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Background: Amyotrophic lateral sclerosis (ALS)-related white-matter microstructural abnormalities have received considerable attention; however, gray-matter structural abnormalities have not been fully elucidated. This study aimed to evaluate cortical microstructural abnormalities in ALS and determine their association with disease severity. Methods: This study included 34 patients with ALS and 30 healthy controls. Diffusion-weighted data were used to estimate neurite orientation dispersion and density imaging (NODDI) parameters, including neurite density index (NDI) and orientation dispersion index (ODI). We performed gray matter-based spatial statistics (GBSS) in a voxel-wise manner to determine the cortical microstructure difference. We used the revised ALS Functional Rating Scale (ALSFRS-R) to assess disease severity and conducted a correlation analysis between NODDI parameters and ALSFRS-R. Results: In patients with ALS, the NDI reduction involved several cortical regions [primarily the precentral gyrus, postcentral gyrus, temporal cortex, prefrontal cortex, occipital cortex, and posterior parietal cortex; family-wise error (FWE)-corrected P<0.05]. ODI decreased in relatively few cortical regions (including the precentral gyrus, postcentral gyrus, prefrontal cortex, and inferior parietal lobule; FWE-corrected P<0.05). The NDI value in the left precentral and postcentral gyrus was positively correlated with the ALS disease severity (FWE-corrected P<0.05). Conclusions: The decreases in NDI and ODI involved both motor-related and extra-motor regions and indicated the presence of gray-matter microstructural impairment in ALS. NODDI parameters are potential imaging biomarkers for evaluating disease severity in vivo. Our results showed that GBSS is a feasible method for identifying abnormalities in the cortical microstructure of patients with ALS.

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The human brain undergoes age-related microstructural alterations across the lifespan. Soma and Neurite Density Imaging (SANDI), a novel biophysical model of diffusion MRI, provides estimates of cell body (soma) radius and density, and neurite density in gray matter. The goal of this cross-sectional study was to assess the sensitivity of high-gradient diffusion MRI toward age-related alterations in cortical microstructure across the adult lifespan using SANDI. Seventy-two cognitively unimpaired healthy subjects (ages 19-85 years; 40 females) were scanned on the 3T Connectome MRI scanner with a maximum gradient strength of 300mT/m using a multi-shell diffusion MRI protocol incorporating 8 b-values and diffusion time of 19 ms. Intra-soma signal fraction obtained from SANDI model-fitting to the data was strongly correlated with age in all major cortical lobes (r = -0.69 to -0.60, FDR-p < 0.001). Intra-soma signal fraction (r = 0.48-0.63, FDR-p < 0.001) and soma radius (r = 0.28-0.40, FDR-p < 0.04) were significantly correlated with cortical volume in the prefrontal cortex, frontal, parietal, and temporal lobes. The strength of the relationship between SANDI metrics and age was greater than or comparable to the relationship between cortical volume and age across the cortical regions, particularly in the occipital lobe and anterior cingulate gyrus. In contrast to the SANDI metrics, all associations between diffusion tensor imaging (DTI) and diffusion kurtosis imaging metrics and age were low to moderate. These results suggest that high-gradient diffusion MRI may be more sensitive to underlying substrates of neurodegeneration in the aging brain than DTI and traditional macroscopic measures of neurodegeneration such as cortical volume and thickness.

