Derek K Jones

University of South Wales, Понтиприте, Wales, United Kingdom

Are you Derek K Jones?

Claim your profile

Publications (85)410.47 Total impact

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Graph theory (GT) is a powerful framework for quantifying topological features of neuroimaging-derived functional and structural networks. However, false positive (FP) connections arise frequently and influence the inferred topology of networks. Thresholding is often used to overcome this problem, but an appropriate threshold often relies on a priori assumptions, which will alter inferred network topologies. Four common network metrics (global efficiency, mean clustering coefficient, mean betweenness and smallworldness) were tested using a model tractography dataset. It was found that all four network metrics were significantly affected even by just one FP. Results also show that thresholding effectively dampens the impact of FPs, but also adds significant bias to network metrics. In a larger number (n=248) of tractography datasets, statistics were computed across random group permutations for a range of thresholds, revealing that statistics for network metrics varied significantly more than for non-network metrics (i.e., number of streamlines and number of edges). Varying degrees of network atrophy were introduced artificially to half the datasets, to test sensitivity to genuine group differences. For some network metrics, this atrophy was detected as significant (p<0.05, determined using permutation testing) only across a limited range of thresholds. We propose a multi-threshold permutation correction (MTPC) method, based on the cluster-enhanced permutation correction approach, to identify sustained significant effects across clusters of thresholds. This approach minimises requirements to determine a single threshold a priori. We demonstrate improved sensitivity of MTPC-corrected metrics to genuine group effects compared to an existing approach and demonstrate the use of MTPC on a previously published network analysis of tractography data derived from a clinical population. In conclusion, we show that there are large biases and instability induced by thresholding, making statistical comparisons of network metrics difficult. However, by testing for effects across multiple thresholds using MTPC, true group differences can be robustly identified. Copyright © 2015. Published by Elsevier Inc.
    NeuroImage 05/2015; 118:313–333. DOI:10.1016/j.neuroimage.2015.05.011 · 6.13 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Schizophrenia is often regarded as a "dysconnectivity" disorder and recent work using graph theory has been used to better characterize dysconnectivity of the structural connectome in schizophrenia. However, there are still little data on the topology of connectomes in less severe forms of the condition. Such analysis will identify topological markers of less severe disease states and provide potential predictors of further disease development. Individuals with psychotic experiences (PEs) were identified from a population-based cohort without relying on participants presenting to clinical services. Such individuals have an increased risk of developing clinically significant psychosis. 123 individuals with PEs and 125 controls were scanned with diffusion-weighted MRI. Whole-brain structural connectomes were derived and a range of global and local GT-metrics were computed. Global efficiency and density were significantly reduced in individuals with PEs. Local efficiency was reduced in a number of regions, including critical network hubs. Further analysis of functional subnetworks showed differential impairment of the default mode network. An additional analysis of pair-wise connections showed no evidence of differences in individuals with PEs. These results are consistent with previous findings in schizophrenia. Reduced efficiency in critical core hubs suggests the brains of individuals with PEs may be particularly predisposed to dysfunction. The absence of any detectable effects in pair-wise connections illustrates that, at less severe stages of psychosis, white-matter alterations are subtle and only manifest when examining network topology. This study indicates that topology could be a sensitive biomarker for early stages of psychotic illness. Hum Brain Mapp, 2015.© 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
