The atlas by Heinrich Sachs (1892) provided an accurate description of the intralobar fibres of the occipital lobe, with a detailed representation of the short associative tracts connecting different parts of the lobe. Little attention has been paid to the work of Sachs since its publication. In this study, we present the results of the dissection of three hemispheres, performed according to the Klingler technique (1935). Our anatomical findings are then compared to the original description of the occipital fibres anatomy as detailed by Sachs.Three hemispheres were dissected according to Klingler's technique (1935). Specimens were fixed in 10% formalin and frozen at -15 °C for two weeks. After defreezing, dissection of the white matter fibres was performed with blunt dissectors. Coronal sections were obtained according to the cuts originally described by Sachs. In addition, medial to lateral and lateral to medial dissection of the white matter of the occipital lobe was also performed.A network of short association fibres was demonstrated in the occipital lobe, comprising intralobar association fibres and U-shaped fibres, which are connecting neighbouring gyri. Lateral to the ventricles, longitudinal fibres of the stratum sagittale were also identified that are arranged as external and internal layers. Fibres of the forceps major were also found to be in direct contact with the ventricular walls. We were able to replicate all tracts originally described by Sachs. In addition, a previously unrecognised tract, connecting the cuneus to the lingual gyrus, was identified. This tract corresponds to the "sledge runner", described in tractography studies.The occipital lobe shows a rich network of intralobar fibres, arranged around the ventricular wall. Good concordance was observed between the Klingler dissection technique and the histological preparations of Sachs.Copyright © 2014 Elsevier Ltd. All rights reserved.

Diffusion magnetic resonance imaging is a technique for non-invasive detection of microstructure in the white matter of the human brain, which is widely used in neuroscience research of the brain. However, diffusion-weighted images(DWI) are sensitive to noise, which affects the subsequent reconstruction of fiber orientation direction, microstructural parameter estimation and fiber tracking. In order to better eliminate the noise in diffusion-weighted images, this study proposes a noise reduction method combining Marchenko-Pastur principal component analysis(MPPCA) and rotation-invariant non-local means filter(RINLM) to further remove residual noise and preserve the image texture detail information. In this study, the algorithm is applied to the fiber structure and the prevailing microstructural models within the human brain voxels based on simulated and real human brain datasets. Experimental comparisons between the proposed method and the state-of-the-art methods are performed in single-fiber, multi-fiber, crossed and curved-fiber regions as well as in different microstructure estimation models. Results demonstrated the superior performance of the proposed method in denoising DWI data, which can reduce the angular error in fiber orientation reconstruction to obtain more valid fiber structure estimation and enable more complete fiber tracking trajectories with higher coverage. Meanwhile, the method reduces the estimation errors of various white matter microstructural parameters and verifies the performance of the method in white matter microstructure estimation.© 2023. International Federation for Medical and Biological Engineering.

基于扩散磁共振成像的纤维追踪技术为非侵入性观测脑白质结构提供了有力的手段，约束球面反卷积作为一种多纤维追踪模型，能够对体素内纤维的方向信息进行建模，进而实现脑纤维的重构.针对约束球面反卷积模型的不适定性以及细节信息丢失问题，本文在约束球面反卷积的基础上，结合邻域信息和分数阶正则化，提出了一种基于非局部约束球面反卷积模型的确定型纤维追踪算法，分数阶的非局部特性使得纤维方向分布模型估计的误差更小，而邻域信息的引入保证了空间一致性，可以减少噪声的影响.分别利用模拟数据、人脑实际数据对本文算法及基于约束球面反卷积的确定型纤维追踪算法作对比实验，结果表明，利用本文算法追踪的纤维不仅整体视觉效果上较整洁，而且对交叉纤维的重建结果更完整准确.

