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

Preoperative identification of the facial nerve in patients with large cerebellopontine angle tumors using high-density diffusion tensor imaging

OBJECT

Facial nerve paresis can be a devastating complication following resection of large (> 2.5 cm) cerebellopontine angle (CPA) tumors. The authors have developed and used a new high-density diffusion tensor imaging (HD-DT imaging) method, aimed at preoperatively identifying the location and course of the facial nerve in relation to large CPA tumors. Their study objective was to preoperatively identify the facial nerve in patients with large CPA tumors and compare their HD-DT imaging method with a traditional standard DT imaging method and correlate with intraoperative findings.

METHODS

The authors prospectively studied 5 patients with large (> 2.5 cm) CPA tumors. All patients underwent preoperative traditional standard- and HD-DT imaging. Imaging results were correlated with intraoperative findings.

RESULTS

Utilizing their HD-DT imaging method, the authors positively identified the location and course of the facial nerve in all patients. In contrast, using a standard DT imaging method, the authors were unable to identify the facial nerve in 4 of the 5 patients.

CONCLUSIONS

The HD-DT imaging method that the authors describe and use has proven to be a powerful, accurate, and rapid method for preoperatively identifying the facial nerve in relation to large CPA tumors. Routine integration of HD-DT imaging in preoperative planning for CPA tumor resection could lead to improved facial nerve preservation.

Functional MRI and diffusion tensor imaging of brain reorganization after experimental stroke

The potential of the adult brain to reorganize after ischemic injury is critical for functional recovery and provides a significant target for therapeutic strategies to promote brain repair. Despite the accumulating evidence of brain plasticity, the interaction and significance of morphological and physiological modifications in post-stroke brain tissue remain mostly unclear. Neuroimaging techniques such as functional MRI (fMRI) and diffusion tensor imaging (DTI) enable in vivo assessment of the spatial and temporal pattern of functional and structural changes inside and outside ischemic lesion areas. This can contribute to the elucidation of critical aspects in post-stroke brain remodeling. Task/stimulus-related fMRI, resting-state fMRI, or pharmacological MRI enables direct or indirect measurement of neuronal activation, functional connectivity, or neurotransmitter system responses, respectively. DTI allows estimation of the structural integrity and connectivity of white matter tracts. Together, these MRI methods provide an unprecedented means to (a) measure longitudinal changes in tissue structure and function close by and remote from ischemic lesion areas, (b) evaluate the organizational profile of neural networks after stroke, and (c) identify degenerative and restorative processes that affect post-stroke functional outcome. Besides, the availability of MRI in clinical institutions as well as research laboratories provides an optimal basis for translational research on stroke recovery. This review gives an overview of the current status and perspectives of fMRI and DTI applications to study brain reorganization in experimental stroke models.

Cortical control of inhibition of return: evidence from patients with inferior parietal damage and visual neglect

Inhibition of return (IOR) refers to slower reaction times to targets presented at previously stimulated or inspected locations. This phenomenon biases orienting towards novel locations and is functional to an effective exploration of the environment. Patients with right brain damage and left visual neglect explore their environment asymmetrically, with strong difficulties to orient attention to left-sided objects. We show for the first time a dissociation between manual and saccadic IOR in neglect. Our patients demonstrated facilitation, instead of inhibition, for repeated right-sided targets with manual responses, but normal IOR to right-sided targets with saccadic responses. All neglect patients had damage to the supramarginal gyrus in the right parietal lobe, or to its connections with the ipsilateral prefrontal cortex. We concluded that IOR with manual responses relies on fronto-parietal attentional networks in the right hemisphere, whose functioning is typically impaired in neglect patients. Saccadic IOR may instead depend on circuits less likely to be damaged in neglect, such as the retinotectal visual pathway.

k-space and q-space: combining ultra-high spatial and angular resolution in diffusion imaging using ZOOPPA at 7 T

There is ongoing debate whether using a higher spatial resolution (sampling k-space) or a higher angular resolution (sampling q-space angles) is the better way to improve diffusion MRI (dMRI) based tractography results in living humans. In both cases, the limiting factor is the signal-to-noise ratio (SNR), due to the restricted acquisition time. One possible way to increase the spatial resolution without sacrificing either SNR or angular resolution is to move to a higher magnetic field strength. Nevertheless, dMRI has not been the preferred application for ultra-high field strength (7 T). This is because single-shot echo-planar imaging (EPI) has been the method of choice for human in vivo dMRI. EPI faces several challenges related to the use of a high resolution at high field strength, for example, distortions and image blurring. These problems can easily compromise the expected SNR gain with field strength. In the current study, we introduce an adapted EPI sequence in conjunction with a combination of ZOOmed imaging and Partially Parallel Acquisition (ZOOPPA). We demonstrate that the method can produce high quality diffusion-weighted images with high spatial and angular resolution at 7 T. We provide examples of in vivo human dMRI with isotropic resolutions of 1 mm and 800 μm. These data sets are particularly suitable for resolving complex and subtle fiber architectures, including fiber crossings in the white matter, anisotropy in the cortex and fibers entering the cortex.

A review of diffusion tensor magnetic resonance imaging computational methods and software tools

In this work we provide an up-to-date short review of computational magnetic resonance imaging (MRI) and software tools that are widely used to process and analyze diffusion-weighted MRI data. A review of different methods used to acquire, model and analyze diffusion-weighted imaging data (DWI) is first provided with focus on diffusion tensor imaging (DTI). The major preprocessing, processing and post-processing procedures applied to DTI data are discussed. A list of freely available software packages to analyze diffusion MRI data is also provided.

Probing brain connectivity by combined analysis of diffusion MRI tractography and electrocorticography

Electrocorticography (ECoG) allows for measurement of task-related local field potentials directly from cortex in neurosurgical patients. Diffusion tensor imaging (DTI) tractography is an MRI technique that allows for reconstruction of brain white matter tracts, which can be used to infer structural connectivity. This paper reports a novel merger of these two modalities. A processing stream is described in which fiber tracts near intracranial macroelectrodes showing task-related functional responses are isolated to explore structural networks related to working memory maintenance. Results show that ECoG-constrained tractography is useful for revealing structural connectivity patterns related to spatially- and temporally-specific functional responses.

