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.
We have developed a novel method to describe human white matter anatomy using an approach that is both intuitive and simple to use, and which automatically extracts white matter tracts from diffusion ...MRI volumes. Further, our method simplifies the quantification and statistical analysis of white matter tracts on large diffusion MRI databases. This work reflects the careful syntactical definition of major white matter fiber tracts in the human brain based on a neuroanatomist’s expert knowledge. The framework is based on a novel query language with a near-to-English textual syntax. This query language makes it possible to construct a dictionary of anatomical definitions that describe white matter tracts. The definitions include adjacent gray and white matter regions, and rules for spatial relations. This novel method makes it possible to automatically label white matter anatomy across subjects. After describing this method, we provide an example of its implementation where we encode anatomical knowledge in human white matter for ten association and 15 projection tracts per hemisphere, along with seven commissural tracts. Importantly, this novel method is comparable in accuracy to manual labeling. Finally, we present results applying this method to create a white matter atlas from 77 healthy subjects, and we use this atlas in a small proof-of-concept study to detect changes in association tracts that characterize schizophrenia.
Understanding sex differences in stress regulation has important implications for understanding basic physiological differences in the male and female brain and their impact on vulnerability to sex ...differences in chronic medical disorders associated with stress response circuitry. In this functional magnetic resonance imaging study, we demonstrated that significant sex differences in brain activity in stress response circuitry were dependent on women's menstrual cycle phase. Twelve healthy Caucasian premenopausal women were compared to a group of healthy men from the same population, based on age, ethnicity, education, and right handedness. Subjects were scanned using negative valence/high arousal versus neutral visual stimuli that we demonstrated activated stress response circuitry amygdala, hypothalamus, hippocampus, brainstem, orbitofrontal cortex (OFC), medial prefrontal cortex (mPFC), and anterior cingulate gyrus (ACG). Women were scanned twice based on normal variation in menstrual cycle hormones i.e., early follicular (EF) compared with late follicular-midcycle (LF/MC) menstrual phases. Using SPM8b, there were few significant differences in blood oxygenation level-dependent (BOLD) signal changes in men compared to EF women, except ventromedial nucleus (VMN), lateral hypothalamic area (LHA), left amygdala, and ACG. In contrast, men exhibited significantly greater BOLD signal changes compared to LF/MC women on bilateral ACG and OFC, mPFC, LHA, VMN, hippocampus, and periaqueductal gray, with largest effect sizes in mPFC and OFC. Findings suggest that sex differences in stress response circuitry are hormonally regulated via the impact of subcortical brain activity on the cortical control of arousal, and demonstrate that females have been endowed with a natural hormonal capacity to regulate the stress response that differs from males.
Gambling Disorder (GD) is a condition constituting a public health concern, with a burden of harm which is much greater than that of drug addiction. Patients with GD are generally reluctant to ...pharmacologic treatment and seem to prefer nonpharmacological interventions. Therefore, this proof-of-concept study aimed to investigate the feasibility of continuous Theta Burst Stimulation (cTBS) on the pre-SMA in six patients (5 males, 1 female), aged 30–64 years, with a DSM-5 diagnosis of Gambling Disorder and no comorbid mood disorders. Participants received over 10 sessions of Continuous TBS (cTBS) over pre-SMA bilaterally and have been evaluated using rating scales, including the PG-YBOCS and the CGI, before treatment (T0), at day 10 of treatment (T1) and at day 30 after treatment (T2); cTBS intervention was safe and without side effects. Since the design of our study does not allow us to draw conclusions on the effectiveness of the intervention with respect to the improvement of the functioning of the subject with GD, a more in-depth study, including a sham condition, neurocognitive measures of disinhibition and decision making, and collecting follow-up data on the sustained effect of TBS over a longer period is ongoing.