Diffusion tensor imaging (DTI), high angular resolution diffusion imaging (HARDI), and diffusion spectrum imaging (DSI) have been widely used in the neuroimaging field to examine the macro-scale fiber connection patterns in the cerebral cortex. However, the topographic and geometric relationships between diffusion imaging derived streamline fiber connection patterns and cortical folding patterns remain largely unknown. This paper specifically identifies and characterizes the U-shapes of diffusion imaging derived streamline fibers via a novel fiber clustering framework and examines their co-localization patterns with cortical sulci based on DTI, HARDI, and DSI datasets of human, chimpanzee and macaque brains. We verified the presence of these U-shaped streamline fibers that connect neighboring gyri by coursing around cortical sulci such as the central sulcus, pre-central sulcus, post-central sulcus, superior temporal sulcus, inferior frontal sulcus, and intra-parietal sulcus. This study also verified the existence of U-shape fibers across data modalities (DTI/HARDI/DSI) and primate species (macaque, chimpanzee and human), and suggests that the common pattern of U-shape fibers coursing around sulci is evolutionarily-preserved in cortical architectures.Copyright © 2014 Elsevier B.V. All rights reserved.

The temporo-parieto-occipital (TPO) junction plays a unique role in human high-level neurological functions. Long-range fibers from and to this area have been described in detail but little is known about short TPO tracts mediating local connectivity. In this study, we performed high angular diffusion spectrum imaging (DSI) analyses to visualize the short TPO connections in the human brain. Fiber tracking was conducted on a subject-specific approach (10 subjects) and a template of 90 subjects (NTU-90 Atlas). Three tracts were identified: posterior segment of the superior longitudinal fasciculus (SLF-V), connecting the posterior part of the middle and inferior temporal gyri with the angular gyrus and supramarginal gyrus, vertical occipital fasciculus (VOF), connecting the inferior parietal with the lower temporal and occipital lobe, and a novel temporo-parietal (TP) connection, interconnecting the inferior temporal gyrus, middle temporal gyrus and fusiform gyrus, and inferior occipital lobe with the superior parietal lobe. These studies were complemented by fiber dissection techniques. It is the first study that demonstrated the trajectory and connectivity of the VOF using fiber dissection, as well as displayed the spatial relationship of the SLF-V with the cortex and the adjacent fiber bundles on one dissecting hemisphere. By providing a more accurate and detailed description of the local connectivity of the TPO junction, our findings help to develop new insights into its functional role in the human brain.Copyright © 2016 Elsevier B.V. All rights reserved.

The Human Connectome Project (HCP) relies primarily on three complementary magnetic resonance (MR) methods. These are: 1) resting state functional MR imaging (rfMRI) which uses correlations in the temporal fluctuations in an fMRI time series to deduce 'functional connectivity'; 2) diffusion imaging (dMRI), which provides the input for tractography algorithms used for the reconstruction of the complex axonal fiber architecture; and 3) task based fMRI (tfMRI), which is employed to identify functional parcellation in the human brain in order to assist analyses of data obtained with the first two methods. We describe technical improvements and optimization of these methods as well as instrumental choices that impact speed of acquisition of fMRI and dMRI images at 3T, leading to whole brain coverage with 2 mm isotropic resolution in 0.7 s for fMRI, and 1.25 mm isotropic resolution dMRI data for tractography analysis with three-fold reduction in total dMRI data acquisition time. Ongoing technical developments and optimization for acquisition of similar data at 7 T magnetic field are also presented, targeting higher spatial resolution, enhanced specificity of functional imaging signals, mitigation of the inhomogeneous radio frequency (RF) fields, and reduced power deposition. Results demonstrate that overall, these approaches represent a significant advance in MR imaging of the human brain to investigate brain function and structure.Copyright © 2013 Elsevier Inc. All rights reserved.

扩散磁共振成像是目前唯一非侵入性研究脑神经纤维束微结构的技术,神经纤维追踪技术是显示神经纤维的关键步骤.本文综述了两大类的神经纤维追踪算法的研究进展,即：局部型追踪方法和全局型追踪方法,阐明各个追踪算法的优点以及存在的局限性,然后在此基础上介绍了在神经纤维追踪过程中能做出优化的具体方面,包括局部纤维方向建模、张量插值、种子点的选取、传播方向以及终止准则等,最后对神经纤维追踪算法的未来发展趋势进行展望.

