White Matter Tractography Research Articles

Structural network differences in chronic musculoskeletal pain: Beyond fractional anisotropy

Chronic musculoskeletal pain is a condition that influences central nervous system structure. In this study, we combined novel structural neuroimaging techniques, using well-validated software packages including FSL, Mrtrix3, and DSI Studio, to characterize brain grey (GM) and white matter (WM) differences in chronic musculoskeletal pain participants (n = 74), compared to age-matched pain-free controls (n = 31). In participants with chronic pain, we identified significantly higher volume in subcortical GM structures using voxel-based morphometry (FSLVBM). These differences were most prominent in the caudate, amygdala, and the hippocampus. At the same time, volume was lower in the dorsolateral prefrontal cortex, as well as the primary motor and sensory regions in patients with chronic pain. To delineate WM microstructural differences of neuronal (e.g., activity-dependent myelin remodeling) and non-neuronal (e.g., neuroinflammation) origins, we utilized Mrtrix3 software pipelines to investigate WM fiber complexity, density, and cross-section. Whole-brain analyses revealed lower WM fiber complexity within the corpus callosum and the anterior limb of the left internal capsule. Whole brain and region of interest analyses revealed fiber complexity differences within the salience and the sensorimotor networks. In contrast, we detected non-neuronal white matter density differences within the dorsal attention network: density was lower in the inferior fronto-occipital fasciculus and the splenium of the corpus callosum in chronic musculoskeletal pain. Consistent with the involvement of the dorsal attention network, WM tractography analysis, conducted with DSI Studio and Network Based Statistics, revealed higher connectivity from the superior parietal lobule to the hippocampus in patients with chronic pain. No differences were detected in measures of fiber cross-section, suggesting the absence of neuronal degeneration in chronic pain. The combination of multiple neuroimaging techniques in this study offers a unique window into the structural differences within the chronic pain brain and provides the first evidence of microstructural variations in fiber complexity and density.

SlicerDMRI: Open Source Diffusion MRI Software for Brain Cancer Research.

Diffusion MRI (dMRI) is the only noninvasive method for mapping white matter connections in the brain. We describe SlicerDMRI, a software suite that enables visualization and analysis of dMRI for neuroscientific studies and patient-specific anatomic assessment. SlicerDMRI has been successfully applied in multiple studies of the human brain in health and disease, and here, we especially focus on its cancer research applications. As an extension module of the 3D Slicer medical image computing platform, the SlicerDMRI suite enables dMRI analysis in a clinically relevant multimodal imaging workflow. Core SlicerDMRI functionality includes diffusion tensor estimation, white matter tractography with single and multi-fiber models, and dMRI quantification. SlicerDMRI supports clinical DICOM and research file formats, is open-source and cross-platform, and can be installed as an extension to 3D Slicer (www.slicer.org). More information, videos, tutorials, and sample data are available at dmri.slicer.org Cancer Res; 77(21); e101-3. ©2017 AACR.

A structural motor network correlates with motor function and not impairment post stroke.

Combining structural and functional magnetic resonance imaging may provide insight into how residual motor networks contribute to motor outcomes post-stroke. The purpose of this study was to examine whether a structural motor network (SMN), generated with fMRI guided diffusion-based tractography, relates to motor function post-stroke. Twenty-seven individuals with mild to moderate upper limb impairment post stroke underwent diffusion magnetic resonance imaging. A bilateral motor network mask guided white matter tractography for each participant. Fractional anisotrophy (FA) was calculated for the SMN and corticospinal tracts (CST). The Wolf Motor Function Test (WMFT) rate and Fugl-Meyer Upper Limb (FM) tests characterized arm function and impairment respectively. The SMN and ipsilesional CST together explained approximately 35% of the variance in paretic arm function (WMFT-rate p=0.006). This study demonstrates that a broader motor network, like the SMN, is functionally meaningful. Given that the motor network is widely distributed, the proposed SMN warrants further investigation as a potential adjunct biomarker to characterize recovery potential after stroke.

White Matter Connectivity Pattern Associate with Characteristics of Scalp EEG Signals.

