Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers

The connectome mapper: an open-source processing pipeline to map connectomes with MRI

Researchers working in the field of global connectivity analysis using diffusion magnetic resonance imaging (MRI) can count on a wide selection of software packages for processing their data, with methods ranging from the reconstruction of the local intra-voxel axonal structure to the estimation of the trajectories of the underlying fibre tracts. However, each package is generally task-specific and uses its own conventions and file formats. In this article we present the Connectome Mapper, a software pipeline aimed at helping researchers through the tedious process of organising, processing and analysing diffusion MRI data to perform global brain connectivity analyses. Our pipeline is written in Python and is freely available as open-source at www.cmtk.org.

Novel imaging strategies for assessment of cerebrovascular involvement

There is an important correlation between vascular risk factors and nonspecific imaging findings in the brain such as white-matter hyperintensities. These vascular risk factors are also associated with dementia and lesser forms of cognitive impairment. One hypothesis is that these vascular risk factors lead to disruption of connective networks in the central nervous system that are supported by myelinated white-matter fibers, which in turn lead to deficits in functional signaling between various brain regions. Another possibility is an alteration of the neurovascular coupling due to vascular risk factors. This reduced functional signaling contributes to the cognitive deficits in persons harboring these vascular risk factors. Lifestyle changes may restore some of these functional deficits through brain plasticity. It is imperative that preclinical diagnostic techniques are developed to identify these early brain changes in persons harboring vascular risk factors, as such efforts may improve primary and secondary prevention efforts. Recently developed imaging techniques may provide objective imaging biomarkers to measure the structural and functional brain changes in persons with vascular risk factors and resulting subclinical atherosclerotic disease. This article reviews a few of these novel imaging techniques.

Layer-specific diffusion weighted imaging in human primary visual cortex in vitro

One of the most prominent characteristics of the human neocortex is its laminated structure. The first person to observe this was Francesco Gennari in the second half the 18th century: in the middle of the depth of primary visual cortex, myelinated fibres are so abundant that he could observe them with bare eyes as a white line. Because of its saliency, the stria of Gennari has a rich history in cyto- and myeloarchitectural research as well as in magnetic resonance (MR) microscopy. In the present paper we show for the first time the layered structure of the human neocortex with ex vivo diffusion weighted imaging (DWI). To achieve the necessary spatial and angular resolution, primary visual cortex samples were scanned on an 11.7 T small-animal MR system to characterize the diffusion properties of the cortical laminae and the stria of Gennari in particular. The results demonstrated that fractional anisotropy varied over cortical depth, showing reduced anisotropy in the stria of Gennari, the inner band of Baillarger and the deepest layer of the cortex. Orientation density functions showed multiple components in the stria of Gennari and deeper layers of the cortex. Potential applications of layer-specific diffusion imaging include characterization of clinical abnormalities, cortical mapping and (intra)cortical tractography. We conclude that future high-resolution in vivo cortical DWI investigations should take into account the layer-specificity of the diffusion properties.

Altered structural networks and executive deficits in traumatic brain injury patients

Recent research on traumatic brain injury (TBI) has shown that impairments in cognitive and executive control functions are accompanied by a disrupted neural connectivity characterized by white matter damage. We constructed binary and weighted brain structural networks in 21 patients with chronic TBI and 17 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Executive function was assessed with the local global task and the trail making task, requiring inhibition, updating, and switching. The results revealed that TBI patients were less successful than controls on the executive tasks, as shown by the higher reaction times, higher switch costs, and lower accuracy rates. Moreover, both TBI patients and controls exhibited a small world topology in their white matter networks. More importantly, the TBI patients demonstrated increased shortest path length and decreased global efficiency of the structural network. These findings suggest that TBI patients have a weaker globally integrated structural brain network, resulting in a limited capacity to integrate information across brain regions. Furthermore, we showed that the white matter networks of both groups contained highly connected hub regions that were predominately located in the parietal cortex, frontal cortex, and basal ganglia. Finally, we showed significant correlations between switching performance and network property metrics within the TBI group. Specifically, lower scores on the switching tasks corresponded to a lower global efficiency. We conclude that analyzing the structural brain network connectivity provides new insights into understanding cognitive control changes following brain injury.

Diffusion imaging in neurological disease

Diffusion-weighted imaging can be used to assess the microscopic properties of measured tissues, providing insights into the architecture of neural tissues and how they change in physiological and pathological states. Such imaging data can be readily quantified to provide numerical values of parameters that have clinical relevance, particularly in regard to cellular constituents of tumours, chemical contents of cysts, the integrity of neuronal cell bodies and myelin sheaths. Diffusion based techniques have proven to be particularly useful in investigating cerebral infarction, cerebral infections, epidermoid and other cysts, cerebral tumours, and white matter disorders. The purpose of this review is to introduce key concepts in diffusion imaging and illustrate how it may be applied to clinical practice, with particular reference to head injury.

The UCLA multimodal connectivity database: a web-based platform for brain connectivity matrix sharing and analysis

Brain connectomics research has rapidly expanded using functional MRI (fMRI) and diffusion-weighted MRI (dwMRI). A common product of these varied analyses is a connectivity matrix (CM). A CM stores the connection strength between any two regions (“nodes”) in a brain network. This format is useful for several reasons: (1) it is highly distilled, with minimal data size and complexity, (2) graph theory can be applied to characterize the network's topology, and (3) it retains sufficient information to capture individual differences such as age, gender, intelligence quotient (IQ), or disease state. Here we introduce the UCLA Multimodal Connectivity Database (http://umcd.humanconnectomeproject.org), an openly available website for brain network analysis and data sharing. The site is a repository for researchers to publicly share CMs derived from their data. The site also allows users to select any CM shared by another user, compute graph theoretical metrics on the site, visualize a report of results, or download the raw CM. To date, users have contributed over 2000 individual CMs, spanning different imaging modalities (fMRI, dwMRI) and disorders (Alzheimer's, autism, Attention Deficit Hyperactive Disorder). To demonstrate the site's functionality, whole brain functional and structural connectivity matrices are derived from 60 subjects' (ages 26–45) resting state fMRI (rs-fMRI) and dwMRI data and uploaded to the site. The site is utilized to derive graph theory global and regional measures for the rs-fMRI and dwMRI networks. Global and nodal graph theoretical measures between functional and structural networks exhibit low correspondence. This example demonstrates how this tool can enhance the comparability of brain networks from different imaging modalities and studies. The existence of this connectivity-based repository should foster broader data sharing and enable larger-scale meta-analyses comparing networks across imaging modality, age group, and disease state.