Diffusion tensor fiber tracking potentially can give information about in vivo brain connectivity. However, this technique is difficult to validate due to the lack of a gold standard. Fiber tracking reliability will depend on the quality of the data and on the robustness of the algorithms used. Information about the effects of various anatomical and image acquisition parameters on fiber tracking reliability may be used in the design of imaging sequences and of tracking algorithms. In this study, tracking was performed on two different simulated models to study the effects on tracking quality of SNR, anisotropy, curvature, fiber cross-section, background anisotropy, step size, and interpolation. Tracking was also performed on volunteer data to assess the relevance of the simulations to real data. Our results show that, in general, tracking with high SNR and high anisotropy using interpolation and a low step size gives the most reliable results. Partial volume effects are shown to have a detrimental effect when the background is anisotropic and when tracking narrow fibers. The results derived from real data show similar trends and thus support the findings of the simulations. These simulations may therefore help to determine which structures can be tracked for a given image quality.Copyright 2002 Wiley-Liss, Inc.

Diffusion MRI fiber tractography has been increasingly used to map the structural connectivity of the human brain. However, this technique is not without limitations; for example, there is a growing concern over anatomically correlated bias in tractography findings. In this study, we demonstrate that there is a bias for fiber tracking algorithms to terminate preferentially on gyral crowns, rather than the banks of sulci. We investigate this issue by comparing diffusion MRI (dMRI) tractography with equivalent measures made on myelin-stained histological sections. We begin by investigating the orientation and trajectories of axons near the white matter/gray matter boundary, and the density of axons entering the cortex at different locations along gyral blades. These results are compared with dMRI orientations and tract densities at the same locations, where we find a significant gyral bias in many gyral blades across the brain. This effect is shown for a range of tracking algorithms, both deterministic and probabilistic, and multiple diffusion models, including the diffusion tensor and a high angular resolution diffusion imaging technique. Additionally, the gyral bias occurs for a range of diffusion weightings, and even for very high-resolution datasets. The bias could significantly affect connectivity results using the current generation of tracking algorithms.© 2017 Wiley Periodicals, Inc.

Determining the acquisition parameters in diffusion magnetic resonance imaging (dMRI) is governed by a series of trade-offs. Images of lower resolution have less spatial specificity but higher signal to noise ratio (SNR). At the same time higher angular contrast, important for resolving complex fibre patterns, also yields lower SNR. Considering these trade-offs, the Human Connectome Project (HCP) acquires high quality dMRI data for the same subjects at different field strengths (3T and 7T), which are publically released. Due to differences in the signal behavior and in the underlying scanner hardware, the HCP 3T and 7T data have complementary features in k- and q-space. The 3T dMRI has higher angular contrast and resolution, while the 7T dMRI has higher spatial resolution. Given the availability of these datasets, we explore the idea of fusing them together with the aim of combining their benefits. We extend a previously proposed data-fusion framework and apply it to integrate both datasets from the same subject into a single joint analysis. We use a generative model for performing parametric spherical deconvolution and estimate fibre orientations by simultaneously using data acquired under different protocols. We illustrate unique features from each dataset and how they are retained after fusion. We further show that this allows us to complement benefits and improve brain connectivity analysis compared to analyzing each of the datasets individually.Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Recent emergence of human connectome imaging has led to a high demand on angular and spatial resolutions for diffusion magnetic resonance imaging (MRI). While there have been significant growths in high angular resolution diffusion imaging, the improvement in spatial resolution is still limited due to a number of technical challenges, such as the low signal-to-noise ratio and high motion artifacts. As a result, the benefit of a high spatial resolution in the whole-brain connectome imaging has not been fully evaluated in vivo. In this brief report, the impact of spatial resolution was assessed in a newly acquired whole-brain three-dimensional diffusion tensor imaging data set with an isotropic spatial resolution of 0.85 mm. It was found that the delineation of short cortical association fibers is drastically improved as well as the definition of fiber pathway endings into the gray/white matter boundary-both of which will help construct a more accurate structural map of the human brain connectome.

In this work, we exploit the T1 weighted image in conjunction with cortical surface boundary to improve the precision of tractography under the cortex. We show that utilizing the cortical interface and a surface flow, to model the superficial white matter streamlines, enhance and improve tractography trajectory near the cortex. Our novel surface-enhanced tractography reduces the gyral bias, the length bias and the amount of false positive streamlines produced by tractography. This method improves the reproducibility and the cortical surface coverage of tractograms which are crucial for connectomics studies. The usage of cortical surfaces, extracted from the standardly acquired 1 mm isotropic T1, is a straightforward and effective way to improve existing tractography processing pipelines and structural connectivity studies.Copyright © 2017 Elsevier Inc. All rights reserved.