The rhythm of electroencephalogram (EEG) depends on the neuroanatomical-based parameters such as white matter (WM) connectivity. However, the impacts of these parameters on the specific characteristics of EEG have not been clearly understood. Previous studies demonstrated that, these parameters contribute the inter-subject differences of EEG during performance of specific task such as motor imagery (MI). Though researchers have worked on this phenomenon, the idea is yet to be understood in terms of the mechanism that underlies such differences. Here, to tackle this issue, we began our investigations by first examining the structural features related to scalp EEG characteristics, which are event-related desynchronizations (ERDs), during MI using diffusion MRI. Twenty-four right-handed subjects were recruited to accomplish MI tasks and MRI scans. Based on the high spatial resolution of the structural and diffusion images, the motor-related WM links, such as basal ganglia (BG)-primary somatosensory cortex (SM1) pathway and supplementary motor area (SMA)-SM1 connection, were reconstructed by using probabilistic white matter tractography. Subsequently, the relationships of WM characteristics with EEG signals were investigated. These analyses demonstrated that WM pathway characteristics, including the connectivity strength and the positional characteristics of WM connectivity on SM1 (defined by the gyrus-sulcus ratio of connectivity, GSR), have a significant impact on ERDs when doing MI. Interestingly, the high GSR of WM connections between SM1 and BG were linked to the better ERDs. These results therefore, indicated that the connectivity in the gyrus of SM1 interacted with MI network which played the critical role for the scalp EEG signal extraction of MI to a great extent. The study provided the coupling mechanism between structural and dynamic physiological features of human brain, which would also contribute to understanding individual differences of EEG in MI-brain computer interface.

The BDNF Val66Met Polymorphism Affects the Vulnerability of the Brain Structural Network.

Val66Met, a naturally occurring polymorphism in the human brain-derived neurotrophic factor (BDNF) gene resulting in a valine (Val) to methionine (Met) substitution at codon 66, plays an important role in neuroplasticity. While the effect of the BDNF Val66Met polymorphism on local brain structures has previously been examined, its impact on the configuration of the graph-based white matter structural networks is yet to be investigated. In the current study, we assessed the effect of the BDNF polymorphism on the network properties and robustness of the graph-based white matter structural networks. Graph theory was employed to investigate the structural connectivity derived from white matter tractography in two groups, Val homozygotes (n = 18) and Met-allele carriers (n = 55). Although there were no differences in the global network measures including global efficiency, local efficiency, and modularity between the two genotype groups, we found the effect of the BDNF Val66Met polymorphism on the robustness properties of the white matter structural networks. Specifically, the white matter structural networks of the Met-allele carrier group showed higher vulnerability to targeted removal of central nodes as compared with those of the Val homozygote group. These findings suggest that the central role of the BDNF Val66Met polymorphism in regards to neuroplasticity may be associated with inherent differences in the robustness of the white matter structural network according to the genetic variants. Furthermore, greater susceptibility to brain disorders in Met-allele carriers may be understood as being due to their limited stability in white matter structural connectivity.

34 A lesion map of secondary bipolar disorder

Objective Bipolar Disorder (BPD) is a severe mood disorder, affecting 1.5%–4.4% of the population, and manifesting as an episodic, recurrent disturbance of mood, sleep, and behaviour. Secondary BPD (SBPD) develops following a brain insult, and is traditionally associated with right frontal lobe lesions. Yet, evidence supporting this association is mostly anecdotal. Here, we use two methodologies to study the neuroanatomy of SBPD: a systematic review of SBPD cases published in the literature, and reconstitution of brain lesions from a cohort of patients with SBPD in a single 3D template brain. Method Systematic search of pubmed and WebOfScience for SBPD. For the lesion-map, data were collected from 16 consecutive patients (6 women, 10 men, mean age 60,75±14,27 years) with SBPD developing after an MRI-documented right-sided brain-lesion. For each scan we selected the sequence (T1, T2, or FLAIR) providing the best lesion discrimination. Lesions were manually segmented using MITK software.1 After segmentation, each scan was co-registered onto a template reference brain2 using 3DSlicer software.3 Co-registration applies a transformation vector along the three axes of the source image, such that its voxels match the reference brain voxels to the highest possible degree. The resulting transformation vector was then applied to the image of each segmented lesion, and all the co-registered lesions were overlapped on the template brain scan (Automated anatomical labelling atlas or John Hopkins University white matter tractography Atlas for gray- and white-matter analysis, respectively). Results 1476 articles were found in literature review, with 207 eligible cases, including 193 with focal brain lesions, mostly right-sided (84.5%) and more rarely left-sided (34.7%). Lesions were overrepresented in the frontal and temporal lobes bilaterally. In the 3D lesion-map, lesions were spread over the right hemisphere, with highest overlap in a medial area of the superior frontal gyrus (6 patients). Grey-matter quantitative mapping showed that the right superior frontal gyrus right anterior cingulate and supramarginal gyrus and right insula were lesioned in the highest number of patients (respectively 8, 7 and 6 patients). White-matter analysis highlighted the right superior longitudinal fasciculus and superior corona radiata (6 patients each), anterior corona radiata and body of corpus callosum (5 patients each). Conclusion Our systematic review confirmed that right-sided frontotemporal lesions predominate in SBPD. In our cohort lesions converged on areas of the right executive control and anterior salience networks. Both have been implicated in the neurophysiology of primary BPD.4,5

