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Mark E. Bastin

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30

YNIMG Journal 2025 Journal Article

AI-based deformable hippocampal mesh reflects hippocampal morphological characteristics in relation to cognition in healthy older adults

  • Wonjung Park
  • Maria del C. Valdés Hernández
  • Jaeil Kim
  • Susana Muñoz Maniega
  • Fraser N. Sneden
  • Karen J. Ferguson
  • Mark E. Bastin
  • Joanna M. Wardlaw

Magnetic resonance imaging (MRI)-derived hippocampus measurements have been associated with different cognitive domains. The knowledge of hippocampal structural deformations as we age has contributed to our understanding of the overall aging process. Different morphological hippocampal shape analysis methods have been developed, but it is unclear how their principles relate and how consistent are the published results in relation to cognition in the normal elderly in the light of the new deep-learning-based (DL) state-of-the-art modeling methods. We compared results from analyzing the hippocampal morphology using manually-generated binary masks and a Laplacian- based deformation shape analysis method, with those resulting from analyzing SynthSeg-generated hippocampal binary masks using a DL method based on the PointNet architecture, in relation to different cognitive domains. Whilst most previously reported statistically significant associations were also replicated, differences were also observed due to 1) differences in the binary masks and 2) differences in sensitivity between the methods. Differences in the template mesh, number of vertices of the template mesh, and their distribution did not impact the results.

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YNIMG Journal 2023 Journal Article

Strong intercorrelations among global graph-theoretic indices of structural connectivity in the human brain

  • James W. Madole
  • Colin R. Buchanan
  • Mijke Rhemtulla
  • Stuart J. Ritchie
  • Mark E. Bastin
  • Ian J. Deary
  • Simon R. Cox
  • Elliot M. Tucker-Drob

Graph-theoretic metrics derived from neuroimaging data have been heralded as powerful tools for uncovering neural mechanisms of psychological traits, psychiatric disorders, and neurodegenerative diseases. In N = 8,185 human structural connectomes from UK Biobank, we examined the extent to which 11 commonly-used global graph-theoretic metrics index distinct versus overlapping information with respect to interindividual differences in brain organization. Using unthresholded, FA-weighted networks we found that all metrics other than Participation Coefficient were highly intercorrelated, both with each other (mean |r| = 0.788) and with a topologically-naïve summary index of brain structure (mean edge weight; mean |r| = 0.873). In a series of sensitivity analyses, we found that overlap between metrics is influenced by the sparseness of the network and the magnitude of variation in edge weights. Simulation analyses representing a range of population network structures indicated that individual differences in global graph metrics may be intrinsically difficult to separate from mean edge weight. In particular, Closeness, Characteristic Path Length, Global Efficiency, Clustering Coefficient, and Small Worldness were nearly perfectly collinear with one another (mean |r| = 0.939) and with mean edge weight (mean |r| = 0.952) across all observed and simulated conditions. Global graph-theoretic measures are valuable for their ability to distill a high-dimensional system of neural connections into summary indices of brain organization, but they may be of more limited utility when the goal is to index separable components of interindividual variation in specific properties of the human structural connectome.

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YNICL Journal 2022 Journal Article

Contribution of white matter hyperintensities to ventricular enlargement in older adults

  • Angela C.C. Jochems
  • Susana Muñoz Maniega
  • Maria del C Valdés Hernández
  • Gayle Barclay
  • Devasuda Anblagan
  • Lucia Ballerini
  • Rozanna Meijboom
  • Stewart Wiseman

Lateral ventricles might increase due to generalized tissue loss related to brain atrophy. Alternatively, they may expand into areas of tissue loss related to white matter hyperintensities (WMH). We assessed longitudinal associations between lateral ventricle and WMH volumes, accounting for total brain volume, blood pressure, history of stroke, cardiovascular disease, diabetes and smoking at ages 73, 76 and 79, in participants from the Lothian Birth Cohort 1936, including MRI data from all available time points. Lateral ventricle volume increased steadily with age, WMH volume change was more variable. WMH volume decreased in 20% and increased in remaining subjects. Over 6 years, lateral ventricle volume increased by 3% per year of age, 0.1% per mm Hg increase in blood pressure, 3.2% per 1% decrease of total brain volume, and 4.5% per 1% increase of WMH volume. Over time, lateral ventricle volumes were 19% smaller in women than men. Ventricular and WMH volume changes are modestly associated and independent of general brain atrophy, suggesting that their underlying processes do not fully overlap.