Diffusion MRI allows us to make inferences on the structural organisation of the brain by mapping water diffusion to white matter microstructure. However, such a mapping is generally ill-defined; for instance, diffusion measurements are antipodally symmetric (diffusion along x and -x are equal), whereas the distribution of fibre orientations within a voxel is generally not symmetric. Therefore, different sub-voxel patterns such as crossing, fanning, or sharp bending, cannot be distinguished by fitting a voxel-wise model to the signal. However, asymmetric fibre patterns can potentially be distinguished once spatial information from neighbouring voxels is taken into account. We propose a neighbourhood-constrained spherical deconvolution approach that is capable of inferring asymmetric fibre orientation distributions (A-fods). Importantly, we further design and implement a tractography algorithm that utilises the estimated A-fods, since the commonly used streamline tractography paradigm cannot directly take advantage of the new information. We assess performance using ultra-high resolution histology data where we can compare true orientation distributions against sub-voxel fibre patterns estimated from down-sampled data. Finally, we explore the benefits of A-fods-based tractography using in vivo data by evaluating agreement of tractography predictions with connectivity estimates made using different in-vivo modalities. The proposed approach can reliably estimate complex fibre patterns such as sharp bending and fanning, which voxel-wise approaches cannot estimate. Moreover, histology-based and in-vivo results show that the new framework allows more accurate tractography and reconstruction of maps quantifying (symmetric and asymmetric) fibre complexity.Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called "virtual dissection." Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. It is our opinion that if the field of dMRI tractography wants to be taken seriously as a widespread clinical tool, it is imperative to harmonize WM bundle segmentations and develop protocols aimed to be used in clinical settings. The EADC-ADNI Harmonized Hippocampal Protocol achieved such standardization through a series of steps that must be reproduced for every WM bundle. This article is an observation of the problematic. A specific bundle segmentation protocol was used in order to provide a real-life example, but the contribution of this article is to discuss the need for reproducibility and standardized protocol, as for any measurement tool. This study required the participation of 11 experts and 13 nonexperts in neuroanatomy and "virtual dissection" across various laboratories and hospitals. Intra-rater agreement (Dice score) was approximately 0.77, while inter-rater was approximately 0.65. The protocol provided to participants was not necessarily optimal, but its design mimics, in essence, what will be required in future protocols. Reporting tractometry results such as average fractional anisotropy, volume or streamline count of a particular bundle without a sufficient reproducibility score could make the analysis and interpretations more difficult. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction protocols in this era of open and collaborative science.© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.

Two- and three-dimensional (3D) white matter atlases were created on the basis of high-spatial-resolution diffusion tensor magnetic resonance (MR) imaging and 3D tract reconstruction. The 3D trajectories of 17 prominent white matter tracts could be reconstructed and depicted. Tracts were superimposed on coregistered anatomic MR images to parcel the white matter. These parcellation maps were then compared with coregistered diffusion tensor imaging color maps to assign visible structures. The results showed (a). which anatomic structures can be identified on diffusion tensor images and (b). where these anatomic units are located at each section level and orientation. The atlas may prove useful for educational and clinical purposes.Copyright RSNA, 2004