Using magnetic resonance imaging to visualize the brain in chronic pain.

The development of neuroimaging has revolutionized our understanding of the brain’s instrumental role in pain perception. Magnetic resonance imaging–based methods have provided noninvasive access to visualize the brain in awake, feeling humans. Common techniques include functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging to assess white matter (diffusion tensor imaging and tractography) and grey matter (volumetric, cortical thickness analyses) (Fig. 1). Each of these techniques capitalizes on biological properties of the tissues to generate contrast in the image. In fMRI, detection of brain function is derived from neurovascular coupling mechanisms in which neural activity drives changes in local blood flow that can be detected because of the difference in magnetic properties between oxygenated (oxy Hb) and deoxygenated hemoglobin (deoxy Hb).1 In diffusion imaging, restricted (white matter) vs unrestricted (eg, cerebral spinal fluid) diffusion of water has different magnetic properties that provide contrast in the image and provide details about the tissue architecture.8 These techniques do not provide a direct measure of neural functioning or anatomical structure unlike neurophysiological recordings or tracer methodologies.1,8 Neuroimaging can evaluate the engagement of brain regions during pain,5,9 the impact of context (eg, attentional state),2 and how these regions interact and organize into static and dynamic networks.9,10 fMRI can be used to study responses to stimulus-evoked acute pain, while analysis of activity during task-free “resting state” can identify aberrant intrinsic functioning and spontaneous activity in chronic pain patients. For example, studies have shown that brain connectivity in regions of the salience and default mode brain networks is abnormal in chronic back pain patients,3,7 with partial restoration after treatment.3 Peripheral nerve and central nervous system white matter can be assessed using diffusion-weighted imaging and diffusion tensor imaging. Tractography can be used to delineate pathways and quantify abnormalities in chronic pain patients and with group-based analyses such as tract-based spatial statistics with diffusion metrics (fractional anisotropy, axial, radial, and mean diffusivity) indicative of white matter integrity, demyelination, neuroinflammation, and edema.6 Diffusion abnormalities correspond to pain outcomes and pain severity.5 Grey matter assessment, such as cortical thickness analysis or voxel-based morphometry, can elucidate the relationship between pain severity and treatment outcomes and grey matter abnormalities (eg, due to changes in neuronal size or number, synaptogenesis, dendritic branching, axon sprouting, synaptic pruning, neuronal cell death, alterations in vasculature, and the size/number of glial cells).5 For example, gray matter volumes of the amygdala and hippocampal brain in sub-acute back pain patients predict risk for chronic pain.11 Some imaging findings are commonly seen across diverse chronic pain conditions and others do not generalize as they are related to specific disease states. Recent advances in neuroimaging are applying machine learning to predict treatment outcomes in chronic pain patients to inform prognostics for personalized pain management. Paralleling this work, it is imperative to consider the ethical and legal implications of using brain imaging for diagnostics.4

WHITE MATTER FRACTIONAL ANISOTROPY ANALYSIS OF BEHAVIOURAL AND COGNITIVE DYSEXECUTIVE SYNDROMES IN AMNESTIC MILD COGNITIVE IMPAIRMENT AND ALZHEIMER'S DISEASE: A MEXICAN PILOT STUDY

