Structural Connectivity Remote From Lesions Correlates With Somatosensory Outcome Poststroke.

Background and Purpose: Changes in connectivity of white matter fibers remote to a stroke lesion, suggestive of structural connectional diaschisis, may impact on clinical impairment and recovery after stroke. However, until recently, we have not had tract-specific techniques to map changes in white matter tracts in vivo in humans to enable investigation of potential mechanisms and clinical impact of such remote changes. Our aim was to identify and quantify white matter tracts that are affected remote from a stroke lesion and to investigate the associations between reductions in tract-specific connectivity and impaired touch discrimination function after stroke. Methods: We applied fixel-based analysis to diffusion magnetic resonance imaging data from 37 patients with stroke (right lesion =16; left lesion =21) and 26 age-matched healthy adults. Three quantitative metrics were compared between groups: fiber density; fiber-bundle cross-section; and a combined measure of both (fiber-bundle cross-section) that reflects axonal structural connectivity. Results: Compared with healthy adults, patients with stroke showed significant common fiber-bundle cross-section and fiber density reductions in 4 regions remote from focal lesions that play roles in somatosensory and spatial information processing. Structural connectivity along the somatosensory fibers of the lesioned hemisphere was correlated with contralesional hand touch function. Touch function of the ipsilesional hand was associated with connectivity of the superior longitudinal fasciculus, and, for the right-lesion group, the corpus callosum. Conclusions: Remote tract-specific reductions in axonal connectivity indicated by diffusion imaging measures are observed in the somatosensory network after stroke. These remote white matter connectivity reductions, indicative of structural connectional diaschisis, are associated with touch impairment in patients with stroke.

Characterisation of white matter asymmetries in the healthy human brain using diffusion MRI fixel-based analysis.

The diffusion tensor model for diffusion MRI has been used extensively to study asymmetry in the human brain white matter. However, given the limitations of the tensor model, the nature of any underlying asymmetries remains uncertain, particularly in crossing fibre regions. Here, we provide a more robust characterisation of human brain white matter asymmetries based on fibre-specific diffusion MRI metrics and a whole-brain data-driven approach. We used high-quality diffusion MRI data (n = 100) from the Human Connectome Project, the spherical deconvolution model for fibre orientation distribution estimation, and the Fixel-Based Analysis framework to utilise crossing fibre information in registration, data smoothing and statistical inference. We found many significant asymmetries, widespread throughout the brain white matter, with both left>right and right>left dominances observed in different pathways. No influences of sex, age, or handedness on asymmetry were found. We also report on the relative contributions of microstructural and morphological white matter properties toward the asymmetry findings. Our findings should provide important information to future studies focussing on how these asymmetries are affected by disease, development/ageing, or how they correlate to functional/cognitive measures.

Mapping Structural Connectivity Using Diffusion MRI: Challenges and Opportunities.

Diffusion MRI-based tractography is the most commonly-used technique when inferring the structural brain connectome, i.e., the comprehensive map of the connections in the brain. The utility of graph theory-a powerful mathematical approach for modeling complex network systems-for analyzing tractography-based connectomes brings important opportunities to interrogate connectome data, providing novel insights into the connectivity patterns and topological characteristics of brain structural networks. When applying this framework, however, there are challenges, particularly regarding methodological and biological plausibility. This article describes the challenges surrounding quantitative tractography and potential solutions. In addition, challenges related to the calculation of global network metrics based on graph theory are discussed.Evidence Level: 5Technical Efficacy: Stage 1.

Early childhood development of white matter fiber density and morphology.