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The human experience is significantly impacted by timing as it structures how information is processed. Nevertheless, the neurological foundation of time perception remains largely unresolved. Understanding cortical microstructure related to timing is crucial for gaining insight into healthy aging and recognizing structural alterations that are typical of neurodegenerative diseases associated with age. Given the importance, this study aimed to determine the brain regions that are accountable for predicting time perception in older adults using microstructural measures of the brain. In this study, elderly healthy adults performed the Time-Wall Estimation task to measure time perception through average error time. We used support vector regression (SVR) analyses to predict the average error time using cortical neurite microstructures derived from orientation dispersion and density imaging based on multi-shell diffusion magnetic resonance imaging (dMRI). We found significant correlations between observed and predicted average error times for neurite arborization (ODI) and free water (FISO). Neurite arborization and free water properties in specific regions in the medial and lateral prefrontal, superior parietal, and medial and lateral temporal lobes were among the most significant predictors of timing ability in older adults. Further, our results revealed that greater branching along with lower free water in cortical structures result in shorter average error times. Future studies should assess whether these same networks are contributing to time perception in older adults with mild cognitive impairment (MCI) and whether degeneration of these networks contribute to early diagnosis or detection of dementia.

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Associations between brain structure and body mass index (BMI) are increasingly gaining attention. Although BMI-related regional alterations in brain morphology have been previously reported, the effect of BMI on the microstructural profiles, which provide information on the proxy of neuronal density within the cortex, is unexplored. In this study, we investigated the links between cortical layer-specific microstructural profiles and BMI in 302 neurologically healthy young adults. Using the microstructure-sensitive proxy based on the T1-and T2-weighted ratio, we estimated microstructural profile covariance (MPC) by calculating linear correlations of cortical depth-wise intensity profiles between different brain regions. Then, low-dimensional gradients of the MPC matrix were estimated using dimensionality reduction techniques, and the gradients were associated with BMI. Significant effects in the heteromodal association areas were observed. The BMI-gradient association map was related to the geodesic distance along the cortical surface, curvature, and sulcal depth, suggesting that the microstructural alterations occurred along the cortical topology. The BMI-gradient association map was further linked to cognitive states related to negative emotions. Our findings may provide insights into understanding the atypical cortical microstructure associated with BMI.

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BACKGROUND: Early identification of Alzheimer's disease (AD) risk is critical for improving treatment success. Cortical thickness is a macrostructural measure used to assess neurodegeneration in AD. However, cortical microstructural changes appear to precede macrostructural atrophy and may improve early risk identification. Currently, whether cortical microstructural changes in aging are linked to vulnerability to AD pathophysiology remains unclear in nonclinical populations, who are precisely the target for early risk identification. METHODS: In 194 adults, we calculated magnetic resonance imaging-derived maps of changes in cortical mean diffusivity (microstructure) and cortical thickness (macrostructure) over 5 to 6 years (mean age: time 1 = 61.82 years; time 2 = 67.48 years). Episodic memory was assessed using 3 well-established tests. We obtained positron emission tomography-derived maps of AD pathology deposition (amyloid-ß, tau) and neurotransmitter receptors (cholinergic, glutamatergic) implicated in AD pathophysiology. Spatial correlational analyses were used to compare pattern similarity among maps. RESULTS: Spatial patterns of cortical macrostructural changes resembled patterns of cortical organization sensitive to age-related processes (r = -0.31, p < .05), whereas microstructural changes resembled the patterns of tau deposition in AD (r = 0.39, p = .038). Individuals with patterns of microstructural changes that more closely resembled stereotypical tau deposition exhibited greater memory decline (ß = 0.22, p = .029). Microstructural changes and AD pathology deposition were enriched in areas with greater densities of cholinergic and glutamatergic receptors (ps < .05). CONCLUSIONS: Patterns of cortical microstructural changes were more AD-like than patterns of macrostructural changes, which appeared to reflect more general aging processes. Microstructural changes may better inform early risk prediction efforts as a sensitive measure of vulnerability to pathological processes prior to overt atrophy and cognitive decline.