Impairment in executive functions (EF) can appear early in the course of Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI). Dysexecutive syndromes can be divided into behavioural and cognitive components (1), which can coexist or occur independently, and have been linked to alterations in specific neural pathways (2), that can be analysed measuring the fractional anisotropy (FA) of white matter using Diffusion Tensor Imaging (DTI) MRI studies (3). We included 10 AD patients, 10 aMCI patients and 10 elderly controls. Behavioural disturbances were assessed using a cross-culturally adapted version of the Behavioural Dysexecutive Syndrome Inventory (1); cognitive impairment was measured using EF psychological tests. We used the FSL software to examine DTI data in 3 tesla MRI, measuring the FA of 60 white-matter tracts identified by the ICBM-DTI-81 and JHU white-matter tractography atlases (Figure 1). We analysed the statistical differences of mean FA values of tracts between groups. The associations between FA and dysexecutive disturbances were sought. There were no statistical differences between groups' age (p= 0.182), sex (p= 1.0) or academic attainment (p= 0.89) distribution; only in MMSE mean scores by group (p= 0.001). Associations between behavioral disturbances and tracts' FA values different from controls, and the significant correlation indexes between FA values and performance in EF tests are shown in Table 1. In this pilot study, we identified relationships between white-matter integrity and EF's behavioral and cognitive components. We found associations that are consistent with those reported by other authors, but some of our findings have not been reported and can't be supported by current evidence (i.e. medial lemniscus). It's advisable to include more subjects and to refine DTI data analysis in order to get better information on the micro-structural neural underpinnings of these syndromes. 1. Godefroy, O. et al. (2010). Ann. Neurol., 68, 855–864 2. Ardila, A. (2013). J. Neurol. Disord., 3. Teipel, S.J. et al. (2014). Eur. Arch. Psychiatry Clin. Neurosci., 264, 467–483. Skeletonized image of mean FA values of the studied groups.

Building connectomes using diffusion MRI: why, how and but.

Why has diffusion MRI become a principal modality for mapping connectomes in vivo? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI‐based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments.

Integration of Functional MRI and White Matter Tractography in CyberKnife Radiosurgery.

Purpose:To investigate the efficacy of the integration of functional magnetic resonance imaging and diffusion-tensor imaging tractography data into CyberKnife radiosurgery for intracranial tumor management.Materials and Methods:Functional neuroimaging, anatomical magnetic resonance imaging, and computed tomography images of patients with brain lesions in critical areas were acquired before radiosurgery. The acquired data sets were coregistered using the MIM image fusion software module and then were imported into the CyberKnife Robotic Radiosurgery System (Multiplan 4.0.2) for delineating the target, organs at risk, and possible nearby functionally relevant cortical and subcortical areas. Radiation dose distributions with and without the functionally relevant cortical and subcortical areas into the optimization process were developed and compared.Results:There were significant differences between the treatment plans with and without the functionally relevant cortical and subcortical areas into the optimization process. An average 22.71% reduction in the maximum dose to functional areas was observed. No neurological complication due to radiation damage was observed in the follow-up period.Conclusion:The functional neuroimaging could be easily and reliably integrated into the CyberKnife treatment planning. Consideration of functional structures and fiber tracts during treatment planning could clinically reduce the radiation doses to these critical structures, thereby preserving its unique function of brain.

White matter tractography for neurosurgical planning: A topography-based review of the current state of the art.

We perform a review of the literature in the field of white matter tractography for neurosurgical planning, focusing on those works where tractography was correlated with clinical information such as patient outcome, clinical functional testing, or electro-cortical stimulation. We organize the review by anatomical location in the brain and by surgical procedure, including both supratentorial and infratentorial pathologies, and excluding spinal cord applications. Where possible, we discuss implications of tractography for clinical care, as well as clinically relevant technical considerations regarding the tractography methods.We find that tractography is a valuable tool in variable situations in modern neurosurgery. Our survey of recent reports demonstrates multiple potentially successful applications of white matter tractography in neurosurgery, with progress towards overcoming clinical challenges of standardization and interpretation.