Early childhood is an important period for cognitive and brain development, though white matter changes specific to this period remain understudied. Here we utilize a novel analytic approach to quantify and track developmental changes in white matter micro- and macro-structure, calculated from individually oriented fiber-bundle populations, termed "fixels". Fixel-based analysis and mixed-effects models were used to assess tract-wise changes in fiber density and bundle morphology in 73 girls scanned at baseline (ages 4.09-7.02, mean â€‹= â€‹5.47, SD â€‹= â€‹0.81), 6-month (N â€‹= â€‹7), and one-year follow-up (N â€‹= â€‹42). For comparison, we also assessed changes in commonly utilized diffusion tensor metrics: fractional anisotropy (FA), and mean, radial and axial diffusivity (MD, RD, AD). Maturational increases in fixel-metrics were seen in most major white matter tracts, with the most rapid increases in the corticospinal tract and slowest or non-significant increases in the genu of the corpus callosum and uncinate fasciculi. As expected, we observed developmental increases in FA and decreases in MD, RD and AD, though percent changes were smaller relative to fixel-metrics. The majority of tracts showed more substantial morphological than microstructural changes. These findings highlight early childhood as a period of dynamic white matter maturation, characterized by large increases in macroscopic fiber bundle size, mild changes in axonal density, and parallel, albeit less substantial, changes in diffusion tensor metrics.

Maturation and interhemispheric asymmetry in neurite density and orientation dispersion in early childhood.

BACKGROUND: The brain's white matter undergoes profound changes during early childhood, which are believed to underlie the rapid development of cognitive and behavioral skills during this period. Neurite density, and complexity of axonal projections, have been shown to change across the life span, though changes during early childhood are poorly characterized. Here, we utilize neurite orientation dispersion and density imaging (NODDI) to investigate maturational changes in tract-wise neurite density index (NDI) and orientation dispersion index (ODI) during early childhood. Additionally, we assess hemispheric asymmetry of tract-wise NDI and ODI values, and longitudinal changes. METHODS: Two sets of diffusion weighted images with different diffusion-weighting were collected from 125 typically developing children scanned at baseline (N = 125; age range = 4.14-7.29; F/M = 73/52), 6-month (N = 8; F/M = 8/0), and 12-month (N = 52; F/M = 39/13) timepoints. NODDI and template-based tractography using constrained spherical deconvolution were utilized to calculate NDI and ODI values for major white matter tracts. Mixed-effects models controlling for sex, handedness, and in-scanner head motion were utilized to assess developmental changes in tract-wise NDI and ODI. Additional mixed-effects models were used to assess interhemispheric differences in tract-wise NDI and ODI values and hemispheric asymmetries in tract-wise development. RESULTS: Maturational increases in NDI were seen in all major white matter tracts, though we did not observe the expected tract-wise pattern of maturational rates (e.g. fast commissural/projection and slow frontal/temporal tract change). ODI did not change significantly with age in any tract. We observed greater NDI and ODI values in the right as compared to the left hemisphere for most tracts, but no hemispheric asymmetry for rate of change with age. CONCLUSIONS: These findings suggest that neurite density, but not orientation dispersion, increases with age during early childhood. In relation to NDI growth trends reported in infancy and late-childhood, our results suggest that early childhood may be a transitional period for neurite density maturation wherein commissural/projection fibers are approaching maturity, maturation in long range association fibers is increasing, and changes in limbic/frontal fibers remain modest. Rightward asymmetry in NDI and ODI values, but no asymmetry in developmental changes, suggests that rightward asymmetry of neurite density and orientation dispersion is established prior to age 4.

Increased cerebral blood flow with increased amyloid burden in the preclinical phase of alzheimer's disease.