The brain hemispheres can be divided into an upper dorsal and a lower ventral system. Each system consists of distinct cortical regions connected via long association tracts. The tracts cross the ...central sulcus or the limen insulae to connect the frontal lobe with the posterior brain. The dorsal stream is associated with sensorimotor mapping. The ventral stream serves structural analysis and semantics in different domains, as visual, acoustic or space processing. How does the prefrontal cortex, regarded as the platform for the highest level of integration, incorporate information from these different domains? In the current view, the ventral pathway consists of several separate tracts, related to different modalities. Originally the assumption was that the ventral path is a continuum, covering all modalities. The latter would imply a very different anatomical basis for cognitive and clinical models of processing. To further define the ventral connections, we used cutting-edge in vivo global tractography on high-resolution diffusion tensor imaging (DTI) data from 100 normal subjects from the human connectome project and ex vivo preparation of fiber bundles in the extreme capsule of 8 humans using the Klingler technique. Our data showed that ventral stream tracts, traversing through the extreme capsule, form a continuous band of fibers that fan out anteriorly to the prefrontal cortex, and posteriorly to temporal, occipital and parietal cortical regions. Introduction of additional volumes of interest in temporal and occipital lobes differentiated between the inferior fronto-occipital fascicle (IFOF) and uncinate fascicle (UF). Unequivocally, in both experiments, in all subjects a connection between the inferior frontal and middle-to-posterior temporal cortical region, otherwise known as the temporo-frontal extreme capsule fascicle (ECF) from nonhuman primate brain-tracing experiments was identified. In the human brain, this tract connects the language domains of “Broca's area” and “Wernicke's area”. The differentiation in the three tracts, IFOF, UF and ECF seems arbitrary, all three pass through the extreme capsule. Our data show that the ventral pathway represents a continuum. The three tracts merge seamlessly and streamlines showed considerable overlap in their anterior and posterior course. Terminal maps identified prefrontal cortex in the frontal lobe and association cortex in temporal, occipital and parietal lobes as streamline endings. This anatomical substrate potentially facilitates the prefrontal cortex to integrate information across different domains and modalities.
Global fiber tracking centered on the anterior inferior extreme capsule produces a single fanning ventral pathway. Applying additional VOIs in the hind brain identifies the three standard tracts (UF, ECF, IFOF) merging seamlessly. Display omitted
In this paper, we propose an automated white matter connectivity analysis method for machine learning classification and characterization of white matter abnormality via identification of ...discriminative fiber tracts. The proposed method uses diffusion MRI tractography and a data-driven approach to find fiber clusters corresponding to subdivisions of the white matter anatomy. Features extracted from each fiber cluster describe its diffusion properties and are used for machine learning. The method is demonstrated by application to a pediatric neuroimaging dataset from 149 individuals, including 70 children with autism spectrum disorder (ASD) and 79 typically developing controls (TDC). A classification accuracy of 78.33% is achieved in this cross-validation study. We investigate the discriminative diffusion features based on a two-tensor fiber tracking model. We observe that the mean fractional anisotropy from the second tensor (associated with crossing fibers) is most affected in ASD. We also find that local along-tract (central cores and endpoint regions) differences between ASD and TDC are helpful in differentiating the two groups. These altered diffusion properties in ASD are associated with multiple robustly discriminative fiber clusters, which belong to several major white matter tracts including the corpus callosum, arcuate fasciculus, uncinate fasciculus and aslant tract; and the white matter structures related to the cerebellum, brain stem, and ventral diencephalon. These discriminative fiber clusters, a small part of the whole brain tractography, represent the white matter connections that could be most affected in ASD. Our results indicate the potential of a machine learning pipeline based on white matter fiber clustering.
The semantic variant of primary progressive aphasia (svPPA) is typically associated with frontotemporal lobar degeneration (FTLD) with longTAR DNA-binding protein (TDP)-43-positive neuropil threads ...and dystrophic neurites (type C), and is only rarely due to a primary tauopathy or Alzheimer's disease. We undertook this study to investigate the localisation and magnitude of the presumed tau Positron Emission Tomography (PET) tracer
FFlortaucipir (FTP; also known as T807 or AV1451) in patients with svPPA, hypothesising that most patients would not show tracer uptake different from controls.