Automated tractography in patients with temporal lobe epilepsy using TRActs Constrained by UnderLying Anatomy (TRACULA)

PurposeA detailed understanding of white matter tract alterations in patients with temporal lobe epilepsy (TLE) is important as it may provide useful information for likely side of seizure onset, cognitive impairment and postoperative prognosis. However, most diffusion-tensor imaging (DTI) studies have relied on manual reconstruction of tract bundles, despite the recent development of automated techniques. In the present study, we used an automated white matter tractography analysis approach to quantify temporal lobe white matter tract alterations in TLE and determine the relationships between tract alterations, the extent of hippocampal atrophy and the chronicity and severity of the disorder.MethodsWe acquired preoperative T1-weighted and DTI data in 64 patients with well-characterized TLE, with imaging and histopathological evidence of hippocampal sclerosis. Identical acquisitions were collected for 44 age- and sex-matched healthy controls. We employed automatic probabilistic tractography DTI analysis using TRActs Constrained by UnderLying Anatomy (TRACULA) available in context of Freesurfer software for the reconstruction of major temporal lobe tract bundles. We determined the factors influencing probabilistic tract reconstruction and investigated alterations of DTI scalar metrics along white matter tracts with respect to hippocampal volume, which was automatically estimated using Freesurfer's morphometric pipelines. We also explored the relationships between white matter tract alterations and duration of epilepsy, age of onset of epilepsy and seizure burden (defined as a function of seizure frequency and duration of epilepsy).ResultsWhole-tract diffusion characteristics of patients with TLE differed according to side of epilepsy and were significantly different between patients and controls. Waypoint comparisons along each tract revealed that patients had significantly altered tissue characteristics of the ipsilateral inferior-longitudinal, uncinate fasciculus, superior longitudinal fasciculus and cingulum relative to controls. Changes were more widespread (ipsilaterally and contralaterally) in patients with left TLE while patients with right TLE showed changes that remained spatially confined in ipsilateral tract regions. We found no relationship between DTI alterations and volume of the epileptogenic hippocampus. DTI alterations of anterior ipsilateral uncinate and inferior-longitudinal fasciculus correlated with duration of epilepsy (over and above effects of age) and age at onset of epilepsy. Seizure burden correlated with tissue characteristics of the uncinate fasciculus.ConclusionThis study shows that TRACULA permits the detection of alterations of DTI tract scalar metrics in patients with TLE. It also provides the opportunity to explore relationships with structural volume measurements and clinical variables along white matter tracts. Our data suggests that the anterior temporal lobe portions of the uncinate and inferior-longitudinal fasciculus may be particularly vulnerable to pathological alterations in patients with TLE. These alterations are unrelated to the extent of hippocampal atrophy (and therefore potentially mediated by independent mechanisms) but influenced by chronicity and severity of the disorder.

Brain connectivity networks and longitudinal trajectories of depression symptoms in adolescence

High levels of depression during adolescence may contribute to the risk for future depression later in life. This study examined the relationship between the developmental timing of depressive symptoms, and brain structural outcomes in late adolescence. In a prior work, we examined longitudinal trajectories of depressive symptoms in 243 adolescents (121 males and 122 females), and identified four subgroups: a normative group with stable low levels of depression, two groups with declining symptoms, and one group with increasing symptoms. For the current paper, diffusion-weighted MRI images were acquired at the final wave of the study, and used to perform white matter tractography and brain network analysis. The four depression trajectory groups were tested for differences in brain connectivity variables. This revealed differences in several frontal and temporal regions. The groups that had experienced elevated depression symptoms in early adolescence differed from the normative group in a greater number of areas than the group who had experienced depression later. Affected tracts corresponded to areas of white matter that are still maturing during this period, particularly frontolimbic regions. These findings support the proposition that the timing and duration of depression symptoms during adolescence are associated with brain structural outcomes.

The potential of neuroimaging for identifying predictors of adolescent alcohol use initiation and misuse.