Advances in our understanding of sensory-motor integration suggest a unique role of the frontal lobe circuits in cognition and behaviour. Long-range afferent connections convey higher order sensory information to the frontal cortex, which in turn responds to internal and external stimuli with flexible and adaptive behaviour. Long-range connections from and to frontal lobes have been described in detail in monkeys but little is known about short intralobar frontal connections mediating local connectivity in humans. Here we used spherical deconvolution diffusion tractography and post-mortem dissections to visualize the short frontal lobe connections of the human brain. We identified three intralobar tracts connecting: i) posterior Broca's region with supplementary motor area (SMA) and pre-supplementary motor area (pre-SMA) (i.e., the frontal 'aslant' tract - FAT); ii) posterior orbitofrontal cortex with anterior polar region (i.e., fronto-orbitopolar tract - FOP); iii) posterior pre-central cortex with anterior prefrontal cortex (i.e., the frontal superior longitudinal - FSL faciculus system). In addition more complex systems of short U-shaped fibres were identified in the regions of the central, pre-central, perinsular and fronto-marginal sulcus (FMS). The connections between Broca and medial frontal areas (i.e. FAT) and those between the hand-knob motor region and post-central gyrus (PoCG) were found left lateralized in a group of twelve healthy right-handed subjects. The existence of these short frontal connections was confirmed using post-mortem blunt dissections. The functional role of these tracts in motor learning, verbal fluency, prospective behaviour, episodic and working memory is discussed. Our study provides a general model for the local connectivity of the frontal lobes that could be used as an anatomical framework for studies on lateralization and future clinical research in neurological and psychiatric disorders.Copyright © 2011 Elsevier Srl. All rights reserved.

In neuroscience, there is a growing consensus that higher cognitive functions may be supported by distributed networks involving different cerebral regions, rather than by single brain areas. Communication within these networks is mediated by white matter tracts and is particularly prominent in the frontal lobes for the control and integration of information. However, the detailed mapping of frontal connections remains incomplete, albeit crucial to an increased understanding of these cognitive functions. Based on 47 high-resolution diffusion-weighted imaging datasets (age range 22-71 years), we built a statistical normative atlas of the frontal lobe connections in stereotaxic space, using state-of-the-art spherical deconvolution tractography. We dissected 55 tracts including U-shaped fibers. We further characterized these tracts by measuring their correlation with age and education level. We reported age-related differences in the microstructural organization of several, specific frontal fiber tracts, but found no correlation with education level. Future voxel-based analyses, such as voxel-based morphometry or tract-based spatial statistics studies, may benefit from our atlas by identifying the tracts and networks involved in frontal functions. Our atlas will also build the capacity of clinicians to further understand the mechanisms involved in brain recovery and plasticity, as well as assist clinicians in the diagnosis of disconnection or abnormality within specific tracts of individual patients with various brain diseases.

The parietal lobe has a unique place in the human brain. Anatomically, it is at the crossroad between the frontal, occipital, and temporal lobes, thus providing a middle ground for multimodal sensory integration. Functionally, it supports higher cognitive functions that are characteristic of the human species, such as mathematical cognition, semantic and pragmatic aspects of language, and abstract thinking. Despite its importance, a comprehensive comparison of human and simian intraparietal networks is missing. In this study, we used diffusion imaging tractography to reconstruct the major intralobar parietal tracts in twenty-one datasets acquired in vivo from healthy human subjects and eleven ex vivo datasets from five vervet and six macaque monkeys. Three regions of interest (postcentral gyrus, superior parietal lobule and inferior parietal lobule) were used to identify the tracts. Surface projections were reconstructed for both species and results compared to identify similarities or differences in tract anatomy (i.e., trajectories and cortical projections). In addition, post-mortem dissections were performed in a human brain. The largest tract identified in both human and monkey brains is a vertical pathway between the superior and inferior parietal lobules. This tract can be divided into an anterior (supramarginal gyrus) and a posterior (angular gyrus) component in both humans and monkey brains. The second prominent intraparietal tract connects the postcentral gyrus to both supramarginal and angular gyri of the inferior parietal lobule in humans but only to the supramarginal gyrus in the monkey brain. The third tract connects the postcentral gyrus to the anterior region of the superior parietal lobule and is more prominent in monkeys compared to humans. Finally, short U-shaped fibres in the medial and lateral aspects of the parietal lobe were identified in both species. A tract connecting the medial parietal cortex to the lateral inferior parietal cortex was observed in the monkey brain only. Our findings suggest a consistent pattern of intralobar parietal connections between humans and monkeys with some differences for those areas that have cytoarchitectonically distinct features in humans. The overall pattern of intraparietal connectivity supports the special role of the inferior parietal lobule in cognitive functions characteristic of humans.Copyright © 2017. Published by Elsevier Ltd.