Diffusion MRI at 25: exploring brain tissue structure and function

Diffusion MRI (or dMRI) came into existence in the mid-1980s. During the last 25 years, diffusion MRI has been extraordinarily successful (with more than 300,000 entries on Google Scholar for diffusion MRI). Its main clinical domain of application has been neurological disorders, especially for the management of patients with acute stroke. It is also rapidly becoming a standard for white matter disorders, as diffusion tensor imaging (DTI) can reveal abnormalities in white matter fiber structure and provide outstanding maps of brain connectivity. The ability to visualize anatomical connections between different parts of the brain, non-invasively and on an individual basis, has emerged as a major breakthrough for neurosciences. The driving force of dMRI is to monitor microscopic, natural displacements of water molecules that occur in brain tissues as part of the physical diffusion process. Water molecules are thus used as a probe that can reveal microscopic details about tissue architecture, either normal or in a diseased state.

Monkey to human comparative anatomy of the frontal lobe association tracts

The greater expansion of the frontal lobes along the phylogeny scale has been interpreted as the signature of evolutionary changes underlying higher cognitive abilities in humans functions in humans. However, it is unknown how an increase in number of gyri, sulci and cortical areas in the frontal lobe have coincided with a parallel increase in connectivity. Here, using advanced tractography based on spherical deconvolution, we produced an atlas of human frontal association connections that we compared with axonal tracing studies of the monkey brain. We report several similarities between human and monkey in the cingulum, uncinate, superior longitudinal fasciculus, frontal aslant tract and orbito-polar tract. These similarities suggest to preserved functions across anthropoids. In addition, we found major differences in the arcuate fasciculus and the inferior fronto-occipital fasciculus. These differences indicate possible evolutionary changes in the connectional anatomy of the frontal lobes underlying unique human abilities.

The influence of complex white matter architecture on the mean diffusivity in diffusion tensor MRI of the human brain

In diffusion tensor magnetic resonance imaging (DT-MRI), limitations concerning complex fiber architecture (when an image voxel contains fiber populations with more than one dominant orientation) are well-known. Fractional anisotropy (FA) values are lower in such areas because of a lower directionality of diffusion on the voxel-scale, which makes the interpretation of FA less straightforward. Moreover, the interpretation of the axial and radial diffusivities is far from trivial when there is more than one dominant fiber orientation within a voxel. In this work, using (i) theoretical considerations, (ii) simulations, and (iii) experimental data, it is demonstrated that the mean diffusivity (or the trace of the diffusion tensor) is lower in complex white matter configurations, compared with tissue where there is a single dominant fiber orientation within the voxel. We show that the magnitude of this reduction depends on various factors, including configurational and microstructural properties (e.g., the relative contributions of different fiber populations) and acquisition settings (e.g., the b-value). These results increase our understanding of the quantitative metrics obtained from DT-MRI and, in particular, the effect of the microstructural architecture on the mean diffusivity. More importantly, they reinforce the growing awareness that differences in DT-MRI metrics need to be interpreted cautiously.

Mapping the human connectome at multiple scales with diffusion spectrum MRI

The global structural connectivity of the brain, the human connectome, is now accessible at millimeter scale with the use of MRI. In this paper, we describe an approach to map the connectome by constructing normalized whole-brain structural connection matrices derived from diffusion MRI tractography at 5 different scales. Using a template-based approach to match cortical landmarks of different subjects, we propose a robust method that allows (a) the selection of identical cortical regions of interest of desired size and location in different subjects with identification of the associated fiber tracts (b) straightforward construction and interpretation of anatomically organized whole-brain connection matrices and (c) statistical inter-subject comparison of brain connectivity at various scales. The fully automated post-processing steps necessary to build such matrices are detailed in this paper. Extensive validation tests are performed to assess the reproducibility of the method in a group of 5 healthy subjects and its reliability is as well considerably discussed in a group of 20 healthy subjects.

In vivo quantification of global connectivity in the human corpus callosum

Histological studies on nonhuman primates have shown a rich topography of homotopic (i.e., going to the same regions) or heterotopic (i.e., going to different regions) callosal projections. Unfortunately, a complete within-subject mapping of commissural projections in humans has been limited due to the inability of typical imaging methods to detect lateral projections in posterior cortical regions. Here, we set out to map callosal projection connectivity, at the single subject level (N=6), by combining high angular resolution diffusion weighted imaging and a novel multi-stage, region-of-interest (ROI) based fiber tracking approach. With these methods we were able to obtain a consistent increase in coverage of lateral projections to posterior cortical regions. Using 70 automatically segmented ROIs in each hemisphere and permutation statistics, we characterized significant interhemispheric connectivity patterns within each subject and observed: (1) consistent projections to frontal, parietal and occipital, but not temporal, areas, (2) a greater relative proportion of homotopic than heterotopic connections, and (3) commissural projections to the basal ganglia and thalamus that are consistent with human and nonhuman primate neuroanatomical literature. These results illustrate the first full connectivity analysis of the human corpus callosum, revealing several patterns consistent with histological findings in the nonhuman primate.

Diffusion MR imaging: basic principles

From their origin as simple techniques primarily used for detecting acute cerebral ischemia, diffusion MR imaging techniques have rapidly evolved into a versatile set of tools that provide the only noninvasive means of characterizing brain microstructure and connectivity, becoming a mainstay of both clinical and investigational brain MR imaging. In this article, the basic principles required for understanding diffusion MR imaging techniques are reviewed with clinical neuroradiologists in mind.

Large-scale brain networks and psychopathology: a unifying triple network model

The science of large-scale brain networks offers a powerful paradigm for investigating cognitive and affective dysfunction in psychiatric and neurological disorders. This review examines recent conceptual and methodological developments which are contributing to a paradigm shift in the study of psychopathology. I summarize methods for characterizing aberrant brain networks and demonstrate how network analysis provides novel insights into dysfunctional brain architecture. Deficits in access, engagement and disengagement of large-scale neurocognitive networks are shown to play a prominent role in several disorders including schizophrenia, depression, anxiety, dementia and autism. Synthesizing recent research, I propose a triple network model of aberrant saliency mapping and cognitive dysfunction in psychopathology, emphasizing the surprising parallels that are beginning to emerge across psychiatric and neurological disorders.

Differential development of human brain white matter tracts

Neuroscience is increasingly focusing on developmental factors related to human structural and functional connectivity. Unfortunately, to date, diffusion-based imaging approaches have only contributed modestly to these broad objectives, despite the promise of diffusion-based tractography. Here, we report a novel data-driven approach to detect similarities and differences among white matter tracts with respect to their developmental trajectories, using 64-direction diffusion tensor imaging. Specifically, using a cross-sectional sample comprising 144 healthy individuals (7 to 48 years old), we applied k-means cluster analysis to separate white matter voxels based on their age-related trajectories of fractional anisotropy. Optimal solutions included 5-, 9- and 14-clusters. Our results recapitulate well-established tracts (e.g., internal and external capsule, optic radiations, corpus callosum, cingulum bundle, cerebral peduncles) and subdivisions within tracts (e.g., corpus callosum, internal capsule). For all but one tract identified, age-related trajectories were curvilinear (i.e., inverted 'U-shape'), with age-related increases during childhood and adolescence followed by decreases in middle adulthood. Identification of peaks in the trajectories suggests that age-related losses in fractional anisotropy occur as early as 23 years of age, with mean onset at 30 years of age. Our findings demonstrate that data-driven analytic techniques may be fruitfully applied to extant diffusion tensor imaging datasets in normative and neuropsychiatric samples.

