Using diffusion MRI data acquired with ultra-high gradient strength to improve tractography in routine-quality data

White matter tract involvement in anarchic hand syndrome following stroke: Diffusion tensor imaging study

Anarchic Hand Syndrome (AHS) is a rare neurological disorder characterized by involuntary, purposeful hand movements. AHS can also result from damage to the corpus callosum (CC), intra-hemispheric tracts, or descending tracts, but its precise causes remain unclear. This study aimed to identify the white matter tracts associated with AHS development using the automated reconstruction of 42 tracts from diffusion tensor imaging (DTI). We included three female AHS patients with anterior cerebral arterial (ACA) infarctions. Additionally, we enrolled 20 age-matched control subjects and six patients with ACA infarctions but without AHS symptoms (N-AHS group) for comparison. DTI was conducted in AHS, N-AHS, and control groups. Fractional anisotropy (FA) and volume values were extracted from the DTI datasets of participants using TRActs Constrained by UnderLying Anatomy (TRACULA) technique. The AHS group showed lower FA values of the CC body (parietal and temporal section), right arcuate fasciculus (AF), corticospinal tract, extreme capsule, inferior longitudinal fasciculus (ILF), and superior longitudinal fasciculus than the control group. However, these tracts exhibited no significant difference between N-AHS and control groups. Similarly, the volume value in the genu of CC in the AHS group was lower than controls, but not in other tracts. Our results suggests that the extensive CC lesion, especially in the posterior parietal and temporal section of CC body, and damage to intra-hemispheric tracts (AF and ILF), is associated with the development of AHS. These results involved in AHS and underscore the significance of considering a more complex network disruption, involving various white matter tracts beyond CC for understanding this syndrome.

Anisotropic light propagation in human brain white matter

Significance

Accurate modeling of light diffusion in the human brain is crucial for applications in optogenetics and spectroscopy diagnostic techniques. White matter tissue is composed of myelinated axon bundles, suggesting the occurrence of enhanced light diffusion along their local orientation direction, which however has never been characterized experimentally. Existing diffuse optics models assume isotropic properties, limiting their accuracy.

Aim

We aim to characterize the anisotropic scattering properties of human white matter tissue by directly measuring its tensor scattering components along different directions, and to correlate them with the local axon fiber orientation.

Approach

Using a time- and space-resolved setup, we image the transverse propagation of diffusely reflected light across two perpendicular directions in a ex vivo human brain sample. Local fiber orientation is independently determined using light sheet fluorescence microscopy (LSFM).

Results

The directional dependence of light propagation in organized myelinated axon bundles is characterized via Monte Carlo (MC) simulations accounting for a tensor scattering coefficient, revealing a lower scattering rate parallel to the fiber orientation. The effects of white matter anisotropy are further assessed by simulating a typical time-domain near-infrared spectroscopy measurement in a four-layer human head model.

Conclusions

This study provides a first characterization of the anisotropic scattering properties in ex vivo human white matter, highlighting its direct correlation with axon fiber orientation, and opening to the realization of quantitatively accurate anisotropy-aware human head 3D meshes for diffuse optics applications.

Shared and distinctive changes of the white matter integrity in generalized anxiety disorder with or without depressive disorder

BACKGROUND

Generalized anxiety disorder (GAD) is a prevalent anxiety disorder often comorbid with major depressive disorder (MDD). Previous neuroimaging studies have shown that white matter (WM) microstructural alterations are critical for efficient communication between brain regions, and play an important role in the pathology of GAD. However, the exact profile of WM abnormalities in GAD with and without comorbid MDD remain unclear. This study aimed to uncover them using a novel global probabilistic tractography technology named Tracts Constrained by Underlying Anatomy (TRACULA), and to assess the correlations between fascicle integrity and symptom severity.

METHODS

We recruited 20 pure GAD (p-GAD) patients, 14 GAD comorbid with MDD (GAD + MDD) patients, and 41 age- and sex-matched healthy controls (HCs). All participants underwent T1 magnetic resonance imaging and diffusion tensor imaging. For each subject, 42 WM fiber bundles of the whole brain were successfully tracked and calculated with five metrics including volume, fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD). Group comparison were firstly performed between the whole GAD patients and HCs. Then, we compared the differences among the three groups (the p-GAD, GAD + MDD patients and HCs) using the one-way ANCOVA and post hoc analysis with the Bonferroni correction. Furthermore, correlations between abnormal WM metrics and clinical symptom severity were examined using partial correlations analyses among patients.