Structural analysis of the superficial white matter is prerequisite for the understanding of highly integrated functions of the human cerebral cortex. However, the principal components, U-fibers, have been regarded as simple wires to connect adjacent gyri (inter-gyral U-fibers) but have never been thought as indispensable elements of anatomical structures to construct the cortical network. Here, we reported such novel structures made of U-fibers. Seven human cerebral hemispheres were treated with Klingler's method and subjected to fiber dissection (FD). Additionally, tractography using diffusion spectrum imaging (DSI) was performed. Our FD and DSI tractography succeeded disclosing a new type of U-fibers that was hidden in and ran along the white matter ridge of a gyral convolution (intra-gyral U-fibers). They were distinct from inter-gyral U-fibers which paved sulcal floors. Both intra- and inter-gyral U-fibers converged from various directions into junctional areas of white matter ridges, organizing novel anatomical structures, "pyramid-shape crossings". U-fibers to form pyramid-shape crossings also render routes for communication between crossings. There were 97 (mean, range 73-148) pyramid-shape crossings per lateral cortical surface. They are key structures to construct the neural network for intricate communications throughout the entire cerebrum. They can be new anatomical landmarks, too, for the segmentation of the cerebral cortex.© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

Structural delineation and assignment are the fundamental steps in understanding the anatomy of the human brain. The white matter has been structurally defined in the past only at its core regions (deep white matter). However, the most peripheral white matter areas, which are interleaved between the cortex and the deep white matter, have lacked clear anatomical definitions and parcellations. We used axonal fiber alignment information from diffusion tensor imaging (DTI) to delineate the peripheral white matter, and investigated its relationship with the cortex and the deep white matter. Using DTI data from 81 healthy subjects, we identified nine common, blade-like anatomical regions, which were further parcellated into 21 subregions based on the cortical anatomy. Four short association fiber tracts connecting adjacent gyri (U-fibers) were also identified reproducibly among the healthy population. We anticipate that this atlas will be useful resource for atlas-based white matter anatomical studies.

Tractography based on diffusion tensor imaging (DTI) is widely used to quantitatively analyze the status of the white matter anatomy in a tract-specific manner in many types of diseases. This approach, however, involves subjective judgment in the tract-editing process to extract only the tracts of interest. This process, usually performed by manual delineation of regions of interest, is also time-consuming, and certain tracts, especially the short cortico-cortical association fibers, are difficult to reconstruct. In this paper, we propose an automated approach for reconstruction of a large number of white matter tracts. In this approach, existing anatomical knowledge about tract trajectories (called the Template ROI Set or TRS) were stored in our DTI-based brain atlas with 130 three-dimensional anatomical segmentations, which were warped non-linearly to individual DTI data. We examined the degree of matching with manual results for selected fibers. We established 30 TRSs to reconstruct 30 prominent and previously well-described fibers. In addition, TRSs were developed to delineate 29 short association fibers that were found in all normal subjects examined in this paper (N=20). Probabilistic maps of the 59 tract trajectories were created from the normal subjects and were incorporated into our image analysis tool for automated tract-specific quantification.Copyright 2010 Elsevier Inc. All rights reserved.