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BACKGROUND: High levels of infant negative emotionality (NE) and low positive emotionality (PE) predict future emotional and behavioral problems. The prefrontal cortex (PFC) supports emotional regulation, with each PFC subregion specializing in specific emotional processes. Neurite orientation dispersion and density imaging estimates microstructural integrity and myelination via the neurite density index (NDI) and dispersion via the orientation dispersion index (ODI), with potential to more accurately evaluate microstructural alterations in the developing brain. Yet, no study has used these indices to examine associations between PFC microstructure and concurrent or developing infant emotionality. METHODS: We modeled PFC subregional NDI and ODI at 3 months with caregiver-reported infant NE and PE at 3 months (n = 61) and at 9 months (n = 50), using multivariable and subsequent bivariate regression models. RESULTS: The most robust statistically significant findings were positive associations among 3-month rostral anterior cingulate cortex (ACC) ODI and caudal ACC NDI and concurrent NE, a positive association between 3-month lateral orbitofrontal cortex ODI and prospective NE, and a negative association between 3-month dorsolateral PFC ODI and concurrent PE. Multivariate models also revealed that other PFC subregional microstructure measures, as well as infant and caregiver sociodemographic and clinical factors, predicted infant 3- and 9-month NE and PE. CONCLUSIONS: Greater NDI and ODI, reflecting greater microstructural complexity, in PFC regions supporting salience perception (rostral ACC), decision making (lateral orbitofrontal cortex), action selection (caudal ACC), and attentional processes (dorsolateral PFC) might result in greater integration of these subregions with other neural networks and greater attention to salient negative external cues, thus higher NE and/or lower PE. These findings provide potential infant cortical markers of future psychopathology risk.

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Background: In cerebral small vessel disease (CSVD), cortical atrophy occurs at a later stage compared to microstructural abnormalities and therefore cannot be used for monitoring short-term disease progression. We aimed to investigate whether cortical diffusion tensor imaging (DTI) and quantitative (q) magnetic resonance imaging (MRI) are able to detect early microstructural involvement of the cerebral cortex in CSVD. Materials and Methods: 33 CSVD patients without significant cortical or whole-brain atrophy and 16 healthy control subjects were included and underwent structural MRI, DTI and high-resolution qMRI with T2, T2* and T2' mapping at 3 T as well as comprehensive cognitive assessment. After tissue segmentation and reconstruction of the cortical boundaries with the Freesurfer software, DTI and qMRI parameters were saved as surface datasets and averaged across all vertices. Results: Cortical diffusivity and quantitative T2 values were significantly increased in patients compared to controls (p < 0.05). T2 values correlated significantly positively with white matter hyperintensity (WMH) volume (p < 0.01). Both cortical diffusivity and T2 showed significant negative associations with axonal damage to the white matter fiber tracts (p < 0.05). Conclusions: Cortical diffusivity and quantitative T2 mapping are suitable to detect microstructural involvement of the cerebral cortex in CSVD and represent promising imaging biomarkers for monitoring disease progression and effects of therapeutical interventions in clinical studies.

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OBJECTIVE: Tissue abnormalities in focal epilepsy may extend beyond the presumed focus. The underlying pathophysiology of these broader changes is unclear, and it is not known whether they result from ongoing disease processes or treatment-related side effects, or whether they emerge earlier. Few studies have focused on the period of onset for most focal epilepsies, childhood. Fewer still have utilized quantitative magnetic resonance imaging (MRI), which may provide a more sensitive and interpretable measure of tissue microstructural change. Here, we aimed to determine common spatial modes of changes in cortical architecture in children with heterogeneous drug-resistant focal epilepsy and, secondarily, whether changes were related to disease severity. METHODS: To assess cortical microstructure, quantitative T1 and T2 relaxometry (qT1 and qT2) was measured in 43 children with drug-resistant focal epilepsy (age range = 4-18 years) and 46 typically developing children (age range = 2-18 years). We assessed depth-dependent qT1 and qT2 values across the neocortex, as well as their gradient of change across cortical depths. We also determined whether global changes seen in group analyses were driven by focal pathologies in individual patients. Finally, as a proof-of-concept, we trained a classifier using qT1 and qT2 gradient maps from patients with radiologically defined abnormalities (MRI positive) and healthy controls, and tested whether this could classify patients without reported radiological abnormalities (MRI negative). RESULTS: We uncovered depth-dependent qT1 and qT2 increases in widespread cortical areas in patients, likely representing microstructural alterations in myelin or gliosis. Changes did not correlate with disease severity measures, suggesting they may represent antecedent neurobiological alterations. Using a classifier trained with MRI-positive patients and controls, sensitivity was 71.4% at 89.4% specificity on held-out MRI-negative patients. SIGNIFICANCE: These findings suggest the presence of a potential imaging endophenotype of focal epilepsy, detectable irrespective of radiologically identified abnormalities.