Damage to white matter pathways in subacute and chronic spatial neglect: a group study and 2 single-case studies with complete virtual "in vivo" tractography dissection

The exact anatomical localization of right hemisphere lesions that lead to left spatial neglect is still debated. The effect of confounding factors such as acute diaschisis and hypoperfusion, visual field defects, and lesion size may account for conflicting results that have been reported in the literature. Here, we present a comprehensive anatomical investigation of the gray- and white matter lesion correlates of left spatial neglect, which was run in a sample 58 patients with subacute or chronic vascular strokes in the territory of the right middle cerebral artery. Standard voxel-based correlates confirmed the role played by lesions in the posterior parietal cortex (supramarginal gyrus, angular gyrus, and temporal-parietal junction), in the frontal cortex (frontal eye field, middle and inferior frontal gyrus), and in the underlying parietal-frontal white matter. Using a new diffusion tensor imaging-based atlas of the human brain, we were able to run, for the first time, a detailed analysis of the lesion involvement of subcortical white matter pathways. The results of this analysis revealed that, among the different pathways linking parietal with frontal areas, damage to the second branch of the superior longitudinal fasciculus (SLF II) was the best predictor of left spatial neglect. The group study also revealed a subsample of patients with neglect due to focal lesion in the lateral-dorsal portion of the thalamus, which connects the premotor cortex with the inferior parietal lobule. The relevance of fronto-parietal disconnection was further supported by complete in vivo tractography dissection of white matter pathways in 2 patients, one with and the other without signs of neglect. These 2 patients were studied both in the acute phase and 1 year after stroke and were perfectly matched for age, handedness, stroke onset, lesion size, and for cortical lesion involvement. Taken together, the results of the present study support the hypothesis that anatomical disconnections leading to a functional breakdown of parietal-frontal networks are an important pathophysiological factor leading to chronic left spatial neglect. Here, we propose that different loci of SLF disconnection on the rostro-caudal axis can also be associated with disconnection of short-range white matter pathways within the frontal or parietal areas. Such different local disconnection patterns can play a role in the important clinical variability of the neglect syndrome.

Tract profiles of white matter properties: automating fiber-tract quantification

Tractography based on diffusion weighted imaging (DWI) data is a method for identifying the major white matter fascicles (tracts) in the living human brain. The health of these tracts is an important factor underlying many cognitive and neurological disorders. In vivo, tissue properties may vary systematically along each tract for several reasons: different populations of axons enter and exit the tract, and disease can strike at local positions within the tract. Hence quantifying and understanding diffusion measures along each fiber tract (Tract Profile) may reveal new insights into white matter development, function, and disease that are not obvious from mean measures of that tract. We demonstrate several novel findings related to Tract Profiles in the brains of typically developing children and children at risk for white matter injury secondary to preterm birth. First, fractional anisotropy (FA) values vary substantially within a tract but the Tract FA Profile is consistent across subjects. Thus, Tract Profiles contain far more information than mean diffusion measures. Second, developmental changes in FA occur at specific positions within the Tract Profile, rather than along the entire tract. Third, Tract Profiles can be used to compare white matter properties of individual patients to standardized Tract Profiles of a healthy population to elucidate unique features of that patient's clinical condition. Fourth, Tract Profiles can be used to evaluate the association between white matter properties and behavioral outcomes. Specifically, in the preterm group reading ability is positively correlated with FA measured at specific locations on the left arcuate and left superior longitudinal fasciculus and the magnitude of the correlation varies significantly along the Tract Profiles. We introduce open source software for automated fiber-tract quantification (AFQ) that measures Tract Profiles of MRI parameters for 18 white matter tracts. With further validation, AFQ Tract Profiles have potential for informing clinical management and decision-making.

Co-analysis of brain structure and function using fMRI and diffusion-weighted imaging

The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when studying the brain, as the functional role that a brain area fulfills may be largely defined by its connections to other brain areas. In this report, we describe a novel, non-invasive approach for relating brain structure and function using magnetic resonance imaging (MRI). This approach, a combination of structural imaging of long-range fiber connections and functional imaging data, is illustrated in two distinct cognitive domains, visual attention and face perception. Structural imaging is performed with diffusion-weighted imaging (DWI) and fiber tractography, which track the diffusion of water molecules along white-matter fiber tracts in the brain (Figure 1). By visualizing these fiber tracts, we are able to investigate the long-range connective architecture of the brain. The results compare favorably with one of the most widely-used techniques in DWI, diffusion tensor imaging (DTI). DTI is unable to resolve complex configurations of fiber tracts, limiting its utility for constructing detailed, anatomically-informed models of brain function. In contrast, our analyses reproduce known neuroanatomy with precision and accuracy. This advantage is partly due to data acquisition procedures: while many DTI protocols measure diffusion in a small number of directions (e.g., 6 or 12), we employ a diffusion spectrum imaging (DSI)(1, 2) protocol which assesses diffusion in 257 directions and at a range of magnetic gradient strengths. Moreover, DSI data allow us to use more sophisticated methods for reconstructing acquired data. In two experiments (visual attention and face perception), tractography reveals that co-active areas of the human brain are anatomically connected, supporting extant hypotheses that they form functional networks. DWI allows us to create a "circuit diagram" and reproduce it on an individual-subject basis, for the purpose of monitoring task-relevant brain activity in networks of interest.

Radial coherence of diffusion tractography in the cerebral white matter of the human fetus: neuroanatomic insights

High angular resolution diffusion imaging (HARDI) demonstrates transient radial coherence of telencephalic white matter in the human fetus. Our objective was to define the neuroanatomic basis of this radial coherence through correlative HARDI- and postmortem tissue analyses. Applying immunomarkers to radial glial fibers (RGFs), axons, and blood vessels in 18 cases (19 gestational weeks to 3 postnatal years), we compared their developmental profiles to HARDI tractography in brains of comparable ages (n = 11). At midgestation, radial coherence corresponded with the presence of RGFs. At 30-31 weeks, the transition from HARDI-defined radial coherence to corticocortical coherence began simultaneously with the transformation of RGFs to astrocytes. By term, both radial coherence and RGFs had disappeared. White matter axons were radial, tangential, and oblique over the second half of gestation, whereas penetrating blood vessels were consistently radial. Thus, radial coherence in the fetal white matter likely reflects a composite of RGFs, penetrating blood vessels, and radial axons of which its transient expression most closely matches that of RGFs. This study provides baseline information for interpreting radial coherence in tractography studies of the preterm brain in the assessment of the encephalopathy of prematurity.