Tractography: where do we go from here?

Diffusion tractography offers enormous potential for the study of human brain anatomy. However, as a method to study brain connectivity, tractography suffers from limitations, as it is indirect, inaccurate, and difficult to quantify. Despite these limitations, appropriate use of tractography can be a powerful means to address certain questions. In addition, while some of tractography's limitations are fundamental, others could be alleviated by methodological and technological advances. This article provides an overview of diffusion magnetic resonance tractography methods with a focus on how future advances might address challenges in measuring brain connectivity. Parts of this review are somewhat provocative, in the hope that they may trigger discussions possibly lacking in a field where the apparent simplicity of the methods (compared to their functional magnetic resonance imaging counterparts) can hide some fundamental issues that ultimately hinder the interpretation of findings, and cast doubt as to what tractography can really teach us about human brain anatomy.

Diffusion tensor imaging of cerebral white matter integrity in cognitive aging

In this article we review recent research on diffusion tensor imaging (DTI) of white matter (WM) integrity and the implications for age-related differences in cognition. Neurobiological mechanisms defined from DTI analyses suggest that a primary dimension of age-related decline in WM is a decline in the structural integrity of myelin, particularly in brain regions that myelinate later developmentally. Research integrating behavioral measures with DTI indicates that WM integrity supports the communication among cortical networks, particularly those involving executive function, perceptual speed, and memory (i.e., fluid cognition). In the absence of significant disease, age shares a substantial portion of the variance associated with the relation between WM integrity and fluid cognition. Current data are consistent with one model in which age-related decline in WM integrity contributes to a decreased efficiency of communication among networks for fluid cognitive abilities. Neurocognitive disorders for which older adults are at risk, such as depression, further modulate the relation between WM and cognition, in ways that are not as yet entirely clear. Developments in DTI technology are providing a new insight into both the neurobiological mechanisms of aging WM and the potential contribution of DTI to understanding functional measures of brain activity. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.

A novel approach for improved tractography and quantitative analysis of probabilistic fibre tracking curves

This paper presents a novel approach for improved diffusion tensor fibre tractography, aiming to tackle a number of the limitations of current fibre tracking algorithms, and describes a quantitative analysis tool for probabilistic tracking algorithms. We consider the sampled random paths generated by a probabilistic tractography algorithm from a seed point as a set of curves, and develop a statistical framework for analysing the curve-set geometrically that finds the average curve and dispersion measures of the curve-set statistically. This study is motivated firstly by the goal of developing a robust fibre tracking algorithm, combining the power of both deterministic and probabilistic tracking methods using average curves. These typical curves produce strong connections to every anatomically distinct fibre tract from a seed point and also convey important information about the underlying probability distribution. These single well-defined trajectories overcome a number of the limitations of deterministic and probabilistic approaches. A new clustering algorithm for branching curves is employed to separate fibres into branches before applying the averaging methods. Secondly, a quantitative analysis tool for probabilistic tracking methods is introduced using statistical measures of curve-sets. Results on phantom and in vivo data confirm the efficiency and effectiveness of the proposed approach for the tracking algorithm and the quantitative analysis of the probabilistic methods.

Neurological imaging: statistics behind the pictures

Neurological imaging represents a powerful paradigm for investigation of brain structure, physiology and function across different scales. The diverse phenotypes and significant normal and pathological brain variability demand reliable and efficient statistical methodologies to model, analyze and interpret raw neurological images and derived geometric information from these images. The validity, reproducibility and power of any statistical brain map require appropriate inference on large cohorts, significant community validation, and multidisciplinary collaborations between physicians, engineers and statisticians.

Reflections on the theory of "silver bullet" octreotide tracers: implications for ligand-receptor interactions in the age of peptides, heterodimers, receptor mosaics, truncated receptors, and multifractal analysis

The classical attitude of Nuclear Medicine practitioners on matters of peptide-receptor interactions has maintained an intrinsic monogamic character since many years. New advances in the field of biochemistry and even in clinical Nuclear Medicine have challenged this type of thinking, which prompted me to work on this review. The central issue of this paper will be the use of somatostatin analogs, i.e., octreotide, in clinical imaging procedures as well as in relation to neuroendocirne tumors. Newly described characteristics of G-protein coupled receptors such as the formation of receptor mosaics will be discussed. A small section will enumerate the regulatory processes found in the cell membrane. Possible new interpretations, other than tumor detection, based on imaging procedures with somatostatin analogs will be presented. The readers will be taken to situations such as inflammation, nociception, mechanosensing, chemosensing, fibrosis, taste, and vascularity where somatostatin is involved. Thyroid-associated orbitopathy will be used as a model for the development of multi-agent therapeutics. The final graphical summary depicts the multifactorial properties of ligand binding.

A diffusion tensor brain template for rhesus macaques

Diffusion tensor imaging (DTI) is a powerful and noninvasive imaging method for characterizing tissue microstructure and white matter organization in the brain. While it has been applied extensively in research studies of the human brain, DTI studies of non-human primates have been performed only recently. The growing application of DTI in rhesus monkey studies would significantly benefit from a standardized framework to compare findings across different studies. A very common strategy for image analysis is to spatially normalize (co-register) the individual scans to a representative template space. This paper presents the development of a DTI brain template, UWRMAC-DTI271, for adolescent Rhesus Macaque (Macaca mulatta) monkeys. The template was generated from 271 rhesus monkeys, collected as part of a unique brain imaging genetics study. It is the largest number of animals ever used to generate a computational brain template, which enables the generation of a template that has high image quality and accounts for variability in the species. The quality of the template is further ensured with the use of DTI-TK, a well-tested and high-performance DTI spatial normalization method in human studies. We demonstrated its efficacy in monkey studies for the first time by comparing it to other commonly used scalar-methods for DTI normalization. It is anticipated that this template will play an important role in facilitating cross-site voxelwise DTI analyses in Rhesus Macaques. Such analyses are crucial in investigating the role of white matter structure in brain function, development, and other psychopathological disorders for which there are well-validated non-human primate models.