The supplementary motor area (SMA) is frequently involved by brain tumours (particularly WHO grade II gliomas). Surgery in this area can be followed by the 'SMA syndrome', characterised by contralateral akinesia and mutism. Knowledge of the connections of the SMA can provide new insights on the genesis of the SMA syndrome, and a better understanding of the challenges related to operating in this region.White matter connections of the SMA were studied with both postmortem dissection and advance diffusion imaging tractography. Postmortem dissections were performed according to the Klingler technique. 12 specimens were fixed in 10% formalin and frozen at -15°C for 2 weeks. After thawing, dissection was performed with blunt dissectors. For diffusion tractography, high-resolution diffusion imaging datasets from 10 adult healthy controls from the Human Connectome Project database were used. Whole brain tractography was performed using a spherical deconvolution approach.Five main connections were identified in both postmortem dissections and tractography reconstructions: (1) U-fibres running in the precentral sulcus, connecting the precentral gyrus and the SMA; (2) U-fibres running in the cingulate sulcus, connecting the SMA with the cingulate gyrus; (3) frontal 'aslant' fascicle, directly connecting the SMA with the pars opercularis of the inferior frontal gyrus; (4) medial fibres connecting the SMA with the striatum; and (5) SMA callosal fibres. Good concordance was observed between postmortem dissections and diffusion tractography.The SMA shows a wide range of white matter connections with motor, language and lymbic areas. Features of the SMA syndrome (akinesia and mutism) can be better understood on the basis of these findings.Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Diffusion tensor imaging and tractography allow studying white matter fiber bundles in the human brain in vivo. Electrophysiological studies and postmortem dissections permit improving our knowledge about the short association fibers connecting the pre- and postcentral gyri. The aim of this study was first to extract and analyze the features of these short fiber bundles and secondly to analyze their asymmetry according to the subjects' handedness.Ten right-handed and ten left-handed healthy subjects were included. White matter fiber bundles were extracted using a streamline tractography approach, with two seed regions of interest (ROI) taken from a parcellation of the pre- and postcentral gyri. This parcellation was achieved using T1 magnetic resonance images (MRI) and semi-automatically generated three ROIs within each gyrus. MRI tracks were reconstructed between all pairs of ROIs connecting the adjacent pre- and postcentral gyri. A quantitative analysis was performed on the number of tracks connecting each ROI pair. A statistical analysis studied the repartition of these MRI tracks in the right and left hemispheres and as a function of the subjects' handedness.The quantitative analysis showed an increased density of MRI tracks in the middle part of the central area in each hemisphere of the 20 subjects. The statistical analysis showed significantly more MRI tracks for the left hemisphere, when we consider the whole population, and this difference was presumably driven by the left-handers.These results raise questions about the functional role of these MRI tracks and their relation with laterality.

This paper presents a method for automatic segmentation of white matter fiber bundles from massive dMRI tractography datasets. The method is based on a multi-subject bundle atlas derived from a two-level intra-subject and inter-subject clustering strategy. This atlas is a model of the brain white matter organization, computed for a group of subjects, made up of a set of generic fiber bundles that can be detected in most of the population. Each atlas bundle corresponds to several inter-subject clusters manually labeled to account for subdivisions of the underlying pathways often presenting large variability across subjects. An atlas bundle is represented by the multi-subject list of the centroids of all intra-subject clusters in order to get a good sampling of the shape and localization variability. The atlas, composed of 36 known deep white matter bundles and 47 superficial white matter bundles in each hemisphere, was inferred from a first database of 12 brains. It was successfully used to segment the deep white matter bundles in a second database of 20 brains and most of the superficial white matter bundles in 10 subjects of the same database.Copyright © 2012 Elsevier Inc. All rights reserved.

Human brain connectivity is extremely complex and variable across subjects. While long association and projection bundles are stable and have been deeply studied, short association bundles present higher intersubject variability, and few studies have been carried out to adequately describe the structure, shape, and reproducibility of these bundles. However, their analysis is crucial to understand brain function and better characterize the human connectome. In this study, we propose an automatic method to identify reproducible short association bundles of the superficial white matter, based on intersubject hierarchical clustering. The method is applied to the whole brain and finds representative clusters of similar fibers belonging to a group of subjects, according to a distance metric between fibers. We experimented with both affine and non-linear registrations and, due to better reproducibility, chose the results obtained from non-linear registration. Once the clusters are calculated, our method performs automatic labeling of the most stable connections based on individual cortical parcellations. We compare results between two independent groups of subjects from a HARDI database to generate reproducible connections for the creation of an atlas. To perform a better validation of the results, we used a bagging strategy that uses pairs of groups of 27 subjects from a database of 74 subjects. The result is an atlas with 44 bundles in the left hemisphere and 49 in the right hemisphere, of which 33 bundles are found in both hemispheres. Finally, we use the atlas to automatically segment 78 new subjects from a different HARDI database and to analyze stability and lateralization results.

In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.