BACKGROUND: Arterial spin labeling (ASL) is an emerging MRI technique for noninvasive measurement of cerebral blood flow (CBF) that has been used to show hemodynamic changes in the brains of people with Alzheimer's disease (AD). CBF changes have been measured using positron emission tomography (PET) across the AD spectrum, but ASL showed limited success in measuring CBF variations in the preclinical phase of AD, where amyloid ß (Aß) plaques accumulate in the decades prior to symptom onset. PURPOSE: To investigate the relationship between CBF measured by multiphase-pseudocontinuous-ASL (MP-PCASL) and Aß burden as measured by 11 C-PiB PET imaging in a study of cognitively normal (CN) subjects age over 65. STUDY TYPE: Cross-sectional. POPULATION: Forty-six CN subjects including 33 with low levels of Aß burden and 13 with high levels of Aß. FIELD STRENGTH/SEQUENCE: 3T/3D MP-PCASL. ASSESSMENT: The MP-PCASL method was chosen because it has a high signal-to-noise ratio. Furthermore, the data were analyzed using an efficient processing pipeline consisting of motion correction, ASL motion correction imprecision removal, temporal and spatial filtering, and partial volume effect correction. STATISTICAL TESTS: General Linear Model. RESULTS: In CN subjects positive for Aß burden (n = 13), we observed a positive correlation between CBF and Aß burden in the hippocampus, amygdala, caudate (P < 0.01), frontal, temporal, and insula (P < 0.05). DATA CONCLUSION: To the best of our knowledge, this is the first study using MP-PCASL in the study of AD, and the results suggest a potential compensatory hemodynamic mechanism that protects against pathology in the early stages of AD. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:505-513.

Basal ganglia and thalamic tract connectivity in very preterm and full-term children; associations with 7-year neurodevelopment.

BACKGROUND: Altered basal ganglia and thalamic connectivity may be critical for cognitive, motor and behavioural impairments common to very preterm (<32 weeks' gestational age) children. This study aims to (1) compare corticostriatal and thalamocortical tract connectivity between very preterm and term-born children at 7 years of age; (2) explore tract connectivity associations with 7-year neurodevelopmental outcomes, and whether these relationships differed between groups. METHODS: Eighty-three very preterm and 19 term-born (≥37 weeks' gestational age) children underwent structural and diffusion magnetic resonance imaging and had a neuropsychological assessment at 7 years. Corticostriatal and thalamocortical tracts were reconstructed and white matter connectivity was estimated with apparent fibre density. RESULTS: Compared with term-born controls, very preterm children had decreased connectivity in tracts linking the caudate to right motor areas (-10%, p = 0.03) and the thalamus with left motor areas (-5.7%, p = 0.03). Reduced connectivity in corticostriatal and thalamocortical tracts was associated with adverse motor functioning in both groups (p = 0.06). Decreased connectivity of the left caudate and putamen with the lateral prefrontal cortex was associated with lower reading performance for controls (p = 0.06). CONCLUSION: Corticostriatal and thalamocortical tracts are vulnerable to very preterm birth. Poorer connectivity in these tracts may underlie the motor impairments observed in very preterm children.

Dorsal language stream anomalies in an inherited speech disorder.

Speech disorders are highly prevalent in the preschool years, but frequently resolve. The neurobiological basis of the most persistent and severe form, apraxia of speech, remains elusive. Current neuroanatomical models of speech processing in adults propose two parallel streams. The dorsal stream is involved in sound to motor speech transformations, while the ventral stream supports sound/letter to meaning. Data-driven theories on the role of these streams during atypical speech and language development are lacking. Here we provide comprehensive behavioural and neuroimaging data on a large novel family where one parent and 11 children presented with features of childhood apraxia of speech (the same speech disorder associated with FOXP2 variants). The genetic cause of the disorder in this family remains to be identified. Importantly, in this family the speech disorder is not systematically associated with language or literacy impairment. Brain MRI scanning in seven children revealed large grey matter reductions over the left temporoparietal region, but not in the basal ganglia, relative to typically-developing matched peers. In addition, we detected white matter reductions in the arcuate fasciculus (dorsal language stream) bilaterally, but not in the inferior fronto-occipital fasciculus (ventral language stream) nor in primary motor pathways. Our findings identify disruption of the dorsal language stream as a novel neural phenotype of developmental speech disorders, distinct from that reported in speech disorders associated with FOXP2 variants. Overall, our data confirm the early role of this stream in auditory-to-articulation transformations. 10.1093/brain/awz018_video1 awz018media1 6018582401001.