RESULTS

Compare to HCs, both p-GAD and GAD + MDD patients exhibited decreased FA values in left superior longitudinal fasciculus (SLF) II, and right dorsal of cingulum bundle (CBD); Moreover, GAD + MDD patients showed decreased FA, increased MD and RD values in the central and temporal section of the body of the corpus callosum (CC-BODY), right SLF I and II compared to HCs. Within the GAD + MDD group, GAD-7 scores were negatively correlated with FA values (r = -0.75, p = 0.008) and positively correlated with RD values (r = 0.7, p = 0.017) in the right CBD.

CONCLUSION

This study identified both shared and distinctive changes in GAD patients with and without MDD. The shared WM disruption in the p-GAD and GAD + MDD groups located in the left SLF and right CBD, while only GAD + MDD patients showed distinctive changes in the central and temporal sections of the CC-BODY and right SLF. Current study gave a comprehensive characterization of WM abnormalities among these patients, and highlighted TRACULA's value in identifying critical WM changes.

Traumatic brain injury, posttraumatic stress disorder, and vascular risk are independently associated with white matter aging in Vietnam-Era veterans

OBJECTIVE

Traumatic brain injury (TBI), mental health conditions (e.g., posttraumatic stress disorder [PTSD]), and vascular comorbidities (e.g., hypertension, diabetes) are highly prevalent in the Veteran population and may exacerbate age-related changes to cerebral white matter (WM). Our study examined (1) relationships between health conditions-TBI history, PTSD, and vascular risk-and cerebral WM micro- and macrostructure, and (2) associations between WM measures and cognition.

METHOD

We analyzed diffusion tensor images from 183 older male Veterans (mean age = 69.18; SD = 3.61) with (n = 95) and without (n = 88) a history of TBI using tractography. Generalized linear models examined associations between health conditions and diffusion metrics. Total WM hyperintensity (WMH) volume was calculated from fluid-attenuated inversion recovery images. Robust regression examined associations between health conditions and WMH volume. Finally, elastic net regularized regression examined associations between WM measures and cognitive performance.

RESULTS

Veterans with and without TBI did not differ in severity of PTSD or vascular risk (p's >0.05). TBI history, PTSD, and vascular risk were independently associated with poorer WM microstructural organization (p's <0.5, corrected), however the effects of vascular risk were more numerous and widespread. Vascular risk was positively associated with WMH volume (p = 0.004, β=0.200, R2 = 0.034). Higher WMH volume predicted poorer processing speed (R2 = 0.052).

CONCLUSIONS

Relative to TBI history and PTSD, vascular risk may be more robustly associated with WM micro- and macrostructure. Furthermore, greater WMH burden is associated with poorer processing speed. Our study supports the importance of vascular health interventions in mitigating negative brain aging outcomes in Veterans.

Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging - A Symposium Review

Advances in the spatiotemporal resolution and field-of-view of neuroimaging tools are driving mesoscale studies for translational neuroscience. On October 10, 2023, the Center for Mesoscale Mapping (CMM) at the Massachusetts General Hospital (MGH) Athinoula A. Martinos Center for Biomedical Imaging and the Massachusetts Institute of Technology (MIT) Health Sciences Technology based Neuroimaging Training Program (NTP) hosted a symposium exploring the state-of-the-art in this rapidly growing area of research. "Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging" brought together researchers who use a broad range of imaging techniques to study brain structure and function at the convergence of the microscopic and macroscopic scales. The day-long event centered on areas in which the CMM has established expertise, including the development of emerging technologies and their application to clinical translational needs and basic neuroscience questions. The in-person symposium welcomed more than 150 attendees, including 57 faculty members, 61 postdoctoral fellows, 35 students, and four industry professionals, who represented institutions at the local, regional, and international levels. The symposium also served the training goals of both the CMM and the NTP. The event content, organization, and format were planned collaboratively by the faculty and trainees. Many CMM faculty presented or participated in a panel discussion, thus contributing to the dissemination of both the technologies they have developed under the auspices of the CMM and the findings they have obtained using those technologies. NTP trainees who benefited from the symposium included those who helped to organize the symposium and/or presented posters and gave "flash" oral presentations. In addition to gaining experience from presenting their work, they had opportunities throughout the day to engage in one-on-one discussions with visiting scientists and other faculty, potentially opening the door to future collaborations. The symposium presentations provided a deep exploration of the many technological advances enabling progress in structural and functional mesoscale brain imaging. Finally, students worked closely with the presenting faculty to develop this report summarizing the content of the symposium and putting it in the broader context of the current state of the field to share with the scientific community. We note that the references cited here include conference abstracts corresponding to the symposium poster presentations.