Integrating temporal and spatial scales: human structural network motifs across age and region of interest size

Human brain networks can be characterized at different temporal or spatial scales given by the age of the subject or the spatial resolution of the neuroimaging method. Integration of data across scales can only be successful if the combined networks show a similar architecture. One way to compare networks is to look at spatial features, based on fiber length, and topological features of individual nodes where outlier nodes form single node motifs whose frequency yields a fingerprint of the network. Here, we observe how characteristic single node motifs change over age (12–23 years) and network size (414, 813, and 1615 nodes) for diffusion tensor imaging structural connectivity in healthy human subjects. First, we find the number and diversity of motifs in a network to be strongly correlated. Second, comparing different scales, the number and diversity of motifs varied across the temporal (subject age) and spatial (network resolution) scale: certain motifs might only occur at one spatial scale or for a certain age range. Third, regions of interest which show one motif at a lower resolution may show a range of motifs at a higher resolution which may or may not include the original motif at the lower resolution. Therefore, both the type and localization of motifs differ for different spatial resolutions. Our results also indicate that spatial resolution has a higher effect on topological measures whereas spatial measures, based on fiber lengths, remain more comparable between resolutions. Therefore, spatial resolution is crucial when comparing characteristic node fingerprints given by topological and spatial network features. As node motifs are based on topological and spatial properties of brain connectivity networks, these conclusions are also relevant to other studies using connectome analysis.

Reconstructing micrometer-scale fiber pathways in the brain: multi-contrast optical coherence tomography based tractography

Comprehensive understanding of connective neural pathways in the brain has put great challenges on the current imaging techniques, for which three-dimensional (3D) visualization of fiber tracts with high spatiotemporal resolution is desirable. Here we present optical imaging and tractography of rat brain ex-vivo using multi-contrast optical coherence tomography (MC-OCT), which is capable of simultaneously generating depth-resolved images of reflectivity, phase retardance, optic axis orientation and, for in-vivo studies, blood flow images. Using the birefringence property of myelin sheath, nerve fiber tracts as small as a few tens of micrometers can be resolved and neighboring fiber tracts with different orientations can be distinguished in cross-sectional optical slices, 2D en-face images and 3D volumetric images. Combinational contrast of MC-OCT images enables visualization of the spatial architecture and nerve fiber orientations in the brain with unprecedented detail. The results suggest that optical tractography, by virtue of its direct accessibility to nerve fibers, has the potential to validate diffusion magnetic resonance images and investigate structural connections in normal brain and neurological disorders. In addition, an endoscopic MC-OCT may be useful in neurosurgical interventions to aid in placement of deep brain stimulating electrodes.

Diffusion imaging with prospective motion correction and reacquisition

A major source of artifacts in diffusion-weighted imaging is subject motion. Slow bulk subject motion causes misalignment of data when more than one average or diffusion gradient direction is acquired. Fast bulk subject motion can cause signal dropout artifacts in diffusion-weighted images and results in erroneous derived maps, e.g., fractional anisotropy maps. To address both types of artifacts, a fully automatic method is presented that combines prospective motion correction with a reacquisition scheme. Motion correction is based on the prospective acquisition correction method modified to work with diffusion-weighted data. The images to reacquire are determined automatically during the acquisition from the imaging data, i.e., no extra reference scan, navigators, or external devices are necessary. The number of reacquired images, i.e., the additional scan duration can be adjusted freely. Diffusion-weighted prospective acquisition correction corrects slow bulk motion well and reduces misalignment artifacts like image blurring. Mean absolute residual values for translation and rotation were <0.6 mm and 0.5°. Reacquisition of images affected by signal dropout artifacts results in diffusion maps and fiber tracking free of artifacts. The presented method allows the reduction of two types of common motion related artifacts at the cost of slightly increased acquisition time.

White matter abnormalities of fronto-striato-thalamic circuitry in obsessive-compulsive disorder: A study using diffusion spectrum imaging tractography

Previous studies have reported white matter abnormalities in patients with obsessive-compulsive disorder (OCD). This study aimed to further explore white matter abnormalities in OCD patients through diffusion spectrum imaging (DSI) and tractography of the two white matter tracts which most probably play an important role in OCD neuropathology: the anterior segment of cingulum bundles (ACB) and the anterior thalamic radiations (ATR). Twelve right-handed, medicated adult patients with OCD and 12 matched controls underwent DSI on a 3 tesla magnetic resonance imaging (MRI) system. Tractography based on DSI data was reconstructed to define the ACB and ATR. Mean generalized fractional anisotropy (GFA) was calculated for each targeted tract and was used to analyze local changes in microstructural integrity along individual tracts. There was a significantly lower mean GFA in both the right ATR and left ACB in OCD subjects compared to controls. OCD subjects also demonstrated decreased left-lateralized asymmetry of the ACB when compared to controls. Furthermore, the mean GFA of the left ACB positively correlated with OCD subjects' obsessive subscores on the Yale-Brown Obsessive-Compulsive scale. This study supports the white matter abnormalities in the ACB and ATR of OCD subjects, which corroborates neurobiological models that posit a defect in fronto-striato-thalamic circuitry in OCD.

NTU-90: a high angular resolution brain atlas constructed by q-space diffeomorphic reconstruction

We present a high angular resolution brain atlas constructed by averaging 90 diffusion spectrum imaging (DSI) datasets in the ICBM-152 space. The spatial normalization of the diffusion information was conducted by a novel q-space diffeomorphic reconstruction method, which reconstructed the spin distribution function (SDF) in the ICBM-152 space from the diffusion MR signals. The performance of this method was examined by a simulation study modeling nonlinear transformation. The result showed that the reconstructed SDFs can resolve crossing fibers and that the accumulated quantitative anisotropy can reveal the relative ratio of the fiber populations. In the in vivo study, the SDF of the constructed atlas was shown to resolve crossing fiber orientations. Further, fiber tracking showed that the atlas can be used to present the pathways of fiber bundles, and the termination locations of the fibers can provide anatomical localization of the connected cortical regions. This high angular resolution brain atlas may facilitate future connectome research on the complex structure of the human brain.

Gerstmann meets Geschwind: a crossing (or kissing) variant of a subcortical disconnection syndrome?

That disconnection causes clinical symptoms is a very influential concept in behavioral neurology. Criteria for subcortical disconnection usually are symptoms that are distinct from those following cortical lesions and damage to a single, long-range fiber tract. Yet, a recent study combining functional magnetic resonance imaging and fiber tracking concluded that a focal lesion in left parietal white matter provides the only tenable explanation for pure Gerstmann's syndrome, an enigmatic tetrad of acalculia, agraphia, finger agnosia, and left-right disorientation. Such a lesion would affect not only a single fiber tract but crossing or "kissing" of different fiber tracts and hence disconnect separate cortical networks. As fiber crossing is prominent in the cerebral white matter, the authors propose an extension to the subcortical disconnection framework that opens the door to ascribing a more diversified clinical phenomenology to white matter damage and ensuing disconnection than has been the case so far.