Dysfunction in brain regions underlying impulse control, reward processing and executive function have been associated previously with adolescent alcohol misuse. However, identifying pre-existing neurobiological risk factors, as distinct from changes arising from early alcohol-use, is difficult. Here, we outline how neuroimaging data can identify the neural predictors of adolescent alcohol-use initiation and misuse by using prospective longitudinal studies to follow initially alcohol-naive individuals over time and by neuroimaging adolescents with inherited risk factors for alcohol misuse. A comprehensive narrative of the literature regarding neuroimaging studies published between 2010 and 2016 focusing on predictors of adolescent alcohol use initiation and misuse. Prospective, longitudinal neuroimaging studies have identified pre-existing differences between adolescents who remained alcohol-naive and those who transitioned subsequently to alcohol use. Both functional and structural grey matter differences were observed in temporal and frontal regions, including reduced brain activity in the superior frontal gyrus and temporal lobe, and thinner temporal cortices of future alcohol users. Interactions between brain function and genetic predispositions have been identified, including significant association found between the Ras protein-specific guanine nucleotide releasing factor 2 (RASGRF2) gene and reward-related striatal functioning. Neuroimaging predictors of alcohol use have shown modest utility to date. Future research should use out-of-sample performance as a quantitative measure of a predictor's utility. Neuroimaging data should be combined across multiple modalities, including structural information such as volumetrics and cortical thickness, in conjunction with white-matter tractography. A number of relevant neurocognitive systems should be assayed; particularly, inhibitory control, reward processing and executive functioning. Combining a rich magnetic resonance imaging data set could permit the generation of neuroimaging risk scores, which could potentially yield targeted interventions.

Exploring the neural substrates of attentional control and human intelligence: Diffusion tensor imaging of prefrontal white matter tractography in healthy cognition

We combined diffusion tension imaging (DTI) of prefrontal white matter integrity and neuropsychological measures to examine the functional neuroanatomy of human intelligence. Healthy participants completed the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) along with neuropsychological tests of attention and executive control, as measured by Trail Making Test (TMT) and Wisconsin Card Sorting Test (WCST). Stochastic tractography, considered the most effective DTI method, quantified white matter integrity of the medial orbital frontal cortex (mOFC) and rostral anterior cingulate cortex (rACC) circuitry. Based on prior studies, we hypothesized that posterior mOFC–rACC connections may play a key structural role linking attentional control processes and intelligence. Behavioral results provided strong support for this hypothesis, specifically linking attentional control processes, measured by Trails B and WCST perseverative errors, to intelligent quotient (IQ). Hierarchical regression results indicated left posterior mOFC–rACC fractional anisotropy (FA) and Trails B performance time, but not WCST perseverative errors, each contributed significantly to IQ, accounting for approximately 33.95–51.60% of the variance in IQ scores. These findings suggested that left posterior mOFC–rACC white matter connections may play a key role in supporting the relationship of executive functions of attentional control and general intelligence in healthy cognition.

Fast Automatic Segmentation of White Matter Streamlines Based on a Multi-Subject Bundle Atlas.

This paper presents an algorithm for fast segmentation of white matter bundles from massive dMRI tractography datasets using a multisubject atlas. We use a distance metric to compare streamlines in a subject dataset to labeled centroids in the atlas, and label them using a per-bundle configurable threshold. In order to reduce segmentation time, the algorithm first preprocesses the data using a simplified distance metric to rapidly discard candidate streamlines in multiple stages, while guaranteeing that no false negatives are produced. The smaller set of remaining streamlines is then segmented using the original metric, thus eliminating any false positives from the preprocessing stage. As a result, a single-thread implementation of the algorithm can segment a dataset of almost 9 million streamlines in less than 6 minutes. Moreover, parallel versions of our algorithm for multicore processors and graphics processing units further reduce the segmentation time to less than 22 seconds and to 5 seconds, respectively. This performance enables the use of the algorithm in truly interactive applications for visualization, analysis, and segmentation of large white matter tractography datasets.

Brain connectome modularity in weight-restored anorexia nervosa and body dysmorphic disorder.