    Human Brain Mapping 04/2015; 36:2629–2643. DOI:10.1002/hbm.22796 · 6.92 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: A comprehensive image-based characterization of white matter should include the ability to quantify myelin and axonal attributes irrespective of the complexity of fibre organization within the voxel. While progress has been made with diffusion MRI-based approaches to measure axonal morphology, to date available myelin metrics simply assign a single scalar value to the voxel, reflecting some form of average of its constituent fibres. Here, a new experimental framework that combines diffusion MRI and relaxometry is introduced. It provides, for the first time, the ability to assign to each unique fibre system within a voxel, a unique value of the longitudinal relaxation time, T1 , which is largely influenced by the myelin content. We demonstrate the method through simulations, in a crossing fibres phantom, in fixed brains and in vivo. The method is capable of recovering unique values of T1 for each fibre population. The ability to extract fibre-specific relaxometry properties will provide enhanced specificity and, therefore, sensitivity to differences in white matter architecture, which will be invaluable in many neuroimaging studies. Further the enhanced specificity should ultimately lead to earlier diagnosis and access to treatment in a range of white matter diseases where axons are affected. Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
    Magnetic Resonance in Medicine 03/2015; DOI:10.1002/mrm.25644 · 3.40 Impact Factor
  • Source
    Miriam Cooper, Anita Thapar, Derek K. Jones
    [Show abstract] [Hide abstract]
    ABSTRACT: This analysis examined hypothesised associations between microstructural attributes in specific white matter (WM) tracts selected a priori and measures of clinical variability in adolescents with a diagnosis of attention deficit hyperactivity disorder (ADHD). Firstly, associations were explored between WM microstructure and ADHD severity in the subgenual cingulum. Secondly, to ensure that tract-specific approaches afforded enhanced rather than differential sensitivity, associations were measured between WM microstructure and autistic traits in the right corticospinal tract based on results of a previously-published voxelwise analysis. 40 right-handed males aged 14-18 years (19 with DSM-IV combined type ADHD and 21 healthy controls) underwent a 60 direction diffusion MRI scan. Clinical ADHD and autism variation were assessed by validated questionnaires. Deterministic tractography based on spherical deconvolution methods was used to map the subgenual cingulum and corticospinal tract. Fractional anisotropy was positively correlated and radial diffusivity was negatively correlated with a) ADHD severity in the left subgenual cingulum and b) autistic traits in the inferior segment of the right corticospinal tract. No case-control differences were found. Results shed light on possible anatomical correlates of ADHD severity and autistic symptoms in pathways which may be involved in the ADHD phenotype. They provide further evidence that tract-specific approaches may a) reveal associations between microstructural metrics and indices of phenotypic variability which would not be detected using voxelwise approaches, and b) provide improved rather than differential sensitivity compared to voxelwise approaches.
    02/2015; 1064. DOI:10.1016/j.nicl.2015.02.012
  • [Show abstract] [Hide abstract]
    ABSTRACT: The fornix and hippocampus are critical to recollection in the healthy human brain. Fornix degeneration is a feature of aging and Alzheimer's disease. In the presence of fornix damage in mild cognitive impairment (MCI), a recognized prodrome of Alzheimer's disease, recall shows greater dependence on other tracts, notably the parahippocampal cingulum (PHC). The current aims were to determine whether this shift is adaptive and to probe its relationship to cholinergic signaling, which is also compromised in Alzheimer's disease. Twenty-five human participants with MCI and 20 matched healthy volunteers underwent diffusion MRI, behavioral assessment, and volumetric measurement of the basal forebrain. In a regression model for recall, there was a significant group × fornix interaction, indicating that the association between recall and fornix structure was weaker in patients. The opposite trend was present for the left PHC. To further investigate this pattern, two regression models were generated to account for recall performance: one based on fornix microstructure and the other on both fornix and left PHC. The realignment to PHC was positively correlated with free recall but not non-memory measures, implying a reconfiguration that is beneficial to residual memory. There was a positive relationship between realignment to PHC and basal forebrain gray matter volume despite this region demonstrating atrophy at a group level, i.e., the cognitive realignment to left PHC was most apparent when cholinergic areas were relatively spared. Therefore, cholinergic systems appear to enable adaptation to injury even as they degenerate, which has implications for functional restoration. Copyright © 2015 Ray et al.