Ventral and dorsal visual streams in posterior cortical atrophy: a DT MRI study

Using diffusion tensor magnetic resonance imaging tractography, ventral (inferior longitudinal fasciculus) and fronto-occipital (inferior fronto-occipital fasciculus) and dorsal (fronto-parietal superior longitudinal fasciculus) visual pathways were assessed in 7 patients with posterior cortical atrophy (PCA), showing either predominantly ventral or additional dorsal cognitive deficits. Corpus callosum and corticospinal tracts were also studied. Gray and white matter atrophy was assessed using voxel-based morphometry. In all PCA patients, abnormal diffusivity indexes were found in bilateral inferior longitudinal fasciculus and inferior fronto-occipital fasciculus, with a left-side predominance. Patients also had mild microstructural damage to the corpus callosum. The 2 patients with more dorsal symptoms also showed right fronto-parietal superior longitudinal fasciculus abnormalities. Corticospinal tracts were normal, bilaterally. When studied separately, patients with ventral clinical impairment showed a pattern of atrophy mainly located in the ventral occipitotemporal regions, bilaterally; patients with both ventral and dorsal clinical deficits showed additional atrophy of the bilateral inferior parietal lobe. Magnetic resonance imaging patterns of abnormalities mirror closely the clinical phenotypes and could provide reliable ante mortem markers of tissue damage in PCA.

Brain networks in posterior cortical atrophy: a single case tractography study and literature review

Posterior cortical atrophy (PCA) is rare neurodegenerative dementia, clinically characterized by a progressive decline in higher-visual object and space processing. After a brief review of the literature on the neuroimaging in PCA, here we present a study of the brain structural connectivity in a patient with PCA and progressive isolated visual and visuo-motor signs. Clinical and cognitive data were acquired in a 58-years-old patient (woman, right-handed, disease duration 18 months). Brain structural and diffusion tensor (DT) magnetic resonance imaging (MRI) were obtained. A voxel-based morphometry (VBM) study was performed to explore the pattern of gray matter (GM) atrophy, and a fully automatic segmentation was assessed to obtain the hippocampal volumes. DT MRI-based tractography was used to assess the integrity of long-range white matter (WM) pathways in the patient and in six sex- and age-matched healthy subjects. This PCA patient had a clinical syndrome characterized by left visual neglect, optic ataxia, and left limb apraxia, as well as mild visuo-spatial episodic memory impairment. VBM study showed bilateral posterior GM atrophy with right predominance; DT MRI tractography demonstrated WM damage to the right hemisphere only, including the superior and inferior longitudinal fasciculi and the inferior fronto-occipital fasciculus, as compared to age-matched controls. The homologous left-hemisphere tracts were spared. No difference was found between left and right hippocampal volumes. These data suggest that selective visuo-spatial deficits typical of PCA might not result from cortical damage alone, but by a right-lateralized network-level dysfunction including WM damage along the major visual pathways.

Beyond the arcuate fasciculus: consensus and controversy in the connectional anatomy of language

The growing consensus that language is distributed into large-scale cortical and subcortical networks has brought with it an increasing focus on the connectional anatomy of language, or how particular fibre pathways connect regions within the language network. Understanding connectivity of the language network could provide critical insights into function, but recent investigations using a variety of methodologies in both humans and non-human primates have provided conflicting accounts of pathways central to language. Some of the pathways classically considered language pathways, such as the arcuate fasciculus, are now argued to be domain-general rather than specialized, which represents a radical shift in perspective. Other pathways described in the non-human primate remain to be verified in humans. In this review, we examine the consensus and controversy in the study of fibre pathway connectivity for language. We focus on seven fibre pathways-the superior longitudinal fasciculus and arcuate fasciculus, the uncinate fasciculus, extreme capsule, middle longitudinal fasciculus, inferior longitudinal fasciculus and inferior fronto-occipital fasciculus-that have been proposed to support language in the human. We examine the methods in humans and non-human primate used to investigate the connectivity of these pathways, the historical context leading to the most current understanding of their anatomy, and the functional and clinical correlates of each pathway with reference to language. We conclude with a challenge for researchers and clinicians to establish a coherent framework within which fibre pathway connectivity can be systematically incorporated to the study of language.

Layer-specific intracortical connectivity revealed with diffusion MRI

In this work, we show for the first time that the tangential diffusion component is orientationally coherent at the human cortical surface. Using diffusion magnetic resonance imaging (dMRI), we have succeeded in tracking intracortical fiber pathways running tangentially within the cortex. In contrast with histological methods, which reveal little regarding 3-dimensional organization in the human brain, dMRI delivers additional understanding of the layer dependence of the fiber orientation. A postmortem brain block was measured at very high angular and spatial resolution. The dMRI data had adequate resolution to allow analysis of the fiber orientation within 4 notional cortical laminae. We distinguished a lamina at the cortical surface where diffusion was tangential along the surface, a lamina below the surface where diffusion was mainly radial, an internal lamina covering the Stria of Gennari, where both strong radial and tangential diffusion could be observed, and a deep lamina near the white matter, which also showed mainly radial diffusion with a few tangential compartments. The measurement of the organization of the tangential diffusion component revealed a strong orientational coherence at the cortical surface.

Diffusion spectrum MRI using body-centered-cubic and half-sphere sampling schemes

The optimum sequence parameters of diffusion spectrum MRI (DSI) on clinical scanners were investigated previously. However, the scan time of approximately 30 min is still too long for patient studies. Additionally, relatively large sampling interval in the diffusion-encoding space may cause aliasing artifact in the probability density function when Fourier transform is undertaken, leading to estimation error in fiber orientations. Therefore, this study proposed a non-Cartesian sampling scheme, body-centered-cubic (BCC), to avoid the aliasing artifact as compared to the conventional Cartesian grid sampling scheme (GRID). Furthermore, the accuracy of DSI with the use of half-sphere sampling schemes, i.e. GRID102 and BCC91, was investigated by comparing to their full-sphere sampling schemes, GRID203 and BCC181, respectively. In results, smaller deviation angle and lower angular dispersion were obtained by using the BCC sampling scheme. The half-sphere sampling schemes yielded angular precision and accuracy comparable to the full-sphere sampling schemes. The optimum b(max) was approximately 4750 s/mm(2) for GRID and 4500 s/mm(2) for BCC. In conclusion, the BCC sampling scheme could be implemented as a useful alternative to the GRID sampling scheme. Combination of BCC and half-sphere sampling schemes, that is BCC91, may potentially reduce the scan time of DSI from 30 min to approximately 14 min while maintaining its precision and accuracy.