FTP and
CPittsburgh compound B PET imaging as well as MRI were performed in seven patients with svPPA and in 20 controls. FTP signal was analysed by visual inspection and by quantitative comparison to controls, with and without partial volume correction.
All seven patients showed elevated FTP uptake in the anterior temporal lobe with a leftward asymmetry that was not observed in healthy controls. This elevated FTP signal, largely co-localised with atrophy, was evident on both visual inspection and quantitative cortical surface-based analysis. Five patients were amyloid negative, one was amyloid positive and one has an unknown amyloid status.
In this series of patients with clinical profiles, structural MRI and amyloid PET imaging typical for svPPA, FTP signal was unexpectedly elevated with a spatial pattern localised to areas of atrophy. This raises questions about the possible off-target binding of this tracer to non-tau molecules associated with neurodegeneration. Further investigation with autopsy analysis will help illuminate the binding target(s) of FTP in cases of suspected FTLD-TDP neuropathology.
A wealth of neuroimaging research has associated semantic variant primary progressive aphasia with distributed cortical atrophy that is most prominent in the left anterior temporal cortex; however, ...there is little consensus regarding which region within the anterior temporal cortex is most prominently damaged, which may indicate the putative origin of neurodegeneration. In this study, we localized the most prominent and consistent region of atrophy in semantic variant primary progressive aphasia using cortical thickness analysis in two independent patient samples (n = 16 and 28, respectively) relative to age-matched controls (n = 30). Across both samples the point of maximal atrophy was located in the same region of the left temporal pole. This same region was the point of maximal atrophy in 100% of individual patients in both semantic variant primary progressive aphasia samples. Using resting state functional connectivity in healthy young adults (n = 89), we showed that the seed region derived from the semantic variant primary progressive aphasia analysis was strongly connected with a large-scale network that closely resembled the distributed atrophy pattern in semantic variant primary progressive aphasia. In both patient samples, the magnitude of atrophy within a brain region was predicted by that region's strength of functional connectivity to the temporopolar seed region in healthy adults. These findings suggest that cortical atrophy in semantic variant primary progressive aphasia may follow connectional pathways within a large-scale network that converges on the temporal pole.
Computational modeling and simulations are increasingly being used to complement experimental testing for analysis of safety and efficacy of medical devices. Multiple voxel- and surface-based whole- ...and partial-body models have been proposed in the literature, typically with spatial resolution in the range of 1-2 mm and with 10-50 different tissue types resolved. We have developed a multimodal imaging-based detailed anatomical model of the human head and neck, named "MIDA". The model was obtained by integrating three different magnetic resonance imaging (MRI) modalities, the parameters of which were tailored to enhance the signals of specific tissues: i) structural T1- and T2-weighted MRIs; a specific heavily T2-weighted MRI slab with high nerve contrast optimized to enhance the structures of the ear and eye; ii) magnetic resonance angiography (MRA) data to image the vasculature, and iii) diffusion tensor imaging (DTI) to obtain information on anisotropy and fiber orientation. The unique multimodal high-resolution approach allowed resolving 153 structures, including several distinct muscles, bones and skull layers, arteries and veins, nerves, as well as salivary glands. The model offers also a detailed characterization of eyes, ears, and deep brain structures. A special automatic atlas-based segmentation procedure was adopted to include a detailed map of the nuclei of the thalamus and midbrain into the head model. The suitability of the model to simulations involving different numerical methods, discretization approaches, as well as DTI-based tensorial electrical conductivity, was examined in a case-study, in which the electric field was generated by transcranial alternating current stimulation. The voxel- and the surface-based versions of the models are freely available to the scientific community.
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