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Epilepsy is increasingly recognised as a brain network disorder and many studies have investigated functional connectivity (FC) in children with epilepsy using functional MRI (fMRI). This systematic review of fMRI studies, published up to November 2023, investigated profiles of FC changes and their clinical relevance in children with focal epilepsy compared to healthy controls. A literature search in PubMed and Web of Science yielded 62 articles. We categorised the results into three groups: 1) differences in correlation-based FC between patients and controls; 2) differences in other FC measures between patients and controls; and 3) associations between FC and disease variables (for example, age of onset), cognitive and seizure outcomes. Studies revealed either increased or decreased FC across multiple brain regions in children with focal epilepsy. However, findings lacked consistency: conflicting FC alterations (decreased and increased FC) co-existed within or between brain regions across all focal epilepsy groups. The studies demonstrated overall that 1) interhemispheric connections often displayed abnormal connectivity and 2) connectivity within and between canonical functional networks was decreased, particularly for the default mode network. Focal epilepsy disrupted FC in children both locally (e.g., seizure-onset zones, or within-brain subnetworks) and globally (e.g., whole-brain network architecture). The wide variety of FC study methodologies limits clinical application of the results. Future research should employ longitudinal designs to understand the evolution of brain networks during the disease course and explore the potential of FC biomarkers for predicting cognitive and postsurgical seizure outcomes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.)

In Diffusion Weighted MR Imaging (DWI), the signal is affected by the biophysical properties of neuronal cells and their relative placement, as well as extra-cellular tissue compartments. Typically, microstructural indices, such as fractional anisotropy (FA) and mean diffusivity (MD), are based on a tensor model that cannot disentangle the influence of these parameters. Recently, Neurite Orientation Dispersion and Density Imaging (NODDI) has exploited multi-shell acquisition protocols to model the diffusion signal as the contribution of three tissue compartments. NODDI microstructural indices, such as intra-cellular volume fraction (ICVF) and orientation dispersion index (ODI) are directly related to neuronal density and orientation dispersion, respectively. One way of examining the neurophysiological role of these microstructural indices across neuronal fibres is to look into how they relate to brain function. Here we exploit a statistical framework based on sparse Canonical Correlation Analysis (sCCA) and randomised Lasso to identify structural connections that are highly correlated with resting-state functional connectivity measured with simultaneous EEG-fMRI. Our results reveal distinct structural fingerprints for each microstructural index that also reflect their inter-relationships.

Preterm birth has been associated with altered microstructural properties of the white matter and lower cognitive ability in childhood and adulthood. Due to methodological limitations of the diffusion tensor model, it is not clear whether alterations in myelination or variation in fibre orientation are driving these differences. Novel models applied to multi‐shell diffusion imaging have been used to disentangle these effects, but to date this has not been used to study the preterm brain in adulthood. This study investigated whether novel advanced diffusion MRI metrics such as microscopic anisotropy and orientation dispersion are altered in adults born preterm, and whether this was associated with cognitive performance. Seventy‐two preterm born participants (<37 weeks gestational age) were recruited from a 1982–1984 cohort (33 males, mean age 33.5 ± 1.0 years). Seventy‐two term born (>37 weeks gestational age) controls (34 males, mean age 30.9 ± 4.0 years) were recruited from the general population. Tensor FA was calculated with FSL, while microscopic FA and orientation dispersion entropy (ODE) were estimated using the Spherical Mean Technique (SMT). Estimated Full Scale IQ (FSIQ), Verbal Comprehension Index (VCI) and Perceptual Reasoning Index (PRI) were obtained from the WASI‐II (abbreviated) IQ test. Voxel‐wise comparisons using FSL's tract‐based spatial statistics were performed to test between‐group differences in diffusion MRI metrics as well as within‐group associations of diffusion MRI metrics and IQ outcomes. The preterm group had significantly lower FSIQ, VCI and PRI scores. Preterm subjects demonstrated widespread decreases in ODE reflecting increased fibre dispersion, but no differences in microscopic FA. Tensor FA was increased in a small area in the anterior corona radiata. Lower FA values in the preterm population were associated with lower FSIQ and PRI scores. An increase in fibre dispersion in white matter and lower IQ scores after preterm birth exist in adulthood. Advanced diffusion MRI metrics such as the orientation dispersion entropy can be used to monitor white matter alterations across the lifespan in preterm born individuals. Although not significantly different between preterm and term groups, tensor FA values in the preterm group were associated with cognitive outcome. [ABSTRACT FROM AUTHOR]