Response to comment on "the geometric structure of the brain fiber pathways"

In response to Catani et al., we show that corticospinal pathways adhere via sharp turns to two local grid orientations; that our studies have three times the diffusion resolution of those compared; and that the noted technical concerns, including crossing angles, do not challenge the evidence of mathematically specific geometric structure. Thus, the geometric thesis gives the best account of the available evidence.

Diffusion tensor imaging in autism spectrum disorder: a review

White matter tracts of the brain allow neurons and neuronal networks to communicate and function with high efficiency. The aim of this review is to briefly introduce diffusion tensor imaging methods that examine white matter tracts and then to give an overview of the studies that have investigated white matter integrity in the brains of individuals with autism spectrum disorder (ASD). From the 48 studies we reviewed, persons with ASD tended to have decreased fractional anisotropy and increased mean diffusivity in white matter tracts spanning many regions of the brain but most consistently in regions such as the corpus callosum, cingulum, and aspects of the temporal lobe. This decrease in fractional anisotropy was often accompanied by increased radial diffusivity. Additionally, the review suggests possible atypical lateralization in some white matter tracts of the brain and a possible atypical developmental trajectory of white matter microstructure in persons with ASD. Clinical implications and future research directions are discussed.

Independent component analysis tractography combined with a ball-stick model to isolate intravoxel crossing fibers of the corticospinal tracts in clinical diffusion MRI

The independent component analysis (ICA) tractography method has improved the ability to isolate intravoxel crossing fibers; however, the accuracy of ICA is limited in cases with voxels in local clusters lacking sufficient numbers of fibers with the same orientations. To overcome this limitation, the ICA was combined with a ball-stick model (BSM) ["ICA+BSM"]. An ICA approach is applied to identify crossing fiber components in voxels of small cluster, which are maximally independent in orientation. The eigenvectors of these components are numerically optimized via the subsequent BSM procedure. Simulation studies for two or three crossing fibers demonstrate that ICA+BSM overcomes the limitation of the original ICA method by refining regional ICA solutions in diffusion measurement of a single voxel. It shows 2°-5° of angular errors to isolate two or three fibers, providing a better recovery of simulated fibers compared with ICA alone. Human studies show that ICA+BSM achieves high anatomical correspondence of corticospinal tracts compared with postmortem corticospinal histology, yielding 92.2% true positive detection including both lateral and medial projections, compared with 84.1% for ICA alone. This study demonstrates that the intravoxel crossing fiber problem in clinical diffusion MRI may be sorted out more efficiently by combining ICA with BSM.

White matter reorganization and functional response after focal cerebral ischemia in the rat

After stroke, the brain has shown to be able to achieve spontaneous functional recovery despite severe cerebral damage. This phenomenon is poorly understood. To address this issue, focal transient ischemia was induced by 60 min middle cerebral artery occlusion in Wistar rats. The evolution of stroke was followed using two magnetic resonance imaging modalities: diffusion spectrum imaging (acquired before, one and four weeks after stroke) and functional magnetic resonance imaging (acquired before and five weeks after stroke). To confirm the imaging observations, immunohistochemical staining for myelin, astrocytes and macrophages/microglia was added. At four weeks after stroke, a focal alteration of the diffusion anisotropy was observed between the ipsilesional ventricle and the lesion area. Using tractography this perturbation was identified as reorganization of the ipsilesional internal capsule. Functional imaging at five weeks after ischemia demonstrated activation of the primary sensorimotor cortex in both hemispheres in all rats except one animal lacking a functional response in the ipsilesional cortex. Furthermore, fiber tracking showed a transhemispheric fiber connection through the corpus callosum, which-in the rat without functional recovery-was lost. Our study shows the influence of the internal capsule reorganization, combined with inter-hemispheric connections though the corpus callosum, on the functional activation of the brain from stroke. In conclusion, tractography opens a new door to non-invasively investigate the structural correlates of lack of functional recovery after stroke.

Optical coherence tractography using intrinsic contrast

Organs such as the heart and brain possess intricate fiber structures that are best characterized with three-dimensional imaging. For instance, diffusion-based, magnetic resonance tractography (MRT) enables studies of connectivity and remodeling during development and disease macroscopically on the millimeter scale. Here we present complementary, high-resolution microscopic optical coherence imaging and analysis methods that, when used in conjunction with clearing techniques, can characterize fiber architecture in intact organs at tissue depths exceeding 1 mm. We anticipate that these techniques can be used to study fiber architecture in situ at microscopic scales not currently accessible to diffusion magentic resonance (MR), and thus, to validate and complement macroscopic structural imaging techniques. Moreover, as these techniques use intrinsic signals and do not require tissue slicing and staining, they can be used for high-throughput, nondestructive evaluation of fiber architecture across large tissue volumes.

Current status and future perspectives of magnetic resonance high-field imaging: a summary

There are several magnetic resonance (MR) imaging techniques that benefit from high-field MR imaging. This article describes a range of novel techniques that are currently being used clinically or will be used in the future for clinical purposes as they gain popularity. These techniques include functional MR imaging, diffusion tensor imaging, cortical thickness assessment, arterial spin labeling perfusion, white matter hyperintensity lesion assessment, and advanced MR angiography.

Connectivity-based structural and functional parcellation of the human cortex using diffusion imaging and tractography

The parcellation of the cortex via its anatomical properties has been an important research endeavor for over a century. To date, however, a universally accepted parcellation scheme for the human brain still remains elusive. In the current review, we explore the use of in vivo diffusion imaging and white matter tractography as a non-invasive method for the structural and functional parcellation of the human cerebral cortex, discussing the strengths and limitations of the current approaches. Cortical parcellation via white matter connectivity is based on the premise that, as connectional anatomy determines functional organization, it should be possible to segregate functionally-distinct cortical regions by identifying similarities and differences in connectivity profiles. Recent studies have provided initial evidence in support of the efficacy of this connectional parcellation methodology. Such investigations have identified distinct cortical subregions which correlate strongly with functional regions identified via fMRI and meta-analyses. Furthermore, a strong parallel between the cortical regions defined via tractographic and more traditional cytoarchitectonic parcellation methods has been observed. However, the degree of correspondence and relative functional importance of cytoarchitectonic- versus connectivity-derived parcellations still remains unclear. Diffusion tractography remains one of the only methods capable of visualizing the structural networks of the brain in vivo. As such, it is of vital importance to continue to improve the accuracy of the methodology and to extend its potential applications in the study of cognition in neurological health and disease.

Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome.

Rethinking the role of the middle longitudinal fascicle in language and auditory pathways

The middle longitudinal fascicle (MdLF) was originally described in the monkey brain as a pathway that interconnects the superior temporal and angular gyri. Only recently have diffusion tensor imaging studies provided some evidence of its existence in humans, with a connectivity pattern similar to that in monkeys and a potential role in the language system. In this study, we combine high-angular-resolution fiber tractography and fiber microdissection techniques to determine the trajectory, cortical connectivity, and a quantitative analysis of the MdLF. Here, we analyze diffusion spectrum imaging (DSI) studies in 6 subjects (subject-specific approach) and in a template of 90 DSI studies (NTU-90 Atlas). Our tractography and microdissection results show that the human MdLF differs significantly from the monkey. Indeed, the human MdLF interconnects the superior temporal gyrus with the superior parietal lobule and parietooccipital region, and has only minor connections with the angular gyrus. On the basis of the roles of these interconnected cortical regions, we hypothesize that, rather than a language-related tract, the MdLF may contribute to the dorsal "where" pathway of the auditory system.

Diffusion magnetic resonance imaging for Brainnetome: a critical review

Increasing evidence shows that the human brain is a highly self-organized system that shows attributes of small-worldness, hierarchy and modularity. The "connectome" was conceived several years ago to identify the underpinning physical connectivities of brain networks. The need for an integration of multi-spatial and -temporal approaches is becoming apparent. Therefore, the "Brainnetome" (brain-net-ome) project was proposed. Diffusion magnetic resonance imaging (dMRI) is a non-invasive way to study the anatomy of brain networks. Here, we review the principles of dMRI, its methodologies, and some of its clinical applications for the Brainnetome. Future research in this field is discussed.

Neuroanatomic connectivity of the human ascending arousal system critical to consciousness and its disorders

The ascending reticular activating system (ARAS) mediates arousal, an essential component of human consciousness. Lesions of the ARAS cause coma, the most severe disorder of consciousness. Because of current methodological limitations, including of postmortem tissue analysis, the neuroanatomic connectivity of the human ARAS is poorly understood. We applied the advanced imaging technique of high angular resolution diffusion imaging (HARDI) to elucidate the structural connectivity of the ARAS in 3 adult human brains, 2 of which were imaged postmortem. High angular resolution diffusion imaging tractography identified the ARAS connectivity previously described in animals and also revealed novel human pathways connecting the brainstem to the thalamus, the hypothalamus, and the basal forebrain. Each pathway contained different distributions of fiber tracts from known neurotransmitter-specific ARAS nuclei in the brainstem. The histologically guided tractography findings reported here provide initial evidence for human-specific pathways of the ARAS. The unique composition of neurotransmitter-specific fiber tracts within each ARAS pathway suggests structural specializations that subserve the different functional characteristics of human arousal. This ARAS connectivity analysis provides proof of principle that HARDI tractography may affect the study of human consciousness and its disorders, including in neuropathologic studies of patients dying in coma and the persistent vegetative state.

A DTI tractography analysis of infralimbic and prelimbic connectivity in the mouse using high-throughput MRI

BACKGROUND

High throughput, brain-wide analysis of neural circuit connectivity is needed to understand brain function across species. Combining such tractography techniques with small animal models will allow more rapid integration of systems neuroscience with molecular genetic, behavioral, and cellular approaches.

METHODS

We collected DTI and T2 scans on 3 series of 6 fixed mouse brains ex vivo in a 9.4 Tesla magnet. The DTI analysis of ten mouse brains focused on comparing prelimbic (PL) and Infralimbic (IL) probabilistic tractography. To validate the DTI results a preliminary set of 24 additional mice were injected with BDA into the IL and PL. The DTI results and preliminary BDA results were also compared to previously published rat connectivity.

RESULTS

We focused our analyses on the connectivity of the mouse prelimbic (PL) vs. infralimbic (IL) cortices. We demonstrated that this DTI analysis is consistent across scanned mice, with prior analyses of rat IL/PL connectivity, and with mouse PL and IL projections using the BDA tracer.

CONCLUSIONS

High-throughput ex vivo DTI imaging in the mouse delineated both common and differential connectivity of the IL and PL cortex. The scanning methodology provided a balance of tissue contrast, signal-to-noise ratio, resolution and throughput. Our results are largely consistent with previously published anterograde staining techniques in rats, and the preliminary tracer study of the mouse IL and PL provided here.

Connectivity of thalamo-cortical pathway in rat brain: combined diffusion spectrum imaging and functional MRI at 11.7 T

Fiber tracking in combination with functional MRI has recently attracted strong interest, as it may help to elucidate the structural basis for functional connectivities and may be selective in the determination of the fiber bundles responsible for a particular circuit. Diffusion spectrum imaging provides a more complex analysis of fiber circuits than the commonly used diffusion tensor imaging approach, also allowing the discrimination of crossing fibers in the brain. For the understanding of pathophysiological alterations during brain lesion and recovery, such studies need to be extended to small-animal models. In this article, we present the first study combining functional MRI with high-resolution diffusion spectrum imaging in vivo. We have chosen the well-characterized electrical forepaw stimulation paradigm in the rat to examine the thalamo-cortical pathway. Using the functionally activated areas in both thalamus and somatosensory cortex as seed and target regions for fiber tracking, we are able to characterize the fibers responsible for this stimulation pathway. Moreover, we show that the selection of the thalamic nucleus and primary somatosensory cortex on the basis of anatomical description results in a larger fiber bundle, probably encompassing connectivities between the thalamus and other areas of the somatosensory cortex, such as the hindpaw and large barrel field cortex.

MR connectomics: a conceptual framework for studying the developing brain

THE COMBINATION OF ADVANCED NEUROIMAGING TECHNIQUES AND MAJOR DEVELOPMENTS IN COMPLEX NETWORK SCIENCE, HAVE GIVEN BIRTH TO A NEW FRAMEWORK FOR STUDYING THE BRAIN: "connectomics." This framework provides the ability to describe and study the brain as a dynamic network and to explore how the coordination and integration of information processing may occur. In recent years this framework has been used to investigate the developing brain and has shed light on many dynamic changes occurring from infancy through adulthood. The aim of this article is to review this work and to discuss what we have learned from it. We will also use this body of work to highlight key technical aspects that are necessary in general for successful connectome analysis using today's advanced neuroimaging techniques. We look to identify current limitations of such approaches, what can be improved, and how these points generalize to other topics in connectome research.