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BACKGROUND: Higher-order cognition is hypothesized to be implemented via distributed cortical networks that are linked via long-range connections. However, it is unknown how computational advantages of long-range connections reflect cortical microstructure and microcircuitry. METHODS: We investigated this question by (i) profiling long-range cortical connectivity using resting-state functional magnetic resonance imaging (MRI) and cortico-cortical geodesic distance mapping, (ii) assessing how long-range connections reflect local brain microarchitecture, and (iii) examining the microarchitectural similarity of regions connected through long-range connections. RESULTS: Analysis of 2 independent datasets indicated that sensory/motor areas had more clustered short-range connections, while transmodal association systems hosted distributed, long-range connections. Meta-analytical decoding suggested that this topographical difference mirrored shifts in cognitive function, from perception/action towards emotional/social processing. Analysis of myelin-sensitive in vivo MRI as well as postmortem histology and transcriptomics datasets established that gradients in functional connectivity distance are paralleled by those present in cortical microarchitecture. Notably, long-range connections were found to link spatially remote regions of association cortex with an unexpectedly similar microarchitecture. CONCLUSIONS: By mapping covarying topographies of long-range functional connections and cortical microcircuits, the current work provides insights into structure-function relations in human neocortex.

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BACKGROUND: Non-modifiable risk factors of Alzheimer's disease (AD) have lifelong effects on cortical integrity that could be mitigated if identified at early stages. However, it remains unknown whether cortical microstructure is affected in older individuals with non-modifiable AD risk factors and whether altered cortical tissue integrity produces abnormalities in brain functional networks in this AD-risk population. METHODS: Using relative T1w/T2w (rT1w/T2w) ratio maps, we have compared tissue integrity of normal-appearing cortical GM between controls and cognitively normal older adults with either APOE4 (N = 50), with a first-degree family history (FH) of AD (N = 52), or with the co-occurrence of both AD risk factors (APOE4+FH) (N = 35). Additionally, individuals with only one risk factor (APOE4 or FH) were combined into one group (N = 102) and compared with controls. The same number of controls matched in age, sex, and years of education was employed for each of these comparisons. Group differences in resting state functional connectivity (rs-FC) patterns were also investigated, using as FC seeds those cortical regions showing significant changes in rT1w/T2w ratios. RESULTS: Overall, individuals with non-modifiable AD risk factors exhibited significant variations in rT1w/T2w ratios compared to controls, being APOE4 and APOE4+FH at opposite ends of a continuum. The co-occurrence of APOE4 and FH was further accompanied by altered patterns of rs-FC. CONCLUSIONS: These findings may have practical implications for early detection of cortical abnormalities in older populations with APOE4 and/or FH of AD and open new avenues to monitor changes in cortical tissue integrity associated with non-modifiable AD risk factors.

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INTRODUCTION: Neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion-weighted imaging (DWI) model, may be useful for detecting early cortical microstructural alterations in Alzheimer's disease prior to cognitive impairment. METHODS: Using neuroimaging (NODDI and T1-weighted magnetic resonance imaging [MRI]) and cerebrospinal fluid (CSF) biomarker data (measured using Elecsys® CSF immunoassays) from 219 cognitively unimpaired participants, we tested the main and interactive effects of CSF amyloid beta (Aß)42 /Aß40 and phosphorylated tau (p-tau) on cortical NODDI metrics and cortical thickness, controlling for age, sex, and apolipoprotein E ε4. RESULTS: We observed a significant CSF Aß42 /Aß40 × p-tau interaction on cortical neurite density index (NDI), but not orientation dispersion index or cortical thickness. The directionality of these interactive effects indicated: (1) among individuals with lower CSF p-tau, greater amyloid burden was associated with higher cortical NDI; and (2) individuals with greater amyloid and p-tau burden had lower cortical NDI, consistent with cortical neurodegenerative changes. DISCUSSION: NDI is a particularly sensitive marker for early cortical changes that occur prior to gross atrophy or development of cognitive impairment.

