The fiber laterality histogram: a new way to measure white matter asymmetry

Tract Dictionary Learning for Fast and Robust Recognition of Fiber Bundles

In this paper, we propose an efficient framework for parcellation of white matter tractograms using discriminative dictionary learning. Key to our framework is the learning of a compact dictionary for each fiber bundle so that the streamlines within the bundle can be sufficiently represented. Dictionaries for multiple bundles are combined for whole-brain tractogram representation. These dictionaries are learned jointly to encourage inter-bundle incoherence for discriminative power. The proposed method allows tractograms to be assigned to more than one bundle, catering to scenarios where tractograms cannot be clearly separated. Experiments on a bundle-labeled HCP dataset and an infant dataset highlight the ability of our framework in grouping streamlines into anatomically plausible bundles.

XTRACT - Standardised protocols for automated tractography in the human and macaque brain

We present a new software package with a library of standardised tractography protocols devised for the robust automated extraction of white matter tracts both in the human and the macaque brain. Using in vivo data from the Human Connectome Project (HCP) and the UK Biobank and ex vivo data for the macaque brain datasets, we obtain white matter atlases, as well as atlases for tract endpoints on the white-grey matter boundary, for both species. We illustrate that our protocols are robust against data quality, generalisable across two species and reflect the known anatomy. We further demonstrate that they capture inter-subject variability by preserving tract lateralisation in humans and tract similarities stemming from twinship in the HCP cohort. Our results demonstrate that the presented toolbox will be useful for generating imaging-derived features in large cohorts, and in facilitating comparative neuroanatomy studies. The software, tractography protocols, and atlases are publicly released through FSL, allowing users to define their own tractography protocols in a standardised manner, further contributing to open science.

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A new software package for standardised and automated cross-species tractography.

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Homologous white matter bundles in the human and macaque brain.

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Human white matter tract atlases generated from large datasets (1000 subjects).

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Tractography protocols are standardised, but preserve individual variability.

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Generalisability across datasets shown using the HCP and the UK Biobank data.

Registration-free analysis of diffusion MRI tractography data across subjects through the human lifespan

Diffusion MRI tractography produces massive sets of streamlines that need to be clustered into anatomically meaningful white-matter bundles. Conventional clustering techniques group streamlines based on their proximity in Euclidean space. We have developed AnatomiCuts, an unsupervised method for clustering tractography streamlines based on their neighboring anatomical structures, rather than their coordinates in Euclidean space. In this work, we show that the anatomical similarity metric used in AnatomiCuts can be extended to find corresponding clusters across subjects and across hemispheres, without inter-subject or inter-hemispheric registration. Our proposed approach enables group-wise tract cluster analysis, as well as studies of hemispheric asymmetry. We evaluate our approach on data from the pilot MGH-Harvard-USC Lifespan Human Connectome project, showing improved correspondence in tract clusters across 184 subjects aged 8-90. Our method shows up to 38% improvement in the overlap of corresponding clusters when comparing subjects with large age differences. The techniques presented here do not require registration to a template and can thus be applied to populations with large inter-subject variability, e.g., due to brain development, aging, or neurological disorders.

Investigation into local white matter abnormality in emotional processing and sensorimotor areas using an automatically annotated fiber clustering in major depressive disorder

This work presents an automatically annotated fiber cluster (AAFC) method to enable identification of anatomically meaningful white matter structures from the whole brain tractography. The proposed method consists of 1) a study-specific whole brain white matter parcellation using a well-established data-driven groupwise fiber clustering pipeline to segment tractography into multiple fiber clusters, and 2) a novel cluster annotation method to automatically assign an anatomical tract annotation to each fiber cluster by employing cortical parcellation information across multiple subjects. The novelty of the AAFC method is that it leverages group-wise information about the fiber clusters, including their fiber geometry and cortical terminations, to compute a tract anatomical label for each cluster in an automated fashion. We demonstrate the proposed AAFC method in an application of investigating white matter abnormality in emotional processing and sensorimotor areas in major depressive disorder (MDD). Seven tracts of interest related to emotional processing and sensorimotor functions are automatically identified using the proposed AAFC method as well as a comparable method that uses a cortical parcellation alone. Experimental results indicate that our proposed method is more consistent in identifying the tracts across subjects and across hemispheres in terms of the number of fibers. In addition, we perform a between-group statistical analysis in 31 MDD patients and 62 healthy subjects on the identified tracts using our AAFC method. We find statistical differences in diffusion measures in local regions within a fiber tract (e.g. 4 fiber clusters within the identified left hemisphere cingulum bundle (consisting of 14 clusters) are significantly different between the two groups), suggesting the ability of our method in identifying potential abnormality specific to subdivisions of a white matter structure.