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YNICL Journal 2022 Journal Article

Longitudinal microstructural MRI markers of demyelination and neurodegeneration in early relapsing-remitting multiple sclerosis: Magnetisation transfer, water diffusion and g-ratio

  • Elizabeth N. York
  • Rozanna Meijboom
  • Michael J. Thrippleton
  • Mark E. Bastin
  • Agniete Kampaite
  • Nicole White
  • Siddharthan Chandran
  • Adam D. Waldman

INTRODUCTION: Quantitative microstructural MRI, such as myelin-sensitive magnetisation transfer ratio (MTR) or saturation (MTsat), axon-sensitive water diffusion Neurite Orientation Dispersion and Density Imaging (NODDI), and the aggregate g-ratio, may provide more specific markers of white matter integrity than conventional MRI for early patient stratification in relapsing-remitting multiple sclerosis (RRMS). The aim of this study was to determine the sensitivity of such markers to longitudinal pathological change within cerebral white matter lesions (WML) and normal-appearing white matter (NAWM) in recently diagnosed RRMS. METHODS: Seventy-nine people with recently diagnosed RRMS, from the FutureMS longitudinal cohort, were recruited to an extended MRI protocol at baseline and one year later. Twelve healthy volunteers received the same MRI protocol, repeated within two weeks. Ethics approval and written informed consent were obtained. 3T MRI included magnetisation transfer, and multi-shell diffusion-weighted imaging. NAWM and whole brain were segmented from 3D T1-weighted MPRAGE, and WML from T2-weighted FLAIR. MTR, MTsat, NODDI isotropic (ISOVF) and intracellular (ICVF) volume fractions, and g-ratio (calculated from MTsat and NODDI data) were measured within WML and NAWM. Brain parenchymal fraction (BPF) was also calculated. Longitudinal change in BPF and microstructural metrics was assessed with paired t-tests (α = 0.05) and linear mixed models, adjusted for confounding factors with False Discovery Rate (FDR) correction for multiple comparisons. Longitudinal changes were compared with test-retest Bland-Altman limits of agreement from healthy control white matter. The influence of longitudinal change on g-ratio was explored through post-hoc analysis in silico by computing g-ratio with realistic simulated MTsat and NODDI values. RESULTS: In NAWM, g-ratio and ICVF increased, and MTsat decreased over one year (adjusted mean difference = 0.007, 0.005, and -0.057 respectively, all FDR-corrected p < 0.05). There was no significant change in MTR, ISOVF, or BPF. In WML, MTsat, NODDI ICVF and ISOVF increased over time (adjusted mean difference = 0.083, 0.024 and 0.016, respectively, all FDR-corrected p < 0.05). Group-level longitudinal changes exceeded test-retest limits of agreement for NODDI ISOVF and ICVF in WML only. In silico analysis showed g-ratio may increase due to a decrease in MTsat or ISOVF, or an increase in ICVF. DISCUSSION: G-ratio and MTsat changes in NAWM over one year may indicate subtle myelin loss in early RRMS, which were not apparent with BPF or NAWM MTR. Increases in NAWM and WML NODDI ICVF were not anticipated, and raise the possibility of axonal swelling or morphological change. Increases in WML MTsat may reflect myelin repair. Changes in NODDI ISOVF are more likely to reflect alterations in water content. Competing MTsat and ICVF changes may account for the absence of g-ratio change in WML. Longitudinal changes in microstructural measures are significant at a group level, however detection in individual patients in early RRMS is limited by technique reproducibility. CONCLUSION: MTsat and g-ratio are more sensitive than MTR to early pathological changes in RRMS, but complex dependence of g-ratio on NODDI parameters limit the interpretation of aggregate measures in isolation. Improvements in technique reproducibility and validation of MRI biophysical models across a range of pathological tissue states are needed.