This work presents an anatomically curated white matter atlas to enable consistent white matter tract parcellation across different populations. Leveraging a well-established computational pipeline for fiber clustering, we create a tract-based white matter atlas including information from 100 subjects. A novel anatomical annotation method is proposed that leverages population-based brain anatomical information and expert neuroanatomical knowledge to annotate and categorize the fiber clusters. A total of 256 white matter structures are annotated in the proposed atlas, which provides one of the most comprehensive tract-based white matter atlases covering the entire brain to date. These structures are composed of 58 deep white matter tracts including major long range association and projection tracts, commissural tracts, and tracts related to the brainstem and cerebellar connections, plus 198 short and medium range superficial fiber clusters organized into 16 categories according to the brain lobes they connect. Potential false positive connections are annotated in the atlas to enable their exclusion from analysis or visualization. In addition, the proposed atlas allows for a whole brain white matter parcellation into 800 fiber clusters to enable whole brain connectivity analyses. The atlas and related computational tools are open-source and publicly available. We evaluate the proposed atlas using a testing dataset of 584 diffusion MRI scans from multiple independently acquired populations, across genders, the lifespan (1 day-82 years), and different health conditions (healthy control, neuropsychiatric disorders, and brain tumor patients). Experimental results show successful white matter parcellation across subjects from different populations acquired on multiple scanners, irrespective of age, gender or disease indications. Over 99% of the fiber tracts annotated in the atlas were detected in all subjects on average. One advantage in terms of robustness is that the tract-based pipeline does not require any cortical or subcortical segmentations, which can have limited success in young children and patients with brain tumors or other structural lesions. We believe this is the first demonstration of consistent automated white matter tract parcellation across the full lifespan from birth to advanced age.Copyright © 2018 Elsevier Inc. All rights reserved.

The central sulcus is probably one of the most studied folds in the human brain, owing to its clear relationship with primary sensory-motor functional areas. However, due to the difficulty of estimating the trajectories of the U-shape fibres from diffusion MRI, the short structural connectivity of this sulcus remains relatively unknown. In this context, we studied the spatial organization of these U-shape fibres along the central sulcus. Based on high quality diffusion MRI data of 100 right-handed subjects and state-of-the-art pre-processing pipeline, we first define a connectivity space that provides a comprehensive and continuous description of the short-range anatomical connectivity around the central sulcus at both the individual and group levels. We then infer the presence of five major U-shape fibre bundles at the group level in both hemispheres by applying unsupervised clustering in the connectivity space. We propose a quantitative investigation of their position and number of streamlines as a function of hemisphere, sex and functional scores such as handedness and manual dexterity. Main findings of this study are twofold: a description of U-shape short-range connectivity along the central sulcus at group level and the evidence of a significant relationship between the position of three hand related U-shape fibre bundles and the handedness score of subjects.

Human brain connection map is far from being complete. In particular the study of the superficial white matter (SWM) is an unachieved task. Its description is essential for the understanding of human brain function and the study of pathogenesis triggered by abnormal connectivity. In this work we automatically created a multi-subject atlas of SWM diffusion-based bundles of the whole brain. For each subject, the complete cortico-cortical tractogram is first split into sub-tractograms connecting pairs of gyri. Then intra-subject shape-based fiber clustering performs compression of each sub-tractogram into a set of bundles. Proceeding further with shape-based clustering provides a match of the bundles across subjects. Bundles found in most of the subjects are instantiated in the atlas. To increase robustness, this procedure was performed with two independent groups of subjects, in order to discard bundles without match across the two independent atlases. Finally, the resulting intersection atlas was projected on a third independent group of subjects in order to filter out bundles without reproducible and reliable projection. The final multi-subject diffusion-based U-fiber atlas is composed of 100 bundles in total, 50 per hemisphere, from which 35 are common to both hemispheres.Copyright © 2017 Elsevier Inc. All rights reserved.

扩散张量脑模板包含丰富的大脑白质组织信息，在空间标准化或者脑图谱创建中具有重要价值，然而基于扩散张量模型构建的脑模板精度不高，特别是在脑部复杂的神经元微观结构区域中应用受到限制.针对这一问题，研究者们提出了基于高分辨率扩散成像构建大脑模板的方法.本文对使用扩散张量成像方法进行脑模板构建的研究进展进行了综述，首先介绍了扩散张量脑模板构建的发展进程，阐述了脑模板构建中解决的技术问题及同时存在的局限性；接着详细论述了基于扩散频谱成像及高角度分辨率扩散成像构建脑模板的不同方法间的差异，并总结了这些研究方法取得的重要进展；最后通过分析目前研究进展提出该研究问题中存在的不足以及未来的发展趋势.