Research in sickle cell anemia (SCA) has used, with limited race-matched control data, binary categorization of patients according to the presence or absence of silent cerebral infarction (SCI). SCI have primarily been identified using low-resolution MRI, with radiological definitions varying in lesion length and the requirement for abnormality on both fluid attenuated inversion recovery (FLAIR) and T1-weighted images. We aimed to assess the effect of published SCI definitions on global, regional, and lobar lesion metrics and their value in predicting cognition. One hundred and six patients with SCA and 48 controls aged 8–30 years underwent 3T MRI with a high-resolution FLAIR sequence and Wechsler cognitive assessment. Prevalence, number, and volume of lesions were calculated using a semi-automated pipeline for SCI defined as: (1) Liberal: any length (L-SCI); (2) Traditional: >3 mm in greatest dimension (T-SCI); (3) Restrictive; >3 mm in greatest dimension with a corresponding T1-weighted hypo-intensity (R-SCI). Globally, as hypothesized, there were large effects of SCI definition on lesion metrics in patients and controls, with prevalence varying from 24–42% in patients, and 4–23% in controls. However, contrary to hypotheses, there was no effect of any global metric on cognition. Regionally, there was a consistent distribution of SCI in frontal and parietal deep and juxta-cortical regions across definitions and metrics in patients, but no consistent distribution in controls. Effects of regional SCI metrics on cognitive performance were of small magnitude; some were paradoxical. These findings expose the challenges associated with the widespread use of SCI presence as a biomarker of white-matter injury and cognitive dysfunction in cross-sectional high-resolution MRI studies in patients with SCA. The findings indicate that with high-resolution MRI: (1) radiological definitions have a large effect on resulting lesion groups, numbers, and volumes; (2) there is a non-negligible prevalence of lesions in young healthy controls; and (3) at the group-level, there is no cross-sectional association between global lesion metrics and general cognitive impairment irrespective of lesion definition and metric. With high-resolution multi-modal MRI, the dichotomy of presence or absence of SCI does not appear to be a sensitive biomarker for the detection of functionally significant pathology; the search for appropriate endpoints for clinical treatment trials should continue. [ABSTRACT FROM AUTHOR]

Structural network-based approaches can assess white matter connections revealing topological alterations in multiple sclerosis (MS). However, principal network (PN) organisation and its clinical relevance in MS has not been explored yet. Here, structural networks were reconstructed from diffusion data in 58 relapsing-remitting MS (RRMS), 28 primary progressive MS (PPMS), 36 secondary progressive (SPMS) and 51 healthy controls (HCs). Network hubs' strengths were compared with HCs. Then, PN analysis was performed in each clinical subtype. Regression analysis was applied to investigate the associations between nodal strength derived from the first and second PNs (PN1 and PN2) in MS, with clinical disability. Compared with HCs, MS patients had preserved hub number, but some hubs exhibited reduced strength. PN1 comprised 10 hubs in HCs, RRMS and PPMS but did not include the right thalamus in SPMS. PN2 comprised 10 hub regions with intra-hemispheric connections in HCs. In MS, this subnetwork did not include the right putamen whilst in SPMS the right thalamus was also not included. Decreased nodal strength of the right thalamus and putamen from the PNs correlated strongly with higher clinical disability. These PN analyses suggest distinct patterns of disruptions in MS subtypes which are clinically relevant [ABSTRACT FROM AUTHOR]

Connectivity-based parcellation of subcortical structures using diffusion tractography is now a common paradigm in neuroscience. These analyses often imply voxel-level specificity of connectivity, and the formation of compact, spatially coherent clusters is often taken as strong imaging-based evidence for anatomically distinct subnuclei in an individual. In this study, we demonstrate that internal structure in diffusion anisotropy is not necessary for a plausible parcellation to be obtained, by spatially permuting diffusion parameters within the thalami and repeating the parcellation. Moreover, we show that, in a winner-takes-all paradigm, most voxels receive the same label before and after this shuffling process—a finding that is stable across image acquisitions and tractography algorithms. We therefore suggest that such parcellations should be interpreted with caution. [ABSTRACT FROM AUTHOR]