    The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 01/2015; 35(2):739-47. DOI:10.1523/JNEUROSCI.3617-14.2015 · 6.75 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Background White matter microstructure alterations of limbic and reward pathways have been reported repeatedly for depressive episodes in major depressive disorder (MDD) and bipolar disorder (BD). However, findings during remission are equivocal. It was the aim of this study to investigate if white matter microstructure changes during the time course of clinical remission. Methods Fifteen depressed patients (11 MDD, 4 BD) underwent diffusion-weighted MRI both during depression, and during remission following successful antidepressive treatment (average time interval between scans=6 months). Fractional anisotropy (FA) was sampled along reconstructions of the supero-lateral medial forebrain bundle (slMFB), the cingulum bundle (CB), the uncinate fasciculus (UF), the parahippocampal cingulum (PHC) and the fornix. Repeated measures ANCOVAs controlling for the effect of age were calculated for each tract. Results There was a significant main effect of time (inter-scan interval) for mean-FA for the right CB and for the left PHC. For both pathways there was a significant time×age interaction. In the right CB, FA increased in younger patients, while FA decreased in older patients. In the left PHC, a reverse pattern was seen. FA changes in the right CB correlated positively with symptom reductions. Mean-FA of UF, slMFB and fornix did not change between the two time points. Limitations All patients were medicated, sample size, and lack of control group. Conclusions Right CB and left PHC undergo age-dependent plastic changes during the course of remission and may serve as a state marker in depression. UF, slMFB and FO microstructure remains stable.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Transection of the nonhuman primate fornix has been shown to impair learning of configurations of spatial features and object-in-scene memory. Although damage to the human fornix also results in memory impairment, it is not known whether there is a preferential involvement of this white-matter tract in spatial learning, as implied by animal studies. Diffusion-weighted MR images were obtained from healthy participants who had completed versions of a task in which they made rapid same/different discriminations to two categories of highly visually similar stimuli: (1) virtual reality scene pairs; and (2) face pairs. Diffusion-MRI measures of white-matter microstructure [fractional anisotropy (FA) and mean diffusivity (MD)] and macrostructure (tissue volume fraction, f) were then extracted from the fornix of each participant, which had been reconstructed using a deterministic tractography protocol. Fornix MD and f measures correlated with scene, but not face, discrimination accuracy in both discrimination tasks. A complementary voxelwise analysis using tract-based spatial statistics suggested the crus of the fornix as a focus for this relationship. These findings extend previous reports of spatial learning impairments after fornix transection in nonhuman primates, critically highlighting the fornix as a source of interindividual variation in scene discrimination in humans.
    The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 09/2014; 34(36):12121-6. DOI:10.1523/JNEUROSCI.0026-14.2014 · 6.75 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: White matter microstructure alterations of limbic and reward pathways have been reported repeatedly for depressive episodes in major depressive disorder (MDD) and bipolar disorder (BD). However, findings during remission are equivocal. It was the aim of this study to investigate if white matter microstructure changes during the time course of clinical remission.
    Journal of Affective Disorders 08/2014; 170C:143-149. DOI:10.1016/j.jad.2014.08.031 · 3.71 Impact Factor
  • Source
  • Source
    Alzheimer's and Dementia 07/2014; 10(4):P384. DOI:10.1016/j.jalz.2014.05.457 · 17.47 Impact Factor
  • Proceedings of the International Society for Magnetic Resonance in Medicine, Milan, Italy; 05/2014
  • Source
    Miriam Cooper, Anita Thapar, Derek K Jones
    [Show abstract] [Hide abstract]
    ABSTRACT: Traits of autism spectrum disorder (ASD) in children with attention-deficit/hyperactivity disorder (ADHD) have previously been found to index clinical severity. This study examined the association of ASD traits with diffusion parameters in adolescent males with ADHD (n = 17), and also compared WM microstructure relative to controls (n = 17). Significant associations (p < 0.05, corrected) were found between fractional anisotropy/radial diffusivity and ASD trait severity (positive and negative correlations respectively), mostly in the right posterior limb of the internal capsule/corticospinal tract, right cerebellar peduncle and the midbrain. No case-control differences were found for the diffusion parameters investigated. This is the first report of a WM microstructural signature of autistic traits in ADHD. Thus, even in the absence of full disorder, ASD traits may index a distinctive underlying neurobiology in ADHD.
    Journal of Autism and Developmental Disorders 05/2014; 44(11). DOI:10.1007/s10803-014-2131-9 · 3.06 Impact Factor
  • Schizophrenia Research 04/2014; 153:S207. DOI:10.1016/S0920-9964(14)70600-0 · 4.43 Impact Factor
  • Proceedings of the International Society for Magnetic Resonance in Medicine, Milan, Italy; 04/2014