Emerging cerebral connectivity in the human fetal brain: an MR tractography study

Cerebral axonal connections begin to develop before birth during radial migration in each brain area. A number of theories are still actively debated regarding the link between neuronal migration, developing connectivity, and gyrification. Here, we used high angular resolution diffusion tractography on postmortem fetal human brains (postconception week (W) 17-40) to document the regression of radial and tangential organization likely to represent migration pathways and the emergence of corticocortical organization and gyrification. The dominant radial organization at W17 gradually diminished first in dorsal parieto-occipital and later in ventral frontotemporal regions with regional variation: radial organization persisted longer in the crests of gyri than at the depths of sulci. The dominant tangential organization of the ganglionic eminence at W17 also gradually disappeared by term, together with the disappearance of the ganglionic eminence. A few immature long-range association pathways were visible at W17, gradually became evident by term. Short-range corticocortical tracts emerged prior to gyrification in regions where sulci later developed. Our results suggest that the regional regression of radial organization and regional emergence of fetal brain connectivity proceeds in general from posterodorsal to anteroventral with local variations.

The connectome viewer toolkit: an open source framework to manage, analyze, and visualize connectomes

Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit - a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/

From molecules to myofibers: multiscale imaging of the myocardium

Pathology in the heart can be examined at several scales, ranging from the molecular to the macroscopic. Traditionally, fluorescence-based techniques such as flow cytometry have been used to study the myocardium at the molecular, cellular, and microscopic levels. Recent advances in magnetic resonance imaging (MRI), however, have made it possible to image certain cellular and molecular events in the myocardium noninvasively in vivo. In addition, diffusion MRI has been used to image myocardial fiber architecture and microstructure in the intact heart. Diffusion MRI tractography, in particular, is providing novel insights into myocardial microsctructure in both health and disease. Recent developments have also been made in fluorescence imaging, making it possible to image fluorescent probes in the heart of small animals noninvasively in vivo. Moreover, techniques have been developed to perform in vivo fluorescence tomography of the mouse heart. These advances in MRI and fluorescence imaging allow events in the myocardium to be imaged at several scales linking molecular changes to alterations in microstructure and microstructural changes to gross function. A complete and integrated picture of pathophysiology in the myocardium is thus obtained. This multiscale approach has the potential to be of significant value not only in preclinical research but, ultimately, in the clinical arena as well.

The loss of asymmetry and reduced interhemispheric connectivity in adolescents with autism: a study using diffusion spectrum imaging tractography

Evidence from neuroimaging and neurobiological studies suggests that abnormalities in cortical-cortical connectivity involving both local and long-distance scales may be related to autism. The present study analyzed the microstructural integrity of the long-range connectivity related to social cognition and language processing with diffusion tractography among adolescents with autism compared with neurotypical adolescents. Tract-specific analyses were used to study the long-range connectivity responsible for integrating social cognition and language processing. Specifically, three pairs of association fibers and three portions of callosal fiber tracts were analyzed. Generalized fractional anisotropy (GFA) values were measured along individual targeted fiber tracts to investigate alterations in microstructure integrity. The asymmetry patterns were also assessed in three pairs of association fibers. In neurotypical participants, we found a consistent leftward asymmetry in three pairs of association fibers. However, adolescents with autism did not demonstrate such asymmetry. Moreover, adolescents with autism had significantly lower mean GFA in three callosal fiber tracts than neurotypical participants. The loss of leftward asymmetry and reduction of interhemispheric connection in adolescents with autism suggest alterations of the long-range connectivity involved in social cognition and language processing. Our results warrant further investigation by combining developmental and neurocognitive data.

Development of a MR-visible compound for tracing neuroanatomical connections in vivo

Traditional studies of neuroanatomical connections require injection of tracer compounds into living brains, then histology of the postmortem tissue. Here, we describe and validate a compound that reveals neuronal connections in vivo, using MRI. The classic anatomical tracer CTB (cholera-toxin subunit-B) was conjugated with a gadolinium-chelate to form GdDOTA-CTB. GdDOTA-CTB was injected into the primary somatosensory cortex (S1) or the olfactory pathway of rats. High-resolution MR images were collected at a range of time points at 11.7T and 7T. The transported GdDOTA-CTB was visible for at least 1 month post-injection, clearing within 2 months. Control injections of non-conjugated GdDOTA into S1 were not transported and cleared within 1-2 days. Control injections of Gd-Albumin were not transported either, clearing within 7 days. These MR results were verified by classic immunohistochemical staining for CTB, in the same animals. The GdDOTA-CTB neuronal transport was target specific, monosynaptic, stable for several weeks, and reproducible.

An introduction to diffusion tensor image analysis

Diffusion tensor magnetic resonance imaging (DTI) is a relatively new technology that is popular for imaging the white matter of the brain. This article provides a basic and broad overview of DTI to enable the reader to develop an intuitive understanding of these types of data, and an awareness of their strengths and weaknesses.

DTI measures in crossing-fibre areas: increased diffusion anisotropy reveals early white matter alteration in MCI and mild Alzheimer's disease

Though mild cognitive impairment is an intermediate clinical state between healthy aging and Alzheimer's disease (AD), there are very few whole-brain voxel-wise diffusion MRI studies directly comparing changes in healthy control, mild cognitive impairment (MCI) and AD subjects. Here we report whole-brain findings from a comprehensive study of diffusion tensor indices and probabilistic tractography obtained in a very large population of healthy controls, MCI and probable AD subjects. As expected from the literature, all diffusion indices converged to show that the cingulum bundle, the uncinate fasciculus, the entire corpus callosum and the superior longitudinal fasciculus are the most affected white matter tracts in AD. Significant differences between MCI and AD were essentially confined to the corpus callosum. More importantly, we introduce for the first time in a degenerative disorder an application of a recently developed tensor index, the "mode" of anisotropy, as well as probabilistic crossing-fibre tractography. The mode of anisotropy specifies the type of anisotropy as a continuous measure reflecting differences in shape of the diffusion tensor ranging from planar (e.g., in regions of crossing fibres from two fibre populations of similar density or regions of "kissing" fibres) to linear (e.g., in regions where one fibre population orientation predominates), while probabilistic crossing-fibre tractography allows to accurately trace pathways from a crossing-fibre region. Remarkably, when looking for whole-brain diffusion differences between MCI patients and healthy subjects, the only region with significant abnormalities was a region of crossing fibres in the centrum semiovale, showing an increased mode of anisotropy. The only white matter region demonstrating a significant difference in correlations between neuropsychological scores and a diffusion measure (mode of anisotropy) across the three groups was the same region of crossing fibres. Further examination using probabilistic tractography established explicitly and quantitatively that this previously unreported increase of mode and co-localised increase of fractional anisotropy was explained by a relative preservation of motor-related projection fibres (at this early stage of the disease) crossing the association fibres of the superior longitudinal fasciculus. These findings emphasise the benefit of looking at the more complex regions in which spared and affected pathways are crossing to detect very early alterations of the white matter that could not be detected in regions consisting of one fibre population only. Finally, the methods used in this study may have general applicability for other degenerative disorders and, beyond the clinical sphere, they could contribute to a better quantification and understanding of subtle effects generated by normal processes such as visuospatial attention or motor learning.