Conformationally mobile oligomers with helical structures, or ‘dynamic foldamers’, may populate a mixture of screw-sense conformers whose relative proportion has been used as a means of communicating information on a molecular scale. The dibenzazepinyl urea provides a means of quantifying both the sense and degree of this screw-sense preference through a combination of circular dichroism (CD) and NMR spectroscopy. The dibenzazepinyl urea probe is synthetically versatile, readily accessible, and easy to introduce to the terminus of an amide or a urea foldamer. [ABSTRACT FROM AUTHOR]

Aim: Sickle cell disease (SCD) is the commonest cause of childhood stroke worldwide. Magnetic resonance imaging (MRI) is routinely used to detect additional silent cerebral infarction (SCI), as IQ is lower in SCI as well as stroke. This review assesses the effect of infarction on IQ, and specifically whether, compared to healthy controls, IQ differences are seen in children with SCI with no apparent MRI abnormality.Method: A systematic review was conducted to include articles with an SCD paediatric population, MRI information, and Wechsler IQ. A meta-analysis of 19 articles was performed to compare IQ in three groups: stroke vs SCI; SCI vs no SCI; and no SCI vs healthy controls.Results: Mean differences in IQ between all three groups were significant: stroke patients had lower IQ than patients with SCI by 10 points (six studies); patients with SCI had lower IQ than no patients with SCI by 6 points (17 studies); and no patients with SCI had lower IQ than healthy controls by 7 points (seven studies).Interpretation: Children with SCD and no apparent MRI abnormality have significantly lower IQ than healthy controls. In this chronic condition, other biological, socioeconomic, and environmental factors must play a significant role in cognition. [ABSTRACT FROM AUTHOR]

Structural brain networks may be reconstructed from diffusion MRI tractography data and have great potential to further our understanding of the topological organisation of brain structure in health and disease. Network reconstruction is complex and involves a series of processesing methods including anatomical parcellation, registration, fiber orientation estimation and whole-brain fiber tractography. Methodological choices at each stage can affect the anatomical accuracy and graph theoretical properties of the reconstructed networks, meaning applying different combinations in a network reconstruction pipeline may produce substantially different networks. Furthermore, the choice of which connections are considered important is unclear. In this study, we assessed the similarity between structural networks obtained using two independent state-of-the-art reconstruction pipelines. We aimed to quantify network similarity and identify the core connections emerging most robustly in both pipelines. Similarity of network connections was compared between pipelines employing different atlases by merging parcels to a common and equivalent node scale. We found a high agreement between the networks across a range of fiber density thresholds. In addition, we identified a robust core of highly connected regions coinciding with a peak in similarity across network density thresholds, and replicated these results with atlases at different node scales. The binary network properties of these core connections were similar between pipelines but showed some differences in atlases across node scales. This study demonstrates the utility of applying multiple structural network reconstrution pipelines to diffusion data in order to identify the most important connections for further study. [ABSTRACT FROM AUTHOR]

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functionalMRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity. [ABSTRACT FROM AUTHOR]

Sickle cell anaemia ( SCA) is associated with silent cerebral infarction ( SCI), affecting white and cortical grey matter, but there are few data on subcortical volumes. We analysed retrospective magnetic resonance imaging ( MRI) data in 26 SCA patients and 20 controls, comparing mean subcortical volumes between three groups: controls, SCA with SCI ( n = 13) and SCA without visible abnormality ( n = 13). Specific volumetric differences were found in the hippocampus, amygdala, pallidum, caudate, putamen, thalamus, and cerebellum. This is the first study to demonstrate subcortical volume change in SCA, with the most severe volumetric deficits occurring in children with SCI seen on MRI. [ABSTRACT FROM AUTHOR]