Microstructural organizational patterns in the human corticostriatal system

The axons that project into the striatum are known to segregate according to macroscopic cortical systems; however, the within-region organization of these fibers has yet to be described in humans. We used in vivo fiber tractography, in neurologically healthy adults, to map white matter bundles that originate in different neocortical areas, navigate complex fiber crossings, and project into the striatum. As expected, these fibers were generally segregated according to cortical origin. Within a subset of pathways, a patched pattern of inputs was observed, consistent with previous ex vivo histological studies. In projections from the prefrontal cortex, we detected a topography in which fibers from rostral prefrontal areas projected mostly to rostral parts of the striatum and vice versa for inputs originating in caudal cortical areas. Importantly, within this prefrontal system there was also an asymmetry in the subset of divergent projections, with more fibers projecting in a posterior direction than anterior. This asymmetry of information projecting into the basal ganglia was predicted by previous network-level computational models. A rostral-caudal topography was also present at the local level in otherwise somatotopically organized fibers projecting from the motor cortex. This provides clear evidence that the longitudinal organization of input fields, observed at the macroscopic level across cortical systems, is also found at the microstructural scale at which information is segregated as it enters the human basal ganglia.

Ventral and dorsal streams in the evolution of speech and language

The brains of humans and old-world monkeys show a great deal of anatomical similarity. The auditory cortical system, for instance, is organized into a ventral and a dorsal pathway in both species. A fundamental question with regard to the evolution of speech and language (as well as music) is whether human and monkey brains show principal differences in their organization (e.g., new pathways appearing as a result of a single mutation), or whether species differences are of a more subtle, quantitative nature. There is little doubt about a similar role of the ventral auditory pathway in both humans and monkeys in the decoding of spectrally complex sounds, which some authors have referred to as auditory object recognition. This includes the decoding of speech sounds ("speech perception") and their ultimate linking to meaning in humans. The originally presumed role of the auditory dorsal pathway in spatial processing, by analogy to the visual dorsal pathway, has recently been conceptualized into a more general role in sensorimotor integration and control. Specifically for speech, the dorsal processing stream plays a role in speech production as well as categorization of phonemes during on-line processing of speech.

Challenges of High-resolution Diffusion Imaging of the Human Medial Temporal Lobe in Alzheimer Disease

The human medial temporal lobe performs an essential role in memory formation and retrieval. Diseases involving the hippocampus such as Alzheimer disease present a unique opportunity for advanced imaging techniques to detect abnormalities at an early stage. In particular, it is possible that diffusion imaging will measure abnormal microarchitecture beyond the realm of macroscopic imaging. However, this task is formidable because of the detailed anatomy of the medial temporal lobe, the difficulties in obtaining high-quality diffusion images of adequate resolution, and the challenges in diffusion data processing. Moreover, it is unclear if any differences will be significant for an individual patient or simply groups of patients. Successful endeavors will need to address each of these challenges in an integrated fashion. The rewards of such analysis may be detection of microscopic disease in vivo, which could represent a landmark accomplishment for the field of neuroradiology.

An introduction to model-independent diffusion magnetic resonance imaging

q-Space-based techniques such as diffusion spectrum imaging, q-ball imaging, and their variations have been used extensively in research for their desired capability to delineate complex neuronal architectures such as multiple fiber crossings in each of the image voxels. The purpose of this article was to provide an introduction to the q-space formalism and the principles of basic q-space techniques together with the discussion on the advantages as well as challenges in translating these techniques into the clinical environment. A review of the currently used q-space-based protocols in clinical research is also provided.

Mapping of the mouse olfactory system with manganese-enhanced magnetic resonance imaging and diffusion tensor imaging

As the power of studying mouse genetics and behavior advances, research tools to examine systems level connectivity in the mouse are critically needed. In this study, we compared statistical mapping of the olfactory system in adult mice using manganese-enhanced MRI (MEMRI) and diffusion tensor imaging (DTI) with probabilistic tractography. The primary goal was to determine whether these complementary techniques can determine mouse olfactory bulb (OB) connectivity consistent with known anatomical connections. For MEMRI, 3D T1-weighted images were acquired before and after bilateral nasal administration of MnCl(2) solution. Concomitantly, high-resolution diffusion-tensor images were obtained ex vivo from a second group of mice and processed with a probabilistic tractography algorithm originating in the OB. Incidence maps were created by co-registering and overlaying data from the two scan modalities. The resulting maps clearly show pathways between the OB and amygdala, piriform cortex, caudate putamen, and olfactory cortex in both the DTI and MEMRI techniques that are consistent with the known anatomical connections. These data demonstrate that MEMRI and DTI are complementary, high-resolution neuroimaging tools that can be applied to mouse genetic models of olfactory and limbic system connectivity.

Fast approximate stochastic tractography

Many different probabilistic tractography methods have been proposed in the literature to overcome the limitations of classical deterministic tractography: (i) lack of quantitative connectivity information; and (ii) robustness to noise, partial volume effects and selection of seed region. However, these methods rely on Monte Carlo sampling techniques that are computationally very demanding. This study presents an approximate stochastic tractography algorithm (FAST) that can be used interactively, as opposed to having to wait several minutes to obtain the output after marking a seed region. In FAST, tractography is formulated as a Markov chain that relies on a transition tensor. The tensor is designed to mimic the features of a well-known probabilistic tractography method based on a random walk model and Monte-Carlo sampling, but can also accommodate other propagation rules. Compared to the baseline algorithm, our method circumvents the sampling process and provides a deterministic solution at the expense of partially sacrificing sub-voxel accuracy. Therefore, the method is strictly speaking not stochastic, but provides a probabilistic output in the spirit of stochastic tractography methods. FAST was compared with the random walk model using real data from 10 patients in two different ways: 1. the probability maps produced by the two methods on five well-known fiber tracts were directly compared using metrics from the image registration literature; and 2. the connectivity measurements between different regions of the brain given by the two methods were compared using the correlation coefficient ρ. The results show that the connectivity measures provided by the two algorithms are well-correlated (ρ = 0.83), and so are the probability maps (normalized cross correlation 0.818 ± 0.081). The maps are also qualitatively (i.e., visually) very similar. The proposed method achieves a 60x speed-up (7 s vs. 7 min) over the Monte Carlo sampling scheme, therefore enabling interactive probabilistic tractography: the user can quickly modify the seed region if he is not satisfied with the output without having to wait on average 7 min.

