusion-weighted signal, facilitating noise reduction. Periodic spiral sampling of gradient direction encodings results in an acquired signal in each voxel that is pseudo-periodic with characteristics that allow separation of low-frequency signal from high frequency noise. Consequently, it enhances local reconstruction of the orientation distribution function used to define fiber tracks in the brain. Denoising with periodic spiral sampling was tested using synthetic data and in vivo human brain images. The level of improvement in signal-to-noise ratio and in the accuracy of local reconstruction of fiber tracks was significantly improved using our method.