Diurnal microstructural variations in healthy adult brain revealed by diffusion tensor imaging

Biorhythm is a fundamental property of human physiology. Changes in the extracellular space induced by cell swelling in response to the neural activity enable the in vivo characterization of cerebral microstructure by measuring the water diffusivity using diffusion tensor imaging (DTI). To study the diurnal microstructural alterations of human brain, fifteen right-handed healthy adult subjects were recruited for DTI studies in two repeated sessions (8∶30 AM and 8∶30 PM) within a 24-hour interval. Fractional anisotropy (FA), apparent diffusion coefficient (ADC), axial (λ_//) and radial diffusivity (λ_⊥) were compared pixel by pixel between the sessions for each subject. Significant increased morning measurements in FA, ADC, λ_// and λ_⊥ were seen in a wide range of brain areas involving frontal, parietal, temporal and occipital lobes. Prominent evening dominant λ_⊥ (18.58%) was detected in the right inferior temporal and ventral fusiform gyri. AM-PM variation of λ_⊥ was substantially left side hemisphere dominant (p<0.05), while no hemispheric preference was observed for the same analysis for ADC (p = 0.77), λ_// (p = 0.08) or FA (p = 0.25). The percentage change of ADC, λ_//, λ_⊥, and FA were 1.59%, 2.15%, 1.20% and 2.84%, respectively, for brain areas without diurnal diffusivity contrast. Microstructural variations may function as the substrates of the phasic neural activities in correspondence to the environment adaptation in a light-dark cycle. This research provided a baseline for researches in neuroscience, sleep medicine, psychological and psychiatric disorders, and necessitates that diurnal effect should be taken into account in following up studies using diffusion tensor quantities.

Inferior frontal white matter asymmetry correlates with executive control of attention

White matter (WM) asymmetries of the human brain have been well documented using diffusion tensor imaging (DTI). However, the relationship between WM asymmetry pattern and cognitive performance is poorly understood. By means of tract-based spatial statistics (TBSS) and voxel-based analyses of whole brain, this study examined the WM asymmetries and the correlations between WM integrity/asymmetries and three distinct components of attention, namely alerting, orienting, and executive control (EC), which were assessed by attention network test (ANT). We revealed a number of WM anisotropy asymmetries, including leftward asymmetry of cingulum, corticospinal tract and cerebral peduncle, rightward asymmetry of internal capsule, superior longitudinal fasciculus and posterior corona radiata, as well as heterogeneous asymmetries in anterior corpus callosum and anterior corona radiata (ACR). Moreover, specific correlation was found between asymmetric pattern of inferior frontal ACR and EC performance. Additionally, this study also proposed that there were no significant relationships of WM anisotropy asymmetries to alerting and orienting functions. Further clusters of interest analyses and probabilistic fiber tracking validated our findings. In conclusion, there are a number of differences in WM integrity between human brain hemispheres. Specially, the anisotropy asymmetry in inferior frontal ACR plays a crucial role in EC function. Our finding is supportive of the functional studies of inferior frontal regions and in keeping with the theory of the brain lateralization on human ventral attention system.

Special surgical considerations for functional brain mapping

The development of functional mapping techniques gives neurosurgeons many options for preoperative planning. Integrating functional and anatomic data can inform patient selection and surgical planning and makes functional mapping more accessible than when only invasive studies were available. However, the applications of functional mapping to neurosurgical patients are still evolving. Functional imaging remains complex and requires an understanding of the underlying physiologic and imaging characteristics. Neurosurgeons must be accustomed to interpreting highly processed data. Successful implementation of functional image-guided procedures requires efficient interactions between neurosurgeon, neurologist, radiologist, neuropsychologist, and others, but promises to enhance the care of patients.