Enlarged hippocampal fissure in psychosis of epilepsy.

Psychosis of epilepsy (POE) can be a devastating condition, and its neurobiological basis remains unclear. In a previous study, we identified reduced posterior hippocampal volumes in patients with POE. The hippocampus can be further subdivided into anatomically and functionally distinct subfields that, along with the hippocampal fissure, have been shown to be selectively affected in other psychotic disorders and are not captured by gross measures of hippocampal volume. Therefore, in this study, we compared the volume of selected hippocampal subfields and the hippocampal fissure in 31 patients with POE with 31 patients with epilepsy without psychosis. Cortical reconstruction, volumetric segmentation, and calculation of hippocampal subfields and the hippocampal fissure were performed using FreeSurfer. The group with POE had larger hippocampal fissures bilaterally compared with controls with epilepsy, which was significant on the right. There were no significant differences in the volumes of the hippocampal subfields between the two groups. Our findings suggest abnormal development of the hippocampus in POE. They support and expand the neurodevelopmental model of psychosis, which holds that early life stressors lead to abnormal neurodevelopmental processes, which underpin the onset of psychosis in later life. In line with this model, the findings of the present study suggest that enlarged hippocampal fissures may be a biomarker of abnormal neurodevelopment and risk for psychosis in patients with epilepsy.

Fiber-Specific Changes in White Matter Microstructure in Individuals With X-Linked Auditory Neuropathy.

OBJECTIVES: Auditory neuropathy (AN) is the term used to describe a group of hearing disorders, in which the hearing impairment occurs as a result of abnormal auditory nerve function. While our understanding of this condition has advanced significantly over recent years, the ability to determine the site of lesion and the extent of dysfunction in affected individuals remains a challenge. To this end, we investigated potential axonal degeneration in the white matter tracts of the brainstem in individuals with X-linked AN. We hypothesized that individuals with X-linked AN would show focal degeneration within the VIII nerve and/or auditory brainstem tracts, and the degree of degeneration would correlate with the extent of auditory perceptual impairment. DESIGN: This was achieved using a higher-order diffusion magnetic resonance imaging (dMRI)-based quantitative measure called apparent fiber density as obtained from a technique called single-shell 3-tissue constrained spherical deconvolution and analyzed with the fixel-based analysis framework. Eleven subjects with genetically confirmed X-linked AN and 11 controls with normal hearing were assessed using behavioral and objective auditory measures. dMRI data were also collected for each participant. RESULTS: Fixel-based analysis of the brainstem region showed that subjects with X-linked AN had significantly lower apparent fiber density in the VIII nerve compared with controls, consistent with axonal degeneration in this region. Subsequent analysis of the auditory brainstem tracts specifically showed that degeneration was also significant in these structures overall. The apparent fiber density findings were supported by objective measures of auditory function, such as auditory brainstem responses, electrocochleography, and otoacoustic emissions, which showed VIII nerve activity was severely disrupted in X-linked AN subjects while cochlear sensory hair cell function was relatively unaffected. Moreover, apparent fiber density results were significantly correlated with temporal processing ability (gap detection task) in affected subjects, suggesting that the degree of VIII nerve degeneration may impact the ability to resolve temporal aspects of an acoustic signal. Auditory assessments of sound detection, speech perception, and the processing of binaural cues were also significantly poorer in the X-linked AN group compared with the controls with normal hearing. CONCLUSIONS: The results of this study suggest that the dMRI-based measure of apparent fiber density may provide a useful adjunct to existing auditory assessments in the characterization of the site of lesion and extent of dysfunction in individuals with AN. Additionally, the ability to determine the degree of degeneration has the potential to guide rehabilitation strategies in the future.

Reduced White Matter Fiber Density in Autism Spectrum Disorder.