Graph representations of brain connectivity have attracted a lot of recent interest, but existing methods for dividing such graphs into connected subnetworks have a number of limitations in the context of neuroimaging. This is an important problem because most cognitive functions would be expected to involve some but not all brain regions. In this paper we outline a simple approach for decomposing graphs, which may be based on any measure of interregional association, into coherent “principal networks”. The technique is based on an eigendecomposition of the association matrix, and is closely related to principal components analysis. We demonstrate the technique using cortical thickness and diffusion tractography data, showing that the subnetworks which emerge are stable, meaningful and reproducible. Graph-theoretic measures of network cost and efficiency may be calculated separately for each principal network. Unlike some other approaches, all available connectivity information is taken into account, and vertices may appear in none or several of the subnetworks. Subject-by-subject “scores” for each principal network may also be obtained, under certain circumstances, and related to demographic or cognitive variables of interest. [ABSTRACT FROM AUTHOR]

Objectives: To assess the prevalence of behavioral problems in children with isolated optic nerve hypoplasia, mild to moderate or no visual impairment, and no developmental delay. To identify white matter abnormalities that may provide neural correlates for any behavioral abnormalities identified. Patients and Methods: Eleven children with isolated optic nerve hypoplasia (mean age 5.9 years) underwent behavioral assessment and brain diffusion tensor imaging, Twenty four controls with isolated short stature (mean age 6.4 years) underwent MRI, 11 of whom also completed behavioral assessments. Fractional anisotropy images were processed using tract-based spatial statistics. Partial correlation between ventral cingulum, corpus callosum and optic radiation fractional anisotropy, and child behavioral checklist scores (controlled for age at scan and sex) was performed. Results: Children with optic nerve hypoplasia had significantly higher scores on the child behavioral checklist (p<0.05) than controls (4 had scores in the clinically significant range). Ventral cingulum, corpus callosum and optic radiation fractional anisotropy were significantly reduced in children with optic nerve hypoplasia. Right ventral cingulum fractional anisotropy correlated with total and externalising child behavioral checklist scores (r = −0.52, p<0.02, r = −0.46, p<0.049 respectively). There were no significant correlations between left ventral cingulum, corpus callosum or optic radiation fractional anisotropy and behavioral scores. Conclusions: Our findings suggest that children with optic nerve hypoplasia and mild to moderate or no visual impairment require behavioral assessment to determine the presence of clinically significant behavioral problems. Reduced structural integrity of the ventral cingulum correlated with behavioral scores, suggesting that these white matter abnormalities may be clinically significant. The presence of reduced fractional anisotropy in the optic radiations of children with mild to moderate or no visual impairment raises questions as to the pathogenesis of these changes which will need to be addressed by future studies. [ABSTRACT FROM AUTHOR]

Rationale As the population of the world ages, age-related cognitive decline is becoming an ever-increasing problem. However, the changes in brain structure that accompany normal aging, and the role they play in cognitive decline, remain to be fully elucidated. Aims This study aims to characterize changes in brain structure in old age, and to investigate relationships between brain aging and cognitive decline using the Lothian Birth Cohort 1936. Here, we report the rationale, design and methodology of the brain and neurovascular imaging protocol developed to study this cohort. Design An observational, longitudinal study of the Lothian Birth Cohort 1936, which comprises 1091 relatively healthy individuals now in their 70s and living in the Edinburgh area. They are surviving participants of the Scottish Mental Survey 1947, which involved a test of general intelligence taken at age 11 years. At age 70 years, the Lothian Birth Cohort 1936 undertook detailed cognitive, medical and genetic testing, and provided social, family, nutritional, quality of life and physical activity information. At mean age 73 years they underwent detailed brain MRI and neurovascular ultrasound imaging, repeat cognitive and other testing. The MRI protocol is designed to provide qualitative and quantitative measures of gray and white matter atrophy, severity and location of white matter lesions, enlarged perivascular spaces, brain mineral deposits, microbleeds and integrity of major white matter tracts. The neurovascular ultrasound imaging provides velocity, stenosis and intima-media thickness measurements of the carotid and vertebral arteries. Study This valuable imaging dataset will be used to determine which changes in brain structural parameters have the largest effects on cognitive aging. Analysis will include multimodal image analysis and multivariate techniques, such as factor analysis and structural equation modelling. Especially valuable is the ability within this sample to examine the influence that early life intelligence has on brain structural parameters in old age, and the role of genetic, vascular, educational and lifestyle factors. Outcomes Final outcomes include associations between early and late life cognition and integrity of key white matter tracts, volume of gray and white matter, myelination, brain water content, and visible abnormalities such as white matter lesions and mineral deposits; and influences of vascular risk factors, diet, environment, social metrics, education and genetics on healthy brain aging. It is intended that this information will help to inform and develop strategies for successful cognitive aging. [ABSTRACT FROM AUTHOR]