Three-dimensional interactive and stereotactic human brain atlas of white matter tracts

We present a human brain atlas of white matter (WM) tracts containing 40 major tracts, which is three-dimensional (3D), segmented, labeled, interactive, stereotactic and correlated to structure and vasculature. We consider: (1) WM accuracy by correlating WM tracts to underlying neuroanatomy and quantifying them; (2) balance between realism and completeness by processing a sequence of track volumes generated for various parameters with the increasing track number to enable a tract "shape convergence". MPRAGE and DTI in 64 directions of the same subject were acquired on 3 Tesla. The method has three steps: DTI-MPRAGE registration, 3D tract generation from DTI, to WM reconstruction from MPRAGE to parcellation into 17 components. 82 track volumes were generated for a wide spectrum of parameter values: Fractional Anisotropy threshold in [0.0125, 0.55] and trajectory angle lower than 45°, 60°, 65°, 70°, 75°, 80°, 85°, 90°. For each tract, a sequence of track volumes was processed to create/edit contours delineating this tract to achieve its shape convergence. The parcellated tracts were grouped into commissures, associations, projections and posterior fossa tracts, and labeled following Terminologia Anatomica. To facilitate that, a dedicated tract editor is developed which processes multiple track volumes, handles tracts in three representations (tracks, contours, envelopes); provides editing/visualization simultaneously on axial, coronal, sagittal planes; enables tract labeling and coloring; and provides numerous tools (track counting, smoothing and length thresholding; representation conversion and saving; structural atlas support). A stereotactic tract atlas along with parcellated WM was developed to explore in real-time any individual tract or their groups along with surrounding neuroanatomy.

Can spherical deconvolution provide more information than fiber orientations? Hindrance modulated orientational anisotropy, a true-tract specific index to characterize white matter diffusion

Diffusion tensor imaging (DTI) methods are widely used to reconstruct white matter trajectories and to quantify tissue changes using the average diffusion properties of each brain voxel. Spherical deconvolution (SD) methods have been developed to overcome the limitations of the diffusion tensor model in resolving crossing fibers and to improve tractography reconstructions. However, the use of SD methods to obtain quantitative indices of white matter integrity has not been extensively explored. In this study, we show that the hindrance modulated orientational anisotropy (HMOA) index, defined as the absolute amplitude of each lobe of the fiber orientation distribution, can be used as a compact measure to characterize the diffusion properties along each fiber orientation in white matter regions with complex organization. We demonstrate that the HMOA is highly sensitive to changes in fiber diffusivity (e.g., myelination processes or axonal loss) and to differences in the microstructural organization of white matter like axonal diameter and fiber dispersion. Using simulations to describe diffusivity changes observed in normal brain development and disorders, we observed that the HMOA is able to identify white matter changes that are not detectable with conventional DTI indices. We also show that the HMOA index can be used as an effective threshold for in vivo data to improve tractography reconstructions and to better map white matter complexity inside the brain. In conclusion, the HMOA represents a true tract-specific and sensitive index and provides a compact characterization of white matter diffusion properties with potential for widespread application in normal and clinical populations.

The geometric structure of the brain fiber pathways

The structure of the brain as a product of morphogenesis is difficult to reconcile with the observed complexity of cerebral connectivity. We therefore analyzed relationships of adjacency and crossing between cerebral fiber pathways in four nonhuman primate species and in humans by using diffusion magnetic resonance imaging. The cerebral fiber pathways formed a rectilinear three-dimensional grid continuous with the three principal axes of development. Cortico-cortical pathways formed parallel sheets of interwoven paths in the longitudinal and medio-lateral axes, in which major pathways were local condensations. Cross-species homology was strong and showed emergence of complex gyral connectivity by continuous elaboration of this grid structure. This architecture naturally supports functional spatio-temporal coherence, developmental path-finding, and incremental rewiring with correlated adaptation of structure and function in cerebral plasticity and evolution.

Bilateral subcortical heterotopia with partial callosal agenesis in a mouse mutant

Cognition and behavior depend on the precise placement and interconnection of complex ensembles of neurons in cerebral cortex. Mutations that disrupt migration of immature neurons from the ventricular zone to the cortical plate have provided major insight into mechanisms of brain development and disease. We have discovered a new and highly penetrant spontaneous mutation that leads to large nodular bilateral subcortical heterotopias with partial callosal agenesis. The mutant phenotype was first detected in a colony of fully inbred BXD29 mice already known to harbor a mutation in Tlr4. Neurons confined to the heterotopias are mainly born in midgestation to late gestation and would normally have migrated into layers 2-4 of overlying neocortex. Callosal cross-sectional area and fiber number are reduced up to 50% compared with coisogenic wildtype BXD29 substrain controls. Mutants have a pronounced and highly selective defect in rapid auditory processing. The segregation pattern of the mutant phenotype is most consistent with a two-locus autosomal recessive model, and selective genotyping definitively rules out the Tlr4 mutation as a cause. The discovery of a novel mutation with strong pleiotropic anatomical and behavioral effects provides an important new resource for dissecting molecular mechanisms and functional consequences of errors of neuronal migration.

Characteristics and variability of structural networks derived from diffusion tensor imaging

Structural brain networks were constructed based on diffusion tensor imaging (DTI) data of 59 young healthy male adults. The networks had 68 nodes, derived from FreeSurfer parcellation of the cortical surface. By means of streamline tractography, the edge weight was defined as the number of streamlines between two nodes normalized by their mean volume. Specifically, two weighting schemes were adopted by considering various biases from fiber tracking. The weighting schemes were tested for possible bias toward the physical size of the nodes. A novel thresholding method was proposed using the variance of number of streamlines in fiber tracking. The backbone networks were extracted and various network analyses were applied to investigate the features of the binary and weighted backbone networks. For weighted networks, a high correlation was observed between nodal strength and betweenness centrality. Despite similar small-worldness features, binary networks and weighted networks are distinctive in many aspects, such as modularity and nodal betweenness centrality. Inter-subject variability was examined for the weighted networks, along with the test-retest reliability from two repeated scans on 44 of the 59 subjects. The inter-/intra-subject variability of weighted networks was discussed in three levels - edge weights, local metrics, and global metrics. The variance of edge weights can be very large. Although local metrics show less variability than the edge weights, they still have considerable amounts of variability. Weighting scheme one, which scales the number of streamlines by their lengths, demonstrates stable intra-class correlation coefficients against thresholding for global efficiency, clustering coefficient and diversity. The intra-class correlation analysis suggests the current approach of constructing weighted network has a reasonably high reproducibility for most global metrics.