Three-Dimensional In Vivo Modeling of Vestibular Schwannomas and Surrounding Cranial Nerves With Diffusion Imaging Tractography

BACKGROUND:

Preservation of cranial nerves (CNs) is of paramount concern in the treatment of vestibular schwannomas, particularly in large tumors with thinned and distorted CN fibers. However, imaging of the CN fibers surrounding vestibular schwannomas has been limited with 2-dimensional imaging alone.

OBJECTIVE:

To assess whether tractography of the CN combined with anatomic magnetic resonance imaging of the tumor can provide superior 3-dimensional (3D) visualization of tumor/CN complexes.

METHODS:

Magnetic resonance imaging at 3 T, including diffusion tensor imaging and anatomic images, were analyzed in 3 subjects with vestibular schwannomas using 3D Slicer software. The diffusion tensor images were used to track the courses of trigeminal, abducens, facial, and vestibulocochlear nerves. The anatomic images were used to model the 3D volume reconstruction of the tumor. The 2 sets of images were then superimposed through the use of linear registration.

RESULTS:

Combined 3D tumor modeling and CN tractography can effectively and consistently reconstruct the 3D spatial relationship of CN/tumor complexes and allows superior visualization compared with 2-dimensional imaging. Lateral and superior distortion of the trigeminal nerve was observed in all cases. The position of the facial nerve was primarily anteriorly and inferiorly. The gasserian ganglion and early postganglionic branches could also be visualized.

CONCLUSION:

Tractography and anatomic imaging were successfully combined to demonstrate the precise location of surrounding CN fibers. This technique can be useful in both neuronavigation and radiosurgical planning. Because knowledge of the course of these fibers is of important clinical interest, implementation of this technique may help decrease injury to CNs during treatment of these lesions.

Recent advances in diffusion MRI modeling: Angular and radial reconstruction

Recent advances in diffusion magnetic resonance image (dMRI) modeling have led to the development of several state of the art methods for reconstructing the diffusion signal. These methods allow for distinct features to be computed, which in turn reflect properties of fibrous tissue in the brain and in other organs. A practical consideration is that to choose among these approaches requires very specialized knowledge. In order to bridge the gap between theory and practice in dMRI reconstruction and analysis we present a detailed review of the dMRI modeling literature. We place an emphasis on the mathematical and algorithmic underpinnings of the subject, categorizing existing methods according to how they treat the angular and radial sampling of the diffusion signal. We describe the features that can be computed with each method and discuss its advantages and limitations. We also provide a detailed bibliography to guide the reader.

The neural architecture of the language comprehension network: converging evidence from lesion and connectivity analyses

While traditional models of language comprehension have focused on the left posterior temporal cortex as the neurological basis for language comprehension, lesion and functional imaging studies indicate the involvement of an extensive network of cortical regions. However, the full extent of this network and the white matter pathways that contribute to it remain to be characterized. In an earlier voxel-based lesion-symptom mapping analysis of data from aphasic patients (Dronkers et al., 2004), several brain regions in the left hemisphere were found to be critical for language comprehension: the left posterior middle temporal gyrus, the anterior part of Brodmann's area 22 in the superior temporal gyrus (anterior STG/BA22), the posterior superior temporal sulcus (STS) extending into Brodmann's area 39 (STS/BA39), the orbital part of the inferior frontal gyrus (BA47), and the middle frontal gyrus (BA46). Here, we investigated the white matter pathways associated with these regions using diffusion tensor imaging from healthy subjects. We also used resting-state functional magnetic resonance imaging data to assess the functional connectivity profiles of these regions. Fiber tractography and functional connectivity analyses indicated that the left MTG, anterior STG/BA22, STS/BA39, and BA47 are part of a richly interconnected network that extends to additional frontal, parietal, and temporal regions in the two hemispheres. The inferior occipito-frontal fasciculus, the arcuate fasciculus, and the middle and inferior longitudinal fasciculi, as well as transcallosal projections via the tapetum were found to be the most prominent white matter pathways bridging the regions important for language comprehension. The left MTG showed a particularly extensive structural and functional connectivity pattern which is consistent with the severity of the impairments associated with MTG lesions and which suggests a central role for this region in language comprehension.

Distortions and disconnections: disrupted brain connectivity in autism

The past few years have seen considerable interest in findings of abnormal brain connectivity in the autism spectrum disorders (ASD). We review recent work from neuroimaging and other sources, and argue that there is considerable convergent evidence suggesting that connectivity is disrupted in ASD. We point to evidence both of local over-connectivity and of long-distance under-connectivity, and describe some non-uniformities in this picture, most notably that disruptions appear more severe in later-developing cortical regions. We conclude by discussing a number of extant questions. Firstly, we consider whether aberrant connectivity should be seen as part of the primary pathogenesis of autism, or whether disrupted connectivity in ASD emerges over time. Secondly, we consider how the patterns of disrupted connectivity found in ASD might relate to those being found in a range of other disorders.