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To extract Diffusion Tensor Imaging (DTI) parameters from the human cortex, the inner and outer boundaries of the cortex are usually defined on 3D-T1-weighted images and then applied to the co-registered DTI. However, this analysis requires the acquisition of an additional high-resolution structural image that may not be practical in various imaging studies. Here an automatic cortical boundary segmentation method was developed to work directly only on the native DTI images by using fractional anisotropy (FA) maps and mean diffusion weighted images (DWI), the latter with acceptable gray-white matter image contrast. This new method was compared to the conventional cortical segmentations generated from high-resolution T1 structural images in 5 participants. In addition, the proposed method was applied to 15 healthy young adults (10 cross-sectional, 5 test-retest) to measure FA, MD, and radiality of the primary eigenvector across the cortex on whole-brain 1.5 mm isotropic images acquired in 3.5 min at 3T. The proposed method generated reasonable segmentations of the cortical boundaries for all individuals and large proportions of the proposed method segmentations (more than 85%) were within ±1 mm from those generated with the conventional approach on higher resolution T1 structural images. Both FA (~0.15) and MD (~0.77 × 10-3 mm2/s) extracted halfway between the cortical boundaries were relatively stable across the cortex, although focal regions such as the posterior bank of the central sulcus, anterior insula, and medial temporal lobe showed higher FA. The primary eigenvectors were primarily oriented radially to the middle cortical surface, but there were tangential orientations in the sulcal fundi as well as in the posterior bank of the central sulcus. The proposed method demonstrates the feasibility and accuracy of cortical analysis in native DTI space while avoiding the acquisition of other imaging contrasts like 3D T1-weighted scans.

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Leptomeningeal collateral supply is considered pivotal in steno-occlusive vasculopathy to prevent chronic microstructural ischaemic tissue damage. The aim of this study was to assess the alleged protective role of leptomeningeal collaterals in patients with unilateral high-grade steno-occlusive vasculopathy using quantitative (q)T2 mapping and perfusion-weighted imaging (PWI)-based collateral abundance. High-resolution qT2 was used to estimate microstructural damage of the segmented normal-appearing cortex. Volumetric abundance of collaterals was assessed based on PWI source data. The ratio relative cerebral blood flow/relative cerebral blood volume (rCBF/rCBV) as a surrogate of relative cerebral perfusion pressure (rCPP) was used to investigate the intravascular hemodynamic competency of pial collateral vessels and the hemodynamic state of brain parenchyma. Within the dependent vascular territory with increased cortical qT2 values (P = 0.0001) compared to the contralateral side, parenchymal rCPP was decreased (P = 0.0001) and correlated negatively with increase of qT2 (P < 0.05). Furthermore, volumetric abundance of adjacent leptomeningeal collaterals was significantly increased (P < 0.01) and negatively correlated with changes of parenchymal rCPP (P = 0.01). Microstructural cortical damage is closely related to restrictions of antegrade blood flow despite increased pial collateral vessel abundance. Therefore, increased leptomeningeal collateral supply cannot necessarily be regarded as a sign of effective compensation in patients with high-grade steno-occlusive vasculopathy.