Differences in brain networks and underlying white matter abnormalities have been suggested to underlie symptoms of autism spectrum disorder (ASD). However, robustly characterizing microstructural white matter differences has been challenging. In the present study, we applied an analytic technique that calculates structural metrics specific to differently-oriented fiber bundles within a voxel, termed "fixels". Fixel-based analyses were used to compare diffusion-weighted magnetic resonance imaging data from 25 individuals with ASD (mean age = 16.8 years) and 27 typically developing age-matched controls (mean age = 16.9 years). Group comparisons of fiber density (FD) and bundle morphology were run on a fixel-wise, tract-wise, and global white matter (GWM) basis. We found that individuals with ASD had reduced FD, suggestive of decreased axonal count, in several major white matter tracts, including the corpus callosum (CC), bilateral inferior frontal-occipital fasciculus, right arcuate fasciculus, and right uncinate fasciculus, as well as a GWM reduction. Secondary analyses assessed associations with social impairment in participants with ASD, and showed that lower FD in the splenium of the CC was associated with greater social impairment. Our findings suggest that reduced FD could be the primary microstructural white matter abnormality in ASD.

Multi-stage automated local arterial input function selection in perfusion MRI.

OBJECTIVE: Cerebral blood flow (CBF) quantification using dynamic-susceptibility contrast MRI can be achieved via model-independent deconvolution, with local arterial input function (AIF) deconvolution methods identifying multiple arterial regions with unique corresponding arterial input functions. The clinical application of local AIF methods necessitates an efficient and fully automated solution. To date, such local AIF methods have relied on the computation of a singular surrogate measure of bolus arrival time or custom arterial scoring functions to infer vascular supply origins. This paper aims to introduce a new local AIF method that alternatively utilises a multi-stage approach to perform AIF selection. MATERIAL AND METHODS: A fully automated, multi-stage local AIF method is proposed, leveraging both signal-based cluster analysis and priority flooding to define arterial regions and their corresponding vascular supply origins. The introduced method was applied to data from four patients with cerebrovascular disease who showed significant artefacts when using a prevailing automated local AIF method. RESULTS: The immediately apparent image artefacts found using the pre-existing method due to poor AIF selection were found to be absent when using the proposed method. CONCLUSION: The results suggest the proposed solution provides a more robust approach to perfusion quantification than currently available fully automated local AIF methods.

Connectomes from streamlines tractography: Assigning streamlines to brain parcellations is not trivial but highly consequential.

When using diffusion MRI streamlines tractograms to construct structural connectomes, ideally, each streamline should connect exactly 2 regions-of-interest (i.e. network nodes) as defined by a given brain parcellation scheme. However, the ill-posed nature of termination criteria in many tractography algorithms can cause streamlines apparently being associated with zero, one, or more than two grey matter (GM) nodes; streamlines that terminate in white matter or cerebrospinal fluid may even end up being assigned to nodes if the definitions of these nodes are not strictly constrained to genuine GM areas, resulting in a misleading connectome in non-trivial ways. Based on both in-house MRI data and state-of-the-art data provided by the Human Connectome Project, this study investigates the actual influence of streamline-to-node assignment methods, and their interactions with fibre-tracking terminations and brain parcellations, on the construction of pairwise regional connectivity and subsequent connectomic measures. Our results show that the frequency of generating successful pairwise connectivity is heavily affected by the convoluted interactions between the applied strategies for connectome construction, and that minor changes in the mechanism can cause significant variations in the within- and between-module connectivity strengths as well as in the commonly-used graph theory metrics. Our data suggest that these fundamental processes should not be overlooked in structural connectomics research, and that improved data quality is not in itself sufficient to solve the underlying problems associated with assigning streamlines to brain nodes. We demonstrate that the application of advanced fibre-tracking techniques that are designed to correct for inaccuracies of track terminations with respect to anatomical information at the fibre-tracking stage is advantageous to the subsequent connectome construction process, in which pairs of parcellation nodes can be more robustly identified from streamline terminations via a suitable assignment mechanism.

Is removal of weak connections necessary for graph-theoretical analysis of dense weighted structural connectomes from diffusion MRI?