  • Magnetic Resonance in Medicine 03/2014; 71(3). DOI:10.1002/mrm.25160 · 3.40 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Diffusion MRI is used widely to probe microstructural alterations in neurological and psychiatric disease. However, ageing and neurodegeneration are also associated with atrophy, which leads to artefacts through partial volume effects due to cerebrospinal-fluid contamination (CSFC). The aim of this study was to explore the influence of CSFC on apparent microstructural changes in mild cognitive impairment (MCI) at several spatial levels: individually reconstructed tracts; at the level of a whole white matter skeleton (tract-based spatial statistics); and histograms derived from all white matter. 25 individuals with MCI and 20 matched controls underwent diffusion MRI. We corrected for CSFC using a post-acquisition voxel-by-voxel approach of free-water elimination. Tracts varied in their susceptibility to CSFC. The apparent pattern of tract involvement in disease shifted when correction was applied. Both spurious group differences, driven by CSFC, and masking of true differences were observed. Tract-based spatial statistics were found to be robust across much of the skeleton but with some localised CSFC effects. Diffusivity measures were affected disproportionately in MCI, and group differences in fornix microstructure were exaggerated. Group differences in white matter histogram measures were also partly driven by CSFC. For diffusivity measures, up to two thirds of observed group differences were due to CSFC. Our results demonstrate that CSFC has an impact on quantitative differences between MCI and controls. Furthermore, it affects the apparent spatial pattern of white matter involvement. Free-water elimination provides a step towards disentangling intrinsic and volumetric alterations in individuals prone to atrophy.
    NeuroImage 02/2014; 92. DOI:10.1016/j.neuroimage.2014.01.031 · 6.13 Impact Factor
  • Source
  • Proceedings of the International Society for Magnetic Resonance in Medicine, Milan, Italy; 01/2014
  • [Show abstract] [Hide abstract]
    ABSTRACT: Huntington's disease (HD) is an autosominal dominant neurodegenerative condition that leads to progressive loss of motor and cognitive functions. Early symptoms in HD include subtle executive dysfunction related to white and grey matter loss in cortico-striatal-thalamic loops. There is no cure for HD and hence a significant need for early intervention with the potential to delay the clinical onset of the disease.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Fundamental to increasing our understanding of the role of white matter microstructure in normal/abnormal function in the living human is the development of MR-based metrics that provide increased specificity to distinct attributes of the white matter(e.g., local fibre architecture, axon morphology, myelin content). In recent years, different approaches have been developed to enhance this specificity, and the Tractometry framework was introduced to combine the resulting multi-parametricdata for a comprehensive assessment of white matter properties. The present work exploits that framework to characterize the statistical properties, specifically the variance and covariance, of these advanced microstructural indices across the major white matter pathways, blackwith the aim of giving clear indications on the preferred metric(s) given the specific research question. A cohort of healthy subjects was scanned with a protocol that combined multi-component relaxometry with conventional and advanced diffusion MRI acquisitions to build the first comprehensive MRI atlas of white matter microstructure. The mean and standard deviation of the different metrics were analysed in order to understand how they vary across different brain regions/individuals and the correlation between them. Characterizing the fibre architectural complexity (in terms of number of fibre populations in a voxel) provides clear insights into correlation/lack of correlation between the different metrics and explains why DT-MRI is a good model for white matter only some of the time. The study also identifies the metrics that account for the largest inter-subject variability and reports the minimal sample size required to detect differences in means, blackshowing that, on the other hand, conventional DT-MRI indices might still be the safest choice in many contexts.
    NeuroImage 12/2013; 89. DOI:10.1016/j.neuroimage.2013.12.003 · 6.13 Impact Factor

Publication Stats

8k Citations
410.47 Total Impact Points

Institutions

  • 2009–2015
    • University of South Wales
      Понтиприте, Wales, United Kingdom
  • 2007–2015
    • Cardiff University
      • School of Psychology
      Cardiff, Wales, United Kingdom
  • 2013
    • University of Bristol
      • School of Experimental Psychology
      Bristol, England, United Kingdom
  • 2000–2007
    • King's College London
      • • Department of Clinical Neuroscience
      • • Institute of Psychiatry
      Londinium, England, United Kingdom
  • 2006
    • National Institutes of Health
      • Section on Tissue Biophysics and Biomimetics
      Maryland, United States
  • 2004–2005
    • National Institute of Child Health and Human Development
      베서스다, Maryland, United States
  • 1999
    • University of Leicester
      Leiscester, England, United Kingdom