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YNICL Journal 2021 Journal Article

Birth weight is associated with brain tissue volumes seven decades later but not with MRI markers of brain ageing

  • Emily Wheater
  • Susan D. Shenkin
  • Susana Muñoz Maniega
  • Maria Valdés Hernández
  • Joanna M. Wardlaw
  • Ian J. Deary
  • Mark E. Bastin
  • James P. Boardman

Birth weight, an indicator of fetal growth, is associated with cognitive outcomes in early life (which are predictive of cognitive ability in later life) and risk of metabolic and cardiovascular disease across the life course. Brain health in older age, indexed by MRI features, is associated with cognitive performance, but little is known about how variation in normal birth weight impacts on brain structure in later life. In a community dwelling cohort of participants in their early seventies we tested the hypothesis that birth weight is associated with the following MRI features: total brain (TB), grey matter (GM) and normal appearing white matter (NAWM) volumes; whiter matter hyperintensity (WMH) volume; a general factor of fractional anisotropy (gFA) and peak width skeletonised mean diffusivity (PSMD) across the white matter skeleton. We also investigated the associations of birth weight with cortical surface area, volume and thickness. Birth weight was positively associated with TB, GM and NAWM volumes in later life (β ≥ 0.194), and with regional cortical surface area but not gFA, PSMD, WMH volume, or cortical volume or thickness. These positive relationships appear to be explained by larger intracranial volume, rather than by age-related tissue atrophy, and are independent of body height and weight in adulthood. This suggests that larger birth weight is linked to more brain tissue reserve in older life, rather than age-related brain structural features, such as tissue atrophy or WMH volume.

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YNICL Journal 2020 Journal Article

Computational quantification of brain perivascular space morphologies: Associations with vascular risk factors and white matter hyperintensities. A study in the Lothian Birth Cohort 1936

  • Lucia Ballerini
  • Tom Booth
  • Maria del C. Valdés Hernández
  • Stewart Wiseman
  • Ruggiero Lovreglio
  • Susana Muñoz Maniega
  • Zoe Morris
  • Alison Pattie

BACKGROUND AND PURPOSE: Perivascular Spaces (PVS), also known as Virchow-Robin spaces, seen on structural brain MRI, are important fluid drainage conduits and are associated with small vessel disease (SVD). Computational quantification of visible PVS may enable efficient analyses in large datasets and increase sensitivity to detect associations with brain disorders. We assessed the associations of computationally-derived PVS parameters with vascular factors and white matter hyperintensities (WMH), a marker of SVD. PARTICIPANTS: Community dwelling individuals (n = 700) from the Lothian Birth Cohort 1936 who had multimodal brain MRI at age 72.6 years (SD = 0.7). METHODS: We assessed PVS computationally in the centrum semiovale and deep corona radiata on T2-weighted images. The computationally calculated measures were the total PVS volume and count per subject, and the mean individual PVS length, width and size, per subject. We assessed WMH by volume and visual Fazekas scores. We compared PVS visual rating to PVS computational metrics, and tested associations between each PVS measure and vascular risk factors (hypertension, diabetes, cholesterol), vascular history (cardiovascular disease and stroke), and WMH burden, using generalized linear models, which we compared using coefficients, confidence intervals and model fit. RESULTS: In 533 subjects, the computational PVS measures correlated positively with visual PVS ratings (PVS count r = 0.59; PVS volume r = 0.61; PVS mean length r = 0.55; PVS mean width r = 0.52; PVS mean size r = 0.47). PVS size and width were associated with hypertension (OR 1.22, 95% CI [1.03 to 1.46] and 1.20, 95% CI [1.01 to 1.43], respectively), and stroke (OR 1.34, 95% CI [1.08 to 1.65] and 1.36, 95% CI [1.08 to 1.71], respectively). We found no association between other PVS measures and diabetes, hypercholesterolemia or cardiovascular disease history. Computational PVS volume, length, width and size were more strongly associated with WMH (PVS mean size versus WMH Fazekas score β = 0.66, 95% CI [0.59 to 0.74] and versus WMH volume β = 0.43, 95% CI [0.38 to 0.48]) than computational PVS count (WMH Fazekas score β = 0.21, 95% CI [0.11 to 0.3]; WMH volume β = 0.14, 95% CI [0.09 to 0.19]) or visual score. Individual PVS size showed the strongest association with WMH. CONCLUSIONS: Computational measures reflecting individual PVS size, length and width were more strongly associated with WMH, stroke and hypertension than computational count or visual PVS score. Multidimensional computational PVS metrics may increase sensitivity to detect associations of PVS with risk exposures, brain lesions and neurological disease, provide greater anatomic detail and accelerate understanding of disorders of brain fluid and waste clearance.