Recent advances in diffusion MRI tractography permit the generation of dense weighted structural connectomes that offer greater insight into brain organization. However, these efforts are hampered by the lack of consensus on how to extract topological measures from the resulting graphs. Here we evaluate the common practice of removing the graphs' weak connections, which is primarily intended to eliminate spurious connections and emphasize strong connections. Because this processing step requires arbitrary or heuristic-based choices (e.g., setting a threshold level below which connections are removed), and such choices might complicate statistical analysis and inter-study comparisons, in this work we test whether removing weak connections is indeed necessary. To this end, we systematically evaluated the effect of removing weak connections on a range of popular graph-theoretical metrics. Specifically, we investigated if (and at what extent) removal of weak connections introduces a statistically significant difference between two otherwise equal groups of healthy subjects when only applied to one of the groups. Using data from the Human Connectome Project, we found that removal of weak connections had no statistical effect even when removing the weakest ∼70-90% connections. Removing yet a larger extent of weak connections, thus reducing connectivity density even further, did produce a predictably significant effect. However, metric values became sensitive to the exact connectivity density, which has ramifications regarding the stability of the statistical analysis. This pattern persisted whether connections were removed by connection strength threshold or connectivity density, and for connectomes generated using parcellations at different resolutions. Finally, we showed that the same pattern also applies for data from a clinical-grade MRI scanner. In conclusion, our analysis revealed that removing weak connections is not necessary for graph-theoretical analysis of dense weighted connectomes. Because removal of weak connections provides no practical utility to offset the undesirable requirement for arbitrary or heuristic-based choices, we recommend that this step is avoided in future studies.

MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation.

MRtrix3 is an open-source, cross-platform software package for medical image processing, analysis and visualisation, with a particular emphasis on the investigation of the brain using diffusion MRI. It is implemented using a fast, modular and flexible general-purpose code framework for image data access and manipulation, enabling efficient development of new applications, whilst retaining high computational performance and a consistent command-line interface between applications. In this article, we provide a high-level overview of the features of the MRtrix3 framework and general-purpose image processing applications provided with the software.

Bilateral volume reduction in posterior hippocampus in psychosis of epilepsy.

OBJECTIVE: Psychosis of epilepsy (POE) occurs more frequently in temporal lobe epilepsy, raising the question as to whether abnormalities of the hippocampus are aetiologically important. Despite decades of investigation, it is unclear whether hippocampal volume is reduced in POE, perhaps due to small sample sizes and methodological limitations of past research. METHODS: In this study, we examined the volume of the total hippocampus, and the hippocampal head, body and tail, in a large cohort of patients with POE and patients with epilepsy without psychosis (EC). One hundred adults participated: 50 with POE and 50 EC. Total and subregional hippocampal volumes were manually traced and compared between (1) POE and EC; (2) POE with temporal lobe epilepsy, extratemporal lobe epilepsy and generalised epilepsy; and (3) patients with POE with postictal psychosis (PIP) and interictal psychosis (IP). RESULTS: Compared with EC the POE group had smaller total left hippocampus volume (13.5% decrease, p<0.001), and smaller left hippocampal body (13.3% decrease, p=0.002), and left (41.5% decrease, p<0.001) and right (36.4% decrease, p<0.001) hippocampal tail volumes. Hippocampal head volumes did not differ between groups. CONCLUSION: Posterior hippocampal volumes are bilaterally reduced in POE. Volume loss was observed on a posteroanterior gradient, with severe decreases in the tail and moderate volume decreases in the body, with no difference in the hippocampal head. Posterior hippocampal atrophy is evident to a similar degree in PIP and IP. Our findings converge with those reported for the paradigmatic psychotic disorder, schizophrenia, and suggest that posterior hippocampal atrophy may serve as a biomarker of the risk for psychosis, including in patients with epilepsy.

Fibre-specific white matter reductions in Alzheimer's disease and mild cognitive impairment.