Accelerated diffusion spectrum imaging in the human brain using compressed sensing

We developed a novel method to accelerate diffusion spectrum imaging using compressed sensing. The method can be applied to either reduce acquisition time of diffusion spectrum imaging acquisition without losing critical information or to improve the resolution in diffusion space without increasing scan time. Unlike parallel imaging, compressed sensing can be applied to reconstruct a sub-Nyquist sampled dataset in domains other than the spatial one. Simulations of fiber crossings in 2D and 3D were performed to systematically evaluate the effect of compressed sensing reconstruction with different types of undersampling patterns (random, gaussian, Poisson disk) and different acceleration factors on radial and axial diffusion information. Experiments in brains of healthy volunteers were performed, where diffusion space was undersampled with different sampling patterns and reconstructed using compressed sensing. Essential information on diffusion properties, such as orientation distribution function, diffusion coefficient, and kurtosis is preserved up to an acceleration factor of R = 4.

The Human Connectome Project: a data acquisition perspective

The Human Connectome Project (HCP) is an ambitious 5-year effort to characterize brain connectivity and function and their variability in healthy adults. This review summarizes the data acquisition plans being implemented by a consortium of HCP investigators who will study a population of 1200 subjects (twins and their non-twin siblings) using multiple imaging modalities along with extensive behavioral and genetic data. The imaging modalities will include diffusion imaging (dMRI), resting-state fMRI (R-fMRI), task-evoked fMRI (T-fMRI), T1- and T2-weighted MRI for structural and myelin mapping, plus combined magnetoencephalography and electroencephalography (MEG/EEG). Given the importance of obtaining the best possible data quality, we discuss the efforts underway during the first two years of the grant (Phase I) to refine and optimize many aspects of HCP data acquisition, including a new 7T scanner, a customized 3T scanner, and improved MR pulse sequences.

Histological validation of DW-MRI tractography in human postmortem tissue

Despite several previous attempts, histological validation of diffusion-weighted magnetic resonance imaging (DW-MRI)-based tractography as true axonal fiber pathways remains difficult. In the present study, we establish a method to compare histological and tractography data precisely enough for statements on the level of single tractography pathways. To this end, we used carbocyanine dyes to trace connections in human postmortem tissue and aligned them to high-resolution DW-MRI of the same tissue processed within the diffusion tensor imaging (DTI) formalism. We provide robust definitions of sensitivity (true positives) and specificity (true negatives) for DTI tractography and characterize tractography paths in terms of receiver operating characteristics. With sensitivity and specificity rates of approximately 80%, we could show a clear correspondence between histological and inferred tracts. Furthermore, we investigated the effect of fractional anisotropy (FA) thresholds for the tractography and identified FA values between 0.02 and 0.08 as optimal in our study. Last, we validated the course of entire tractography curves to move beyond correctness determination based on pairs of single points on a tract. Thus, histological techniques, in conjunction with alignment and processing tools, may serve as an important validation method of DW-MRI on the level of inferred tractography projections between brain areas.

A tractography study in dyslexia: neuroanatomic correlates of orthographic, phonological and speech processing

Diffusion tensor imaging tractography is a structural magnetic resonance imaging technique allowing reconstruction and assessment of the integrity of three dimensional white matter tracts, as indexed by their fractional anisotropy. It is assumed that the left arcuate fasciculus plays a crucial role for reading development, as it connects two regions of the reading network, the left temporoparietal region and the left inferior frontal gyrus, for which atypical functional activation and lower fractional anisotropy values have been reported in dyslexic readers. In addition, we explored the potential role of the left inferior fronto-occipital fasciculus, which might connect a third region of the reading network, the left ventral occipitotemporal region with the left inferior frontal gyrus. In the present study, 20 adults with dyslexia and 20 typical reading adults were scanned using diffusion tensor imaging, and the bilateral arcuate fasciculus and the left inferior fronto-occipital fasciculus were delineated. Group comparisons show a significantly reduced fractional anisotropy in the left arcuate fasciculus of adults with dyslexia, in particular in the segment that directly connects posterior temporal and frontal areas. This fractional anisotropy reduction might reflect a lower degree of myelination in the dyslexic sample, as it co-occurred with a group difference in radial diffusivity. In contrast, no significant group differences in fractional anisotropy were found in the right arcuate fasciculus or in the left inferior fronto-occipital fasciculus. Correlational analyses (controlled for reading status) demonstrated a specific relation between performance on phoneme awareness and speech perception and the integrity of left arcuate fasciculus as indexed by fractional anisotropy, and between orthographic processing and fractional anisotropy values in left inferior fronto-occipital fasciculus. The present study reveals structural anomalies in the left arcuate fasciculus in adults with dyslexia. This finding corroborates current hypotheses of dyslexia as a disorder of network connections. In addition, our study demonstrates a correlational double dissociation, which might reflect neuroanatomical correlates of the dual route reading model: the left arcuate fasciculus seems to sustain the dorsal phonological route underlying grapheme-phoneme decoding, while the left inferior fronto-occipital fasciculus seems to sustain the ventral orthographic route underlying reading by direct word access.

Patient-tailored connectomics visualization for the assessment of white matter atrophy in traumatic brain injury

Available approaches to the investigation of traumatic brain injury (TBI) are frequently hampered, to some extent, by the unsatisfactory abilities of existing methodologies to efficiently define and represent affected structural connectivity and functional mechanisms underlying TBI-related pathology. In this paper, we describe a patient-tailored framework which allows mapping and characterization of TBI-related structural damage to the brain via multimodal neuroimaging and personalized connectomics. Specifically, we introduce a graphically driven approach for the assessment of trauma-related atrophy of white matter connections between cortical structures, with relevance to the quantification of TBI chronic case evolution. This approach allows one to inform the formulation of graphical neurophysiological and neuropsychological TBI profiles based on the particular structural deficits of the affected patient. In addition, it allows one to relate the findings supplied by our workflow to the existing body of research that focuses on the functional roles of the cortical structures being targeted. A graphical means for representing patient TBI status is relevant to the emerging field of personalized medicine and to the investigation of neural atrophy.