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YNICL Journal 2020 Journal Article

Neonatal morphometric similarity mapping for predicting brain age and characterizing neuroanatomic variation associated with preterm birth

  • Paola Galdi
  • Manuel Blesa
  • David Q. Stoye
  • Gemma Sullivan
  • Gillian J. Lamb
  • Alan J. Quigley
  • Michael J. Thrippleton
  • Mark E. Bastin

Multi-contrast MRI captures information about brain macro- and micro-structure which can be combined in an integrated model to obtain a detailed "fingerprint" of the anatomical properties of an individual's brain. Inter-regional similarities between features derived from structural and diffusion MRI, including regional volumes, diffusion tensor metrics, neurite orientation dispersion and density imaging measures, can be modelled as morphometric similarity networks (MSNs). Here, individual MSNs were derived from 105 neonates (59 preterm and 46 term) who were scanned between 38 and 45 weeks postmenstrual age (PMA). Inter-regional similarities were used as predictors in a regression model of age at the time of scanning and in a classification model to discriminate between preterm and term infant brains. When tested on unseen data, the regression model predicted PMA at scan with a mean absolute error of 0.70 ± 0.56 weeks, and the classification model achieved 92% accuracy. We conclude that MSNs predict chronological brain age accurately; and they provide a data-driven approach to identify networks that characterise typical maturation and those that contribute most to neuroanatomic variation associated with preterm birth.

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YNIMG Journal 2020 Journal Article

The effect of network thresholding and weighting on structural brain networks in the UK Biobank

  • Colin R. Buchanan
  • Mark E. Bastin
  • Stuart J. Ritchie
  • David C. Liewald
  • James W. Madole
  • Elliot M. Tucker-Drob
  • Ian J. Deary
  • Simon R. Cox

Whole-brain structural networks can be constructed using diffusion MRI and probabilistic tractography. However, measurement noise and the probabilistic nature of the tracking procedure result in an unknown proportion of spurious white matter connections. Faithful disentanglement of spurious and genuine connections is hindered by a lack of comprehensive anatomical information at the network-level. Therefore, network thresholding methods are widely used to remove ostensibly false connections, but it is not yet clear how different thresholding strategies affect basic network properties and their associations with meaningful demographic variables, such as age. In a sample of 3153 generally healthy volunteers from the UK Biobank Imaging Study (aged 44–77 years), we constructed whole-brain structural networks and applied two principled network thresholding approaches (consistency and proportional thresholding). These were applied over a broad range of threshold levels across six alternative network weightings (streamline count, fractional anisotropy, mean diffusivity and three novel weightings from neurite orientation dispersion and density imaging) and for four common network measures (mean edge weight, characteristic path length, network efficiency and network clustering coefficient). We compared network measures against age associations and found that: 1) measures derived from unthresholded matrices yielded the weakest age-associations (0. 033 ​≤ ​|β| ​≤ ​0. 409); and 2) the most commonly-used level of proportional-thresholding from the literature (retaining 68. 7% of all possible connections) yielded significantly weaker age-associations (0. 070 ​≤ ​|β| ​≤ ​0. 406) than the consistency-based approach which retained only 30% of connections (0. 140 ​≤ ​|β| ​≤ ​0. 409). However, we determined that the stringency of the threshold was a stronger determinant of the network-age association than the choice of threshold method and the two thresholding approaches identified a highly overlapping set of connections (ICC ​= ​0. 84), when matched at 70% network sparsity. Generally, more stringent thresholding resulted in more age-sensitive network measures in five of the six network weightings, except at the highest levels of sparsity (>90%), where crucial connections were then removed. At two commonly-used threshold levels, the age-associations of the connections that were discarded (mean β ​≤ ​|0. 068|) were significantly smaller in magnitude than the corresponding age-associations of the connections that were retained (mean β ​≤ ​|0. 219|, p ​< ​0. 001, uncorrected). Given histological evidence of widespread degeneration of structural brain connectivity with increasing age, these results indicate that stringent thresholding methods may be most accurate in identifying true white matter connections.

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YNIMG Journal 2019 Journal Article

Early breast milk exposure modifies brain connectivity in preterm infants

  • Manuel Blesa
  • Gemma Sullivan
  • Devasuda Anblagan
  • Emma J. Telford
  • Alan J. Quigley
  • Sarah A. Sparrow
  • Ahmed Serag
  • Scott I. Semple