Alzheimer's disease is increasingly considered a large-scale network disconnection syndrome, associated with progressive aggregation of pathological proteins, cortical atrophy, and functional disconnections between brain regions. These pathological changes are posited to arise in a stereotypical spatiotemporal manner, targeting intrinsic networks in the brain, most notably the default mode network. While this network-specific disruption has been thoroughly studied with functional neuroimaging, changes to specific white matter fibre pathways within the brain's structural networks have not been closely investigated, largely due to the challenges of modelling complex white matter structure. Here, we applied a novel technique known as 'fixel-based analysis' to comprehensively investigate fibre tract-specific differences at a within-voxel level (called 'fixels') to assess potential axonal loss in subjects with Alzheimer's disease and mild cognitive impairment. We hypothesized that patients with Alzheimer's disease would exhibit extensive degeneration across key fibre pathways connecting default network nodes, while patients with mild cognitive impairment would exhibit selective degeneration within fibre pathways connecting regions previously identified as functionally implicated early in Alzheimer's disease. Diffusion MRI data from Alzheimer's disease (n = 49), mild cognitive impairment (n = 33), and healthy elderly control subjects (n = 95) were obtained from the Australian Imaging, Biomarkers and Lifestyle study of ageing. We assessed microstructural differences in fibre density, and macrostructural differences in fibre bundle morphology using fixel-based analysis. Whole-brain analysis was performed to compare groups across all white matter fixels. Subsequently, we performed a tract of interest analysis comparing fibre density and cross-section across 11 selected white matter tracts, to investigate potentially subtle degeneration within fibre pathways in mild cognitive impairment, initially by clinical diagnosis alone, and then by including amyloid status (i.e. a positive or negative amyloid PET scan). Our whole-brain analysis revealed significant white matter loss manifesting both microstructurally and macrostructurally in Alzheimer's disease patients, evident in specific fibre pathways associated with default mode network nodes. Reductions in fibre density and cross-section in mild cognitive impairment patients were only exhibited within the posterior cingulum when statistical analyses were limited to tracts of interest. Interestingly, these degenerative changes did not appear to be associated with high amyloid accumulation, given that amyloid-negative, but not positive, mild cognitive impairment subjects exhibited subtle focal left posterior cingulum deficits. The findings of this study demonstrated a stereotypical distribution of white matter degeneration in patients with Alzheimer's disease, which was in line with canonical findings from other imaging modalities, and with a network-based conceptualization of the disease.awx355media15726254535001.

Robust Identification of Rich-Club Organization in Weighted and Dense Structural Connectomes.

The human brain is a complex network, in which some brain regions, denoted as 'hub' regions, play critically important roles. Some of these hubs are highly interconnected forming a rich-club organization, which has been identified based on the degree metric from structural connectomes constructed using diffusion tensor imaging (DTI)-based fiber tractography. However, given the limitations of DTI, the yielded structural connectomes are largely compromised, possibly affecting the characterization of rich-club organizations. Recent progress in diffusion MRI and fiber tractography now enable more reliable but also very dense structural connectomes to be achieved. However, while the existing rich-club analysis method is based on weighted networks, it is essentially built upon degree metric and, therefore, not suitable for identifying rich-club organizations from such dense networks, as it yields nodes with indistinguishably high degrees. Therefore, we propose a novel method, i.e. Rich-club organization Identification using Combined H-degree and Effective strength to h-degree Ratio (RICHER), to identify rich-club organizations from dense weighted networks. Overall, it is shown that more robust rich-club organizations can be achieved using our proposed framework (i.e., state-of-the-art fiber tractography approaches and our proposed RICHER method) in comparison to the previous method focusing on weighted networks based on degree, i.e., RC-degree. Furthermore, by simulating network attacks in 3 ways, i.e., attack to non-rich-club/non-rich-club edges (NRC2NRC), rich-club/non-rich-club edges (RC2NRC), and rich-club/rich-club edges (RC2RC), brain network damage consequences have been evaluated in terms of global efficiency (GE) reductions. As expected, significant GE reductions have been detected using our proposed framework among conditions, i.e., NRC2NRC < RC2NRC, NRC2NRC < RC2RC and RC2NRC < RC2RC, which however have not been detected otherwise.