Selectively diminished corpus callosum fibers in congenital central hypoventilation syndrome

Congenital central hypoventilation syndrome (CCHS), a condition associated with mutations in the PHOX2B gene, is characterized by loss of breathing drive during sleep, insensitivity to CO2 and O2, and multiple somatomotor, autonomic, neuropsychological, and ophthalmologic deficits, including impaired intrinsic and extrinsic eye muscle control. Brain structural studies show injury in peri-callosal regions and the corpus callosum (CC), which has the potential to affect functions disturbed in the syndrome; however, the extent of CC injury in CCHS is unclear. Diffusion tensor imaging (DTI)-based fiber tractography procedures display fiber directional information and allow quantification of fiber integrity. We performed DTI in 13 CCHS children (age, 18.2±4.7 years; eight male) and 31 control (17.4±4.9 years; 18 male) subjects using a 3.0-Tesla magnetic resonance imaging scanner; CC fibers were assessed globally and regionally with tractography procedures, and fiber counts and densities compared between groups using analysis-of-covariance (covariates; age and sex). Global CC evaluation showed reduced fiber counts and densities in CCHS over control subjects (CCHS vs. controls; fiber-counts, 4490±854 vs. 5232±777, P<0.001; fiber-density, 10.0±1.5 vs. 10.8±0.9 fibers/mm2, P<0.020), and regional examination revealed that these changes are localized to callosal axons projecting to prefrontal (217±47 vs. 248±32, P<0.005), premotor (201±51 vs. 241±47, P<0.012), parietal (179±64 vs. 238±54, P<0.002), and occipital regions (363±46 vs. 431±82, P<0.004). Corpus callosum fibers in CCHS are compromised in motor, cognitive, speech, and ophthalmologic regulatory areas. The mechanisms of fiber injury are unclear, but may result from hypoxia or perfusion deficits accompanying the syndrome, or from consequences of PHOX2B action.

Estimation of fiber orientation and spin density distribution by diffusion deconvolution

A diffusion deconvolution method is proposed to apply deconvolution to the diffusion orientation distribution function (dODF) and calculate the fiber orientation distribution function (fODF), which is defined as the orientation distribution of the fiber spin density. The dODF can be obtained from q-space imaging methods such as q-ball imaging (QBI), diffusion spectrum imaging (DSI), and generalized q-sampling imaging (GQI), and thus the method can be applied to various diffusion sampling schemes. A phantom study was conducted to compare the angular resolution of the fODF with the dODF, and the in vivo datasets were acquired using single-shell, two-shell, and grid sampling schemes, which were then reconstructed by QBI, GQI, and DSI, respectively. The phantom study showed that the fODF significantly improved the angular resolution over the dODF at 45- and 60-degree crossing angles. The in vivo study showed consistent fODF regardless of the applied sampling schemes and reconstruction methods, and the ability to resolve crossing fibers was improved in reduced sampling condition. The fiber spin density obtained from deconvolution showed a higher contrast-to-noise ratio than the fractional anisotropy (FA) mapping, and further application on tractography showed that the fiber spin density can be used to determine the termination of fiber tracts. In conclusion, the proposed deconvolution method is generally applicable to different q-space imaging methods. The calculated fODF improves the angular resolution and also provides a quantitative index of fiber spin density to refine fiber tracking.

Multiplexed echo planar imaging for sub-second whole brain FMRI and fast diffusion imaging

Echo planar imaging (EPI) is an MRI technique of particular value to neuroscience, with its use for virtually all functional MRI (fMRI) and diffusion imaging of fiber connections in the human brain. EPI generates a single 2D image in a fraction of a second; however, it requires 2–3 seconds to acquire multi-slice whole brain coverage for fMRI and even longer for diffusion imaging. Here we report on a large reduction in EPI whole brain scan time at 3 and 7 Tesla, without significantly sacrificing spatial resolution, and while gaining functional sensitivity. The multiplexed-EPI (M-EPI) pulse sequence combines two forms of multiplexing: temporal multiplexing (m) utilizing simultaneous echo refocused (SIR) EPI and spatial multiplexing (n) with multibanded RF pulses (MB) to achieve m×n images in an EPI echo train instead of the normal single image. This resulted in an unprecedented reduction in EPI scan time for whole brain fMRI performed at 3 Tesla, permitting TRs of 400 ms and 800 ms compared to a more conventional 2.5 sec TR, and 2–4 times reductions in scan time for HARDI imaging of neuronal fibertracks. The simultaneous SE refocusing of SIR imaging at 7 Tesla advantageously reduced SAR by using fewer RF refocusing pulses and by shifting fat signal out of the image plane so that fat suppression pulses were not required. In preliminary studies of resting state functional networks identified through independent component analysis, the 6-fold higher sampling rate increased the peak functional sensitivity by 60%. The novel M-EPI pulse sequence resulted in a significantly increased temporal resolution for whole brain fMRI, and as such, this new methodology can be used for studying non-stationarity in networks and generally for expanding and enriching the functional information.

The microstructural integrity of the corpus callosum and associated impulsivity in alcohol dependence: a tractography-based segmentation study using diffusion spectrum imaging

Previous post-mortem and structural magnetic resonance imaging (MRI) studies in patients with alcohol dependence have demonstrated abnormalities of brain white matter. The present study investigated the microstructural integrity in the corpus callosum and the associations of this integrity with neurobehavioral assessments. Twenty-five male cases fulfilling the DSM-IV diagnosis of alcohol dependence and 15 male control subjects were scanned using a 3T MRI system. Callosal fiber tracts were reconstructed by diffusion spectrum imaging tractography and were subdivided into seven functionally distinct segments. The microstructural integrity was quantified in terms of generalized fractional anisotropy (GFA). Compared with normal subjects, men with alcohol dependence showed lower GFA values on all segments of the corpus callosum. The segment interconnecting the bilateral orbitofrontal cortices was the most affected. The score on the Barratt Impulsivity Scale showed an inverse relationship with GFA on the callosal fiber tracts connecting the bilateral orbitofrontal cortices. Furthermore, the duration of regular use was negatively associated with GFA on the callosal fiber tracts connecting the bilateral temporal and parietal cortices. Our findings suggest that a high self-rated impulsivity level was associated with low anisotropy in white matter of corpus callosum sectors extending to the orbitofrontal cortex.

In vivo mapping of microstructural somatotopies in the human corticospinal pathways

The human corticospinal pathway is organized in a body-centric (i.e., somatotopic) manner that begins in cortical cell bodies and is maintained in the axons as they project through the midbrain on their way to spinal motor neurons. The subcortical segment of this somatotopy has been described using histological methods on non-human primates but only coarsely validated from lesion studies in human patient populations. Using high definition fiber tracking (HDFT) techniques, we set out to provide the first in vivo quantitative description of the midbrain somatotopy of corticospinal fibers in humans. Multi-shell diffusion imaging and deterministic fiber tracking were used to map white matter bundles that originate in the neocortex, navigate complex fiber crossings, and project through the midbrain. These fiber bundles were segmented into premotor (dorsal premotor, ventral premotor, and supplementary motor area) and primary motor sections based on the cortical origin of each fiber streamline. With HDFT, we were able to reveal several unique corticospinal patterns, including the cortical origins of ventral premotor fibers and small (∼ 1-2 mm) shifts in the midbrain location of premotor versus primary motor cortex fibers. More importantly, within the relatively small diameter of the pyramidal tracts (∼ 5 mm), we were able to map and quantify the direction of the corticospinal somatotopy. These results show how an HDFT approach to white matter mapping provides the first in vivo, quantitative mapping of subcortical corticospinal topographies at resolutions previously only available with postmortem histological techniques.