Preterm infants are at increased risk of alterations in brain structure and connectivity, and subsequent neurocognitive impairment. Breast milk may be more advantageous than formula feed for promoting brain development in infants born at term, but uncertainties remain about its effect on preterm brain development and the optimal nutritional regimen for preterm infants. We test the hypothesis that breast milk exposure is associated with improved markers of brain development and connectivity in preterm infants at term equivalent age. We collected information about neonatal breast milk exposure and brain MRI at term equivalent age from 47 preterm infants (mean postmenstrual age [PMA] 29. 43 weeks, range 23. 28–33. 0). Network-Based Statistics (NBS), Tract-based Spatial Statistics (TBSS) and volumetric analysis were used to investigate the effect of breast milk exposure on white matter water diffusion parameters, tissue volumes, and the structural connectome. Twenty-seven infants received exclusive breast milk feeds for ≥75% of days of in-patient care and this was associated with higher connectivity in the fractional anisotropy (FA)-weighted connectome compared with the group who had < 75% of days receiving exclusive breast milk feeds (NBS, p = 0. 04). Within the TBSS white matter skeleton, the group that received ≥75% exclusive breast milk days exhibited higher FA within the corpus callosum, cingulum cingulate gyri, centrum semiovale, corticospinal tracts, arcuate fasciculi and posterior limbs of the internal capsule compared with the low exposure group after adjustment for PMA at birth, PMA at image acquisition, bronchopulmonary dysplasia, and chorioamnionitis (p < 0. 05). The effect on structural connectivity and tract water diffusion parameters was greater with ≥90% exposure, suggesting a dose effect. There were no significant groupwise differences in brain volumes. Breast milk feeding in the weeks after preterm birth is associated with improved structural connectivity of developing networks and greater FA in major white matter fasciculi.

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YNIMG Journal 2019 Journal Article

Hierarchical complexity of the adult human structural connectome

  • Keith Smith
  • Mark E. Bastin
  • Simon R. Cox
  • Maria C. Valdés Hernández
  • Stewart Wiseman
  • Javier Escudero
  • Catherine Sudlow

The structural network of the human brain has a rich topology which many have sought to characterise using standard network science measures and concepts. However, this characterisation remains incomplete and the non-obvious features of this topology have largely confounded attempts towards comprehensive constructive modelling. This calls for new perspectives. Hierarchical complexity is an emerging paradigm of complex network topology based on the observation that complex systems are composed of hierarchies within which the roles of hierarchically equivalent nodes display highly variable connectivity patterns. Here we test the hierarchical complexity of the human structural connectomes of a group of seventy-nine healthy adults. Binary connectomes are found to be more hierarchically complex than three benchmark random network models. This provides a new key description of brain structure, revealing a rich diversity of connectivity patterns within hierarchically equivalent nodes. Dividing the connectomes into four tiers based on degree magnitudes indicates that the most complex nodes are neither those with the highest nor lowest degrees but are instead found in the middle tiers. Spatial mapping of the brain regions in each hierarchical tier reveals consistency with the current anatomical, functional and neuropsychological knowledge of the human brain. The most complex tier (Tier 3) involves regions believed to bridge high-order cognitive (Tier 1) and low-order sensorimotor processing (Tier 2). We then show that such diversity of connectivity patterns aligns with the diversity of functional roles played out across the brain, demonstrating that hierarchical complexity can characterise functional diversity strictly from the network topology.

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YNICL Journal 2018 Journal Article

Prenatal methadone exposure is associated with altered neonatal brain development

  • Victoria J. Monnelly
  • Devasuda Anblagan
  • Alan Quigley
  • Manuel Blesa Cabez
  • E. Sarah Cooper
  • Helen Mactier
  • Scott I. Semple
  • Mark E. Bastin

Methadone is used for medication-assisted treatment of heroin addiction during pregnancy. The neurodevelopmental outcome of children with prenatal methadone exposure can be sub-optimal. We tested the hypothesis that brain development is altered among newborn infants whose mothers were prescribed methadone. 20 methadone-exposed neonates born after 37weeks' postmenstrual age (PMA) and 20 non-exposed controls underwent diffusion MRI at mean PMA of 39+2 and 41+1 weeks, respectively. An age-optimized Tract-based Spatial Statistics (TBSS) pipeline was used to perform voxel-wise statistical comparison of fractional anisotropy (FA) data between exposed and non-exposed neonates. Methadone-exposed neonates had decreased FA within the centrum semiovale, inferior longitudinal fasciculi (ILF) and the internal and external capsules after adjustment for GA at MRI (p<0. 05, TFCE corrected). Median FA across the white matter skeleton was 12% lower among methadone-exposed infants. Mean head circumference (HC) z-scores were lower in the methadone-exposed group (−0. 52 (0. 99) vs 1. 15 (0. 84), p<0. 001); after adjustment for HC z-scores, differences in FA remained in the anterior and posterior limbs of the internal capsule and the ILF. Polydrug use among cases was common. Prenatal methadone exposure is associated with microstructural alteration in major white matter tracts, which is present at birth and is independent of head growth. Although the findings cannot be attributed to methadone per se, the data indicate that further research to determine optimal management of opioid use disorder during pregnancy is required. Future studies should evaluate childhood outcomes including infant brain development and long-term neurocognitive function.