Correlated Resting-State Functional MRI Activity of Frontostriatal, Thalamic, Temporal, and Cerebellar Brain Regions Differentiates Stroke Survivors with High Compared to Low Depressive Symptom Scores.

Background: One in three survivors of stroke experience poststroke depression (PSD). PSD has been linked with poorer recovery of function and cognition, yet our understanding of potential mechanisms is currently limited. Alterations in resting-state functional MRI have been investigated to a limited extent. Fluctuations in low frequency signal are reported, but it is unknown if interactions are present between the level of depressive symptom score and intrinsic brain activity in varying brain regions. Objective: To investigate potential interaction effects between whole-brain resting-state activity and depressive symptoms in stroke survivors with low and high levels of depressive symptoms. Methods: A cross-sectional analysis of 63 stroke survivors who were assessed at 3 months poststroke for depression, using the Montgomery-Åsberg Depression Rating Scale (MÅDRS-SIGMA), and for brain activity using fMRI. A MÅDRS-SIGMA score of >8 was classified as high depressive symptoms. Fractional amplitude of frequency fluctuations (fALFF) data across three frequency bands (broadband, i.e., ~0.01-0.08; subbands, i.e., slow-5: ~0.01-0.027 Hz, slow-4: 0.027-0.07) was examined. Results: Of the 63 stroke survivors, 38 were classified as "low-depressive symptoms" and 25 as "high depressive symptoms." Six had a past history of depression. We found interaction effects across frequency bands in several brain regions that differentiated the two groups. The broadband analysis revealed interaction effects in the left insula and the left superior temporal lobe. The subband analysis showed contrasting fALFF response between the two groups in the left thalamus, right caudate, and left cerebellum. Across the three frequency bands, we found contrasting fALFF response in areas within the fronto-limbic-thalamic network and cerebellum. Conclusions: We provide evidence that fALFF is sensitive to changes in poststroke depressive symptom severity and implicates frontostriatal and cerebellar regions, consistent with previous studies. The use of multiband analysis could be an effective method to examine neural correlates of depression after stroke. The START-PrePARE trial is registered with the Australian New Zealand Clinical Trial Registry, number ACTRN12610000987066.

The role of whole-brain diffusion MRI as a tool for studying human in vivo cortical segregation based on a measure of neurite density.

PURPOSE: To investigate whether diffusion MRI can be used to study cortical segregation based on a contrast related to neurite density, thus providing a complementary tool to myelin-based MRI techniques used for myeloarchitecture. METHODS: Several myelin-sensitive MRI methods (e.g., based on T1 , T2 , and T2*) have been proposed to parcellate cortical areas based on their myeloarchitecture. Recent improvements in hardware, acquisition, and analysis methods have opened the possibility of achieving a more robust characterization of cortical microstructure using diffusion MRI. High-quality diffusion MRI data from the Human Connectome Project was combined with recent advances in fiber orientation modeling. The orientational average of the fiber orientation distribution was used as a summary parameter, which was displayed as inflated brain surface views. RESULTS: Diffusion MRI identifies cortical patterns consistent with those previously seen by MRI methods used for studying myeloarchitecture, which have shown patterns of high myelination in the sensorimotor strip, visual cortex, and auditory areas and low myelination in frontal and anterior temporal areas. CONCLUSION: In vivo human diffusion MRI provides a useful complementary noninvasive approach to myelin-based methods used to study whole-brain cortical parcellation, by exploiting a contrast based on tissue microstructure related to neurite density, rather than myelin itself. Magn Reson Med 79:2738-2744, 2018. © 2017 International Society for Magnetic Resonance in Medicine.