Diffusion tensor imaging correlates with lesion volume in cerebral hemisphere infarctions

Background

Both a large lesion volume and abnormalities in diffusion tensor imaging are independently associated with a poor prognosis after cerebral infarctions. Therefore, we assume that they are associated. This study assessed the associations between lesion volumes and diffusion tensor imaging in patients with a right-sided cerebral infarction.

Methods

The lesion volumes of 33 patients (age 65.9 ± 8.7, 26 males and 7 females) were imaged using computed tomography (CT) in the acute phase (within 3-4 hours) and magnetic resonance imaging (MRI) in the chronic phase (follow-up at 12 months, with a range of 8-27 months). The chronic-phase fractional anisotropy (FA) and mean diffusivity (MD) values were measured at the site of the infarct and selected white matter tracts. Neurological tests in both the acute and chronic phases, and DTI lateralization were assessed with the Wilcoxon signed-rank test. The effects of thrombolytic therapy (n = 10) were assessed with the Mann-Whitney U test. The correlations between the measured parameters were analysed with Spearman's rho correlation. Bonferroni post-hoc correction was used to compensate for the familywise error rate in multiple comparisons.

Results

Several MD values in the right hemisphere correlated positively and FA values negatively with the lesion volumes. These correlations included both lesion area and healthy tissue. The results of the mini-mental state examination and the National Institutes of Health Stroke Scale also correlated with the lesion volume.

Conclusions

A larger infarct volume is associated with more pronounced tissue modifications in the chronic stage as observed with the MD and FA alterations.

Conserved and variable architecture of human white matter connectivity

Whole-brain network analysis of diffusion imaging tractography data is an important new tool for quantification of differential connectivity patterns across individuals and between groups. Here we investigate both the conservation of network architectural properties across methodological variation and the reproducibility of individual architecture across multiple scanning sessions. Diffusion spectrum imaging (DSI) and diffusion tensor imaging (DTI) data were both acquired in triplicate from a cohort of healthy young adults. Deterministic tractography was performed on each dataset and inter-regional connectivity matrices were then derived by applying each of three widely used whole-brain parcellation schemes over a range of spatial resolutions. Across acquisitions and preprocessing streams, anatomical brain networks were found to be sparsely connected, hierarchical, and assortative. They also displayed signatures of topo-physical interdependence such as Rentian scaling. Basic connectivity properties and several graph metrics consistently displayed high reproducibility and low variability in both DSI and DTI networks. The relative increased sensitivity of DSI to complex fiber configurations was evident in increased tract counts and network density compared with DTI. In combination, this pattern of results shows that network analysis of human white matter connectivity provides sensitive and temporally stable topological and physical estimates of individual cortical structure across multiple spatial scales.

Generalized q-sampling imaging

Based on the Fourier transform relation between diffusion magnetic resonance (MR) signals and the underlying diffusion displacement, a new relation is derived to estimate the spin distribution function (SDF) directly from diffusion MR signals. This relation leads to an imaging method called generalized q-sampling imaging (GQI), which can obtain the SDF from the shell sampling scheme used in q-ball imaging (QBI) or the grid sampling scheme used in diffusion spectrum imaging (DSI). The accuracy of GQI was evaluated by a simulation study and an in vivo experiment in comparison with QBI and DSI. The simulation results showed that the accuracy of GQI was comparable to that of QBI and DSI. The simulation study of GQI also showed that an anisotropy index, named quantitative anisotropy, was correlated with the volume fraction of the resolved fiber component. The in vivo images of GQI demonstrated that SDF patterns were similar to the ODFs reconstructed by QBI or DSI. The tractography generated from GQI was also similar to those generated from QBI and DSI. In conclusion, the proposed GQI method can be applied to grid or shell sampling schemes and can provide directional and quantitative information about the crossing fibers.

Feasibility of prefronto-caudate pathway tractography using high resolution diffusion tensor tractography data at 3T

Mapping the human brain frontostriatal pathways using noninvasive diffusion tensor imaging (DTI) has been hampered by the inadequate imaging sensitivity, poor spatial resolution, lower tensor anisotropy within gray matter, increased partial volume averaging effects and poor signal-to-noise ratio. We investigated for the first time the utility of high spatial resolution DTI-based fiber-tractography using the fiber assignment by continuous tracking (FACT) to reconstruct and quantify bilaterally the prefronto-caudo-thalamic connections within the human brain at 3T. Five healthy right-handed men (age range 24-37 years) were studied. We traced the anterior thalamic radiation and prefronto-caudo-thalamic pathways bilaterally and measured the volume of each tract and the corresponding diffusion tensor metrics in all subjects. The anterior thalamic radiation tract volume and corresponding fractional anisotropy (FA) were significantly larger bilaterally than prefronto-caudate pathway, whereas the mean diffusivity (D(av)) values were similar (p>0.7). For both anterior thalamic radiation and prefronto-caudate pathway the tract volume and corresponding DTI metrics (FA, D(av)) were not significantly different between the two hemispheres (p>0.2). Our DTI acquisition protocol and analysis permitted the reconstruction of the connectivity of the caudate with the thalamus as well as with the prefrontal cortex and allowed tracking of the whole trajectory of the prefronto-caudo-thalamic pathway.

Integrative Understanding of Emergent Brain Properties, Quantum Brain Hypotheses, and Connectome Alterations in Dementia are Key Challenges to Conquer Alzheimer's Disease

The biological substrate for cognition remains a challenge as much as defining this function of living beings. Here, we examine some of the difficulties to understand normal and disordered cognition in humans. We use aspects of Alzheimer's disease and related disorders to illustrate how the wealth of information at many conceptually separate, even intellectually decoupled, physical scales - in particular at the Molecular Neuroscience versus Systems Neuroscience/Neuropsychology levels - presents a challenge in terms of true interdisciplinary integration towards a coherent understanding. These unresolved dilemmas include critically the as yet untested quantum brain hypothesis, and the embryonic attempts to develop and define the so-called connectome in humans and in non-human models of disease. To mitigate these challenges, we propose a scheme incorporating the vast array of scales of the space and time (space-time) manifold from at least the subatomic through cognitive-behavioral dimensions of inquiry, to achieve a new understanding of both normal and disordered cognition, that is essential for a new era of progress in the Generative Sciences and its application to translational efforts for disease prevention and treatment.