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YNICL Journal 2015 Journal Article

Tract shape modeling detects changes associated with preterm birth and neuroprotective treatment effects

  • Devasuda Anblagan
  • Mark E. Bastin
  • Sarah Sparrow
  • Chinthika Piyasena
  • Rozalia Pataky
  • Emma J. Moore
  • Ahmed Serag
  • Alastair Graham Wilkinson

Preterm birth is associated with altered connectivity of neural circuits. We developed a tract segmentation method that provides measures of tract shape and integrity (probabilistic neighborhood tractography, PNT) from diffusion MRI (dMRI) data to test the hypotheses: 1) preterm birth is associated with alterations in tract topology (R), and tract-averaged mean diffusivity (〈D〉) and fractional anisotropy (FA); 2) neural systems are separable based on tract-averaged dMRI parameters; and 3) PNT can detect neuroprotective treatment effects. dMRI data were collected from 87 preterm infants (mean gestational age 29(+1) weeks, range 23(+2) -34(+6)) at term equivalent age and 24 controls (mean gestational age 39(+6) weeks). PNT was used to segment eight major fasciculi, characterize topology, and extract tract-averaged〈D〉and FA. Tract topology was altered by preterm birth in all tracts except the splenium (p < 0.05, false discovery rate [FDR] corrected). After adjustment for age at scan, tract-averaged〈D〉was increased in the genu and splenium, right corticospinal tract (CST) and the left and right inferior longitudinal fasciculi (ILF) in preterm infants compared with controls (p < 0.05, FDR), while tract-averaged FA was decreased in the splenium and left ILF (p < 0.05, FDR). Specific fasciculi were separable based on tract-averaged〈D〉and FA values. There was a modest decrease in tract-averaged〈D〉in the splenium of preterm infants who had been exposed to antenatal MgSO4 for neuroprotection (p = 0.002). Tract topology is a biomarker of preterm brain injury. The data provide proof of concept that tract-averaged dMRI parameters have utility for evaluating tissue effects of perinatal neuroprotective strategies.

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YNICL Journal 2015 Journal Article

White matter integrity and its association with affective and interpersonal symptoms in borderline personality disorder

  • Heather C. Whalley
  • Thomas Nickson
  • Merrick Pope
  • Katie Nicol
  • Liana Romaniuk
  • Mark E. Bastin
  • Scott I. Semple
  • Andrew M. McIntosh

BACKGROUND: Borderline personality disorder (BPD) is a severe psychiatric disorder involving a range of symptoms including marked affective instability and disturbances in interpersonal interactions. Neuroimaging studies are beginning to provide evidence of altered processing in fronto-limbic network deficits in the disorder, however, few studies directly examine structural connections within this circuitry together with their relation to proposed causative processes and clinical features. METHODS: In the current study, we investigated whether individuals with BPD (n = 20) have deficits in white matter integrity compared to a matched group of healthy controls (n = 18) using diffusion tensor MRI (DTI). We hypothesized that the BPD group would have decreased fractional anisotropy (FA), a measure of white matter integrity, compared to the controls in white matter tracts connecting frontal and limbic regions, primarily the cingulum, fornix and uncinate fasciculus. We also investigated the extent to which any such deficits related to childhood adversity, as measured by the childhood trauma questionnaire, and symptom severity as measured by the Zanarini rating scale for BPD. RESULTS: We report decreased white matter integrity in BPD versus controls in the cingulum and fornix. There were no significant relationships between FA and measures of childhood trauma. There were, however, significant associations between FA in the cingulum and clinical symptoms of anger, and in the fornix with affective instability, and measures of avoidance of abandonment from the Zanarini rating scale. CONCLUSIONS: We report deficits within fronto-limbic connections in individuals with BPD. Abnormalities within the fornix and cingulum were related to severity of symptoms and highlight the importance of these tracts in the pathogenesis of the disorder.

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