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The aim of this research was to test a novel in-vivo brain MRI analysis method that could be used in clinical cohorts to investigate cortical architecture changes in patients with Alzheimer's Disease (AD). Three cohorts of patients with probable AD and healthy volunteers were used to assess the results of the method. The first group was used as the "Discovery" cohort, the second as the "Test" cohort and the last "ATN" (Amyloid, Tau, Neurodegeneration) cohort was used to test the method in an ADNI 3 cohort, comparing to amyloid and Tau PET. The method can detect altered quality of cortical grey matter in AD patients, providing an additional tool to assess AD, distinguishing between these and healthy controls with an accuracy range between good and excellent. These new measurements could be used within the "ATN" framework as an index of cortical microstructure quality and a marker of Neurodegeneration. Further development may aid diagnosis, patient selection, and quantification of the "Neurodegeneration" component in response to therapies in clinical trials.

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Cerebral cortical architecture at birth encodes regionally differential dendritic arborization and synaptic formation. It underlies behavioral emergence of 2-year-olds. Brain changes in 0-2 years are most dynamic across the lifespan. Effective prediction of future behavior with brain microstructure at birth will reveal structural basis of behavioral emergence in typical development and identify biomarkers for early detection and tailored intervention in atypical development. Here we aimed to evaluate the neonate whole-brain cortical microstructure quantified by diffusion MRI for predicting future behavior. We found that individual cognitive and language functions assessed at the age of 2 years were robustly predicted by neonate cortical microstructure using support vector regression. Remarkably, cortical regions contributing heavily to the prediction models exhibited distinctive functional selectivity for cognition and language. These findings highlight regional cortical microstructure at birth as a potential sensitive biomarker in predicting future neurodevelopmental outcomes and identifying individual risks of brain disorders.

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During development, cellular events such as cell proliferation, migration, and synaptogenesis determine the structural organization of the brain. These processes are driven in part by spatiotemporally regulated gene expression. We investigated how the genetic signatures of specific neural cell types shape cortical organization of the human brain throughout infancy and childhood. Using a transcriptional atlas and in vivo magnetic resonance imaging (MRI) data, we demonstrated time-dependent associations between the expression levels of neuronal and glial genes and cortical macro- and microstructure. Neonatal cortical phenotypes were associated with prenatal glial but not neuronal gene expression. These associations reflect cell migration and proliferation during fetal development. Childhood cortical phenotypes were associated with neuronal and astrocyte gene expression related to synaptic signaling processes, reflecting the refinement of cortical connections. These findings indicate that sequential developmental stages contribute to distinct MRI measures at different time points. This helps to bridge the gap between the genetic mechanisms driving cellular changes and widely used neuroimaging techniques.

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During the third trimester, the human brain undergoes rapid cellular and molecular processes that reshape the structural architecture of the cerebral cortex. Knowledge of cortical differentiation obtained predominantly from histological studies is limited in localized and small cortical regions. How cortical microstructure is differentiated across cortical regions in this critical period is unknown. In this study, the cortical microstructural architecture across the entire cortex was delineated with non-Gaussian diffusion kurtosis imaging as well as conventional diffusion tensor imaging of 89 preterm neonates aged 31-42 postmenstrual weeks. The temporal changes of cortical mean kurtosis (MK) or fractional anisotropy (FA) were heterogeneous across the cortical regions. Cortical MK decreases were observed throughout the studied age period, while cortical FA decrease reached its plateau around 37 weeks. More rapid decreases in MK were found in the primary visual region, while faster FA declines were observed in the prefrontal cortex. We found that distinctive cortical microstructural changes were coupled with microstructural maturation of associated white matter tracts. Both cortical MK and FA measurements predicted the postmenstrual age of preterm infants accurately. This study revealed a differential 4D spatiotemporal cytoarchitectural signature inferred by non-Gaussian diffusion barriers inside the cortical plate during the third trimester. The cytoarchitectural processes, including dendritic arborization and neuronal density decreases, were inferred by regional cortical FA and MK measurements. The presented findings suggest that cortical MK and FA measurements could be used as effective imaging markers for cortical microstructural changes in typical and potentially atypical brain development.