Abstract: Regions of diffuse periventricular white matter hyperintensities (PVWMH) are a common finding on T2-weighted MRI scans of older subjects, but their aetiology remains unclear. The aim of this study was to characterize differences in water diffusion and magnetization transfer MRI parameters between macroscopically normal-appearing white matter (NAWM) and PVWMH in a cohort of normal older subjects. Forty-two non-demented 83-year olds underwent structural, diffusion tensor and magnetization transfer MRI. Mean diffusivity (), fractional anisotropy (FA), axial (λ ax) and radial (λ rad) diffusivity, and magnetization transfer ratio (MTR) were measured in both NAWM and PVWMH in frontal and parieto-occipital white matter, and centrum semiovale. For all three regions, PVWMH had greater , λ ax and λ rad than NAWM, while FA and MTR were significantly reduced compared with normal tissue (p ≪0.01). For PVWMH, MTR was significantly correlated (Spearman''s ρ in the range −0.93 to 0.70; p <0.01) with , FA, λ ax and λ rad in all three regions. Conversely, for NAWM, the only significant correlation between MTR and a water diffusion parameter was for λ rad in parieto-occipital white matter (ρ =−0.40; p <0.05), with all other correlations close to the ρ =0 level. These data indicate that in normal white matter, characterized by structurally coherent cell membranes, the degree of water molecule diffusion and myelination are held within relatively tight limits. However, within PVWMH, MTR correlates strongly with water diffusion parameters probably because of the pathologically associated neuronal loss, demyelination and gliosis. [Copyright &y& Elsevier]

Since the invention of diffusion magnetic resonance imaging (dMRI), currently the only established method for studying white matter connectivity in a clinical environment, there has been a great deal of interest in the effects of various pathologies on the connectivity of the brain. As methods for in vivo tractography have been developed, it has become possible to track and segment specific white matter structures of interest for particular study. However, the consistency and reproducibility of tractography-based segmentation remain limited, and attempts to improve them have thus far typically involved the imposition of strong constraints on the tract reconstruction process itself. In this work we take a different approach, developing a formal probabilistic model for the relationships between comparable tracts in different scans, and then using it to choose a tract, a posteriori, which best matches a predefined reference tract for the structure of interest. We demonstrate that this method is able to significantly improve segmentation consistency without directly constraining the tractography algorithm. [ABSTRACT FROM AUTHOR]

Abstract: The field of tractography is rapidly developing, and many automatic or semiautomatic algorithms have now been devised to segment and visualize neural white matter fasciculi in vivo. However, these algorithms typically need to be given a starting location as input, and their output can be strongly dependent on the exact location of this “seed point”. No robust method has yet been devised for placing these seed points so as to segment a comparable tract in a group of subjects. Here, we develop a measure of tract similarity, based on the shapes and lengths of the two tracts being compared, and apply it to the problem of consistent seed point placement and tract segmentation in group data. We demonstrate that using a single seed point transferred from standard space to each native space produces considerable variability in tractography output between scans. However, by seeding in a group of nearby candidate points and choosing the output with the greatest similarity to a reference tract chosen in advance–a method we refer to as neighborhood tractography–this variability can be significantly reduced. [Copyright &y& Elsevier]