Anorexia nervosa (AN) and body dysmorphic disorder (BDD) frequently co-occur, and have several overlapping phenomenological features. Little is known about their shared neurobiology. The aim of the study was to compare modular organization of brain structural connectivity. We acquired diffusion-weighted magnetic resonance imaging data on unmedicated individuals with BDD (n = 29), weight-restored AN (n = 24) and healthy controls (HC) (n = 31). We constructed connectivity matrices using whole-brain white matter tractography, and compared modular structures across groups. AN showed abnormal modularity involving frontal, basal ganglia and posterior cingulate nodes. There was a trend in BDD for similar abnormalities, but no significant differences compared with AN. In AN, poor insight correlated with longer path length in right caudal anterior cingulate and right posterior cingulate. Abnormal network organization patterns in AN, partially shared with BDD, may have implications for understanding integration between reward and habit/ritual formation, as well as conflict monitoring/error detection.

Characterization of the Fiber Connectivity Profile of the Cerebral Cortex in Schizotypal Personality Disorder: A Pilot Study.

Schizotypal personality disorder (SPD) is considered one of the classic disconnection syndromes. However, the specific cortical disconnectivity pattern has not been fully investigated. In this study, we aimed to explore significant alterations in whole-cortex structural connectivity in SPD individuals (SPDs) by combining the techniques of brain surface morphometry and white matter tractography. Diffusion and structural MR data were collected from 20 subjects with SPD (all males; age, 19.7 ± 0.9 years) and 18 healthy controls (all males; age, 20.3 ± 1.0 years). To measure the structural connectivity for a given unit area of the cortex, the fiber connectivity density (FiCD) value was proposed and calculated as the sum of the fractional anisotropy of all the fibers connecting to that unit area in tractography. Then, the resultant whole-cortex FiCD maps were compared in a vertex-wise manner between SPDs and controls. Compared with normal controls, SPDs showed significantly decreased FiCD in the rostral middle frontal gyrus (crossing BA 9 and BA 10) and significantly increased FiCD in the anterior part of the fusiform/inferior temporal cortex (P < 0.05, Monte Carlo simulation corrected). Moreover, the gray matter volume extracted from the left rostral middle frontal cluster was observed to be significantly greater in the SPD group (P = 0.02). Overall, this study identifies a decrease in connectivity in the left middle frontal cortex as a key neural deficit at the whole-cortex level in SPD, thus providing insight into its neuropathological basis.

The uncinate fasciculus as observed using diffusion spectrum imaging in the human brain.

The definitive structure and comprehensive role of the uncinate fasciculus (UF) are still obscure. We aimed to map the human UF white matter tractography and investigate the asymmetry, connectivity, and segmentation of the UF. Subcomponents of the UF were analyzed in 9 normal subjects and a 30-subject diffusion spectrum imaging (DSI) template (CMU-30). DSI and microdissection were performed to explore the tractography of the UF. Both methods revealed that it connects the anterior part of the temporal lobe (superior temporal gyrus and temporal pole) with the inferior frontal cortex and the orbitofrontal cortex. The UF starts at the temporal gyrus, runs inferiorly to the inferior frontal occipital fasciculus and splits into two branches, terminating in the ventrolateral frontal cortex and the rostral middle frontal cortex. Our study showed that the cortical areas of termination in the frontal lobe of the UF are the pars triangularis and pars orbitalis. The relative volume of the UF in both hemispheres was calculated. An independent t test was used to determine variances in the value of tract volume between the left and right hemispheres. The volume and the length showed a significant statistical difference in the total volume of the UF. We suggest the UF is leftward asymmetry. The two parts of the UF were divided, but the conclusion is not consistent with the previous published articles which have shown that the UF is segmented into three parts. Our research facilitates a better understanding of the UF.

Intrahemispheric white matter asymmetries: the missing link between brain structure and functional lateralization?

Hemispheric asymmetries are a central principle of nervous system architecture and shape the functional organization of most cognitive systems. Structural gray matter asymmetries and callosal interactions have been identified as contributing neural factors but always fell short to constitute a full explanans. Meanwhile, recent advances in in vivo white matter tractography have unrevealed the asymmetrical organization of many intrahemispheric white matter pathways, which might serve as the missing link to explain the substrate of functional lateralization. By taking into account callosal interactions, gray matter asymmetries and asymmetrical interhemispheric pathways, we opt for a new triadic model that has the potential to explain many observations which cannot be elucidated within the current frameworks of lateralized cognition.