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INTRODUCTION: Cortical mean diffusivity (MD) and free water fraction (FW) changes are proposed biomarkers for Alzheimer's disease (AD). METHODS: We included healthy control subjects (N = 254), mild cognitive impairment (N = 41), and AD dementia (N = 31) patients. Participants underwent a lumbar puncture and a 3 T magnetic resonance imaging. Healthy control subjects were classified following National Institute on Aging-Alzheimer's Association stages (stage 0, N = 220; stage 1, N = 25; and stage 2/3, N = 9). We assessed the cortical MD, cortical FW, and cortical thickness (CTh) changes along the AD continuum. RESULTS: Microstructural and macrostructural changes show a biphasic trajectory. Stage 1 subjects showed increased CTh and decreased MD and FW with respect the stage 0 subjects. Stage 2/3 subjects showed decreased CTh and increased cortical MD and FW, changes that were more widespread in symptomatic stages. DISCUSSION: These results support a biphasic model of changes in AD, which could affect the selection of patients for clinical trials and the use of magnetic resonance imaging as a surrogate marker of disease modification.

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Research in the macaque monkey suggests that cortical areas with similar microstructure are more likely to be connected. Here, we examine this link in the human cerebral cortex using 2 magnetic resonance imaging (MRI) measures: quantitative  T1 maps, which are sensitive to intracortical myelin content and provide an in vivo proxy for cortical microstructure, and resting-state functional connectivity. Using ultrahigh-resolution MRI at 7 T and dedicated image processing tools, we demonstrate a systematic relationship between T1-based intracortical myelin content and functional connectivity. This effect is independent of the proximity of areas. We employ nonlinear dimensionality reduction to characterize connectivity components and identify specific aspects of functional connectivity that are linked to myelin content. Our results reveal a consistent spatial pattern throughout different analytic approaches. While functional connectivity and myelin content are closely linked in unimodal areas, the correspondence is lower in transmodal areas, especially in posteromedial cortex and the angular gyrus. Our findings are in agreement with comprehensive reports linking histologically assessed microstructure and connectivity in different mammalian species and extend them to the human cerebral cortex in vivo.

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The human brain develops rapidly during 32-45 postmenstrual weeks (PMW), a critical stage characterized by dramatic increases of metabolic demand. The increasing metabolic demand can be inferred through measurements of regional cerebral blood flow (CBF), which might be coupled to regional metabolism in preterm brains. Arterial spin labeled (ASL) perfusion MRI is one of the few viable approaches for imaging regional CBF of preterm brains, but must be optimized for the extremely slow blood velocity unique in preterm brains. In this study, we explored the spatiotemporal CBF distribution in newborns scanned at the age of 32-45PMW using a pseudo-continuous ASL (pCASL) protocol adapted to slow blood flow in neonates. A total of 89 neonates were recruited. PCASL MRI was acquired from 34 normal newborns and phase contrast (PC) images from 19 newborns. Diffusion tensor images (DTI) were acquired from all 89 neonates for measuring cortical fractional anisotropy (FA), which characterizes cortical microstructure. Reproducible CBF measurements were obtained with the adjusted pCASL sequence. Global CBF measurement based on PC MRI was found to double its value in the 3rd trimester. Regional CBF increases were heterogeneous across the brain with a significantly higher rate of CBF increase in the frontal lobe and a lower rate of CBF increase in the occipital lobe. A significant correlation was found between frontal cortical CBF and cortical FA measurements (p<0.01). Increasing CBF values observed in the frontal lobe corresponded to lower FA values, suggesting that dendritic arborization and synaptic formation might be associated with an elevated local CBF. These results offer a preliminary account of heterogeneous regional CBF increases in a vital early developmental period and may shed the light on underlying metabolic support for cortical microstructural changes during the developmental period of 32-45PMW. Preterm effects and limitations of pCASL techniques in newborns need to be carefully considered for interpretation these results.

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