Abstract: Purpose: This study assessed test–retest reliability and repeatability of diffusion tensor imaging (DTI) in the kidneys. Materials and methods: Seven healthy volunteers (age range, 19–31 years), were imaged three consecutive times on the same day (short-term reliability) and the same imaging protocol was repeated after a month (long-term reliability). Diffusion-weighted magnetic resonance imaging scans in the coronal-oblique projection of the kidney were acquired on a 1.5T scanner using a multi-section echo-planar sequence; six contiguous slices each 5mm thick, diffusion sensitisation along 20 non-collinear directions, TR=730ms, TE=73ms and 2 b-values (0 and 400smm−2). Volunteers were asked to hold their breath throughout each data acquisition (approx. 20s). The apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values were obtained from maps generated using dedicated software MIStar (Apollo Medical Imaging, Melbourne, Australia). Results: Statistical analyses of both short- and long-term repeats were carried out from which the within-subject coefficient of variation (wsCV) was calculated. The wsCV obtained for both the ADC and FA values were less than 10% in all the analyses carried out. In addition, paired (repeated measures) t-test was used to measure the variation between the diffusion parameters collected from the two scanning sessions a month apart. It showed no significant difference and the wsCV obtained after comparing the first and second scans were found to be smaller than 15% for both ADC and FA. Conclusion: Renal DTI produces reliable and repeatable results which make longitudinal investigation of patients viable. [Copyright &y& Elsevier]

Abstract: Quantitative tractography may provide insights into regional heterogeneity of changes in white matter structure in normal ageing. Here we examine how brain atrophy and white matter lesions affect correlations between tract shape, tract integrity and age in a range of frontal and non-frontal tracts in 90 non-demented subjects aged over 65 years using an enhanced version of probabilistic neighbourhood tractography. This novel method for automatic single seed point placement employs unsupervised learning and streamline selection to provide reliable and accurate tract segmentation, whilst also indicating how the shape of an individual tract compares to that of a predefined reference tract. There were significant negative correlations between tract shape similarity to reference tracts derived from a young brain white matter atlas and age in genu and splenium of corpus callosum. Controlling for intracranial and lateral ventricle volume, the latter of which increased significantly with age, attenuated these correlations by 40% and 84%, respectively, indicating that this age-related change in callosal tract topology is significantly mediated by global atrophy and ventricular enlargement. In accordance with the “frontal ageing” hypothesis, there was a significant positive correlation between mean diffusivity (〈D〉) and age, and a significant negative correlation between fractional anisotropy (FA) and age in corpus callosum genu; correlations not seen in splenium. Significant positive correlations were also observed between 〈D〉 and age in bilateral cingulum cingulate gyri, uncinate fasciculi and right corticospinal tract. This pattern of correlations was not, however, reproduced when those subjects with significant white matter lesion load were analyzed separately from those without. These data therefore suggest that brain atrophy and white matter lesions play a significant role in driving regional patterns of age-related changes in white matter tract shape and integrity. [Copyright &y& Elsevier]

Abstract: Understanding how ageing affects brain structure is an important challenge for medical science. By allowing segmentation of fasciculi-of-interest from diffusion magnetic resonance imaging (dMRI) data, tractography provides a promising tool for assessing white matter connectivity in old age. However, the output from tractography algorithms is usually strongly dependent on the subjective location of user-specified seed points, with the result that it can be both difficult and time consuming to identify the same tract reliably in cross-sectional studies. Here we investigate whether a novel method for automatic single seed point placement based on tract shape modelling, termed probabilistic model-based neighbourhood tractography (PNT), can reliably segment the same tract from subject to subject in a non-demented cohort aged over 65 years. For the fasciculi investigated (genu and splenium of corpus callosum, cingulum cingulate gyri, corticospinal tracts and uncinate fasciculi), PNT was able to provide anatomically plausible representations of the tract in question in 70 to 90% of subjects compared with 2.5 to 60% if single seed points were simply transferred directly from standard to native space. In corpus callosum genu there was a significant negative correlation between a PNT-derived measure of tract shape similarity to a young brain reference tract and age, and a trend towards a significant negative correlation between tract-averaged fractional anisotropy and age; results that are consistent with previous dMRI studies of normal ageing. These data show that it is possible automatically to segment comparable tracts in the brains of older subjects using single seed point tractography, if the seed point is carefully chosen. [Copyright &y& Elsevier]