Altered interhemispheric connectivity in Huntington's Disease

Pyramidal cells give rise to the corpus callosum, interhemispheric fibers that constitute the associations between the left and the right hemispheres. These interconnections are the substrates of important neurological functions, such as perception, memory, emotion, and movement control, which are all affected in Huntington's disease (HD). In this study we used directional tract density patterns (dTDPs) to evaluate changes in interhemispheric connectivity in gene-expanded individuals, which included presymptomatic and early symptomatic HD subjects. Our results demonstrated regionally selective and progressive differences in dTDPs between distinct regions of the corpus callosum (subdivided by Hofer-Frahm scheme) in the gene-expanded cohorts. In the presymptomatic HD cohort, we found trends, such that the density of fibers was reduced in CC regions IIb, III, and IV (p < 0.05); fibers from these regions project to sensory, premotor, and motor cortical regions, respectively. In the HD cohort, we found reduction in the density of fibers in all CC regions, including in fibers extending to the cortical surface (p < 0.002). Our results support the use of dTDPs to evaluate individual and progressive changes in interhemispheric connectivity in HD.

Diffusion tensor imaging biomarkers and clinical assessments in amyotrophic lateral sclerosis (ALS) patients: an exploratory study

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by progressive loss of upper and lower motor neurons. Biomarkers are needed to improve diagnosis, gauge progression, and evaluate treatment. Diffusion tensor imaging (DTI) is a promising biomarker for detecting microstructural alterations in the white matter tracts. This study aimed to assess DTI metrics as biomarkers and to examine their relationship with clinical assessments in patients with ALS. Eleven patients with ALS and 21 healthy controls (HCs) underwent 3T MRI with DTI. DTI metrics, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD), were compared between key motor and extra-motor tract groups. Group comparisons and correlations between DTI metrics also correlated with clinical scores of disability (ALSFRS-R), muscle strength (dynamometry), and motor unit loss (MUNIX). Widespread differences were found between patients with ALS and HCs in DTI metrics, including decreased FA and increased diffusivity metrics. However, MD and RD are more sensitive metrics for detecting white matter changes in patients with ALS. Significant interhemispheric correlations between the tract DTI metrics were also observed. DTI metrics showed symmetry between the hemispheres and correlated with the clinical assessments. MD, RD, and AD increases significantly correlated with lower ALSFRS-R and MUNIX scores and weaker dynamometry results. DTI reveals microstructural damage along the motor and extra-motor regions in ALS patients. DTI metrics can serve as quantitative neuroimaging biomarkers for diagnosis, prognosis, monitoring of progression, and treatment. Combined analysis of imaging, electrodiagnostic, and functional biomarkers shows potential for characterizing disease pathophysiology and progression.

A practical guide for combining functional regions of interest and white matter bundles

Diffusion-weighted imaging (DWI) is the primary method to investigate macro- and microstructure of neural white matter in vivo. DWI can be used to identify and characterize individual-specific white matter bundles, enabling precise analyses on hypothesis-driven connections in the brain and bridging the relationships between brain structure, function, and behavior. However, cortical endpoints of bundles may span larger areas than what a researcher is interested in, challenging presumptions that bundles are specifically tied to certain brain functions. Functional MRI (fMRI) can be integrated to further refine bundles such that they are restricted to functionally-defined cortical regions. Analyzing properties of these Functional Sub-Bundles (FSuB) increases precision and interpretability of results when studying neural connections supporting specific tasks. Several parameters of DWI and fMRI analyses, ranging from data acquisition to processing, can impact the efficacy of integrating functional and diffusion MRI. Here, we discuss the applications of the FSuB approach, suggest best practices for acquiring and processing neuroimaging data towards this end, and introduce the FSuB-Extractor, a flexible open-source software for creating FSuBs. We demonstrate our processing code and the FSuB-Extractor on an openly-available dataset, the Natural Scenes Dataset.

Impact of pathogenic variants of the Ras-mitogen-activated protein kinase pathway on major white matter tracts in the human brain

Noonan syndrome and neurofibromatosis type 1 are genetic conditions linked to pathogenic variants in genes of the Ras-mitogen-activated protein kinase signalling pathway. Both conditions hyper-activate signalling of the Ras-mitogen-activated protein kinase pathway and exhibit a high prevalence of neuropsychiatric disorders. Further, animal models of Noonan syndrome and neurofibromatosis type 1 and human imaging studies show white matter abnormalities in both conditions. While these findings suggest Ras-mitogen-activated protein kinas pathway hyper-activation effects on white matter, it is unknown whether these effects are syndrome-specific or pathway-specific. To characterize the effect of Noonan syndrome and neurofibromatosis type 1 on human white matter's microstructural integrity and discern potential syndrome-specific influences on microstructural integrity of individual tracts, we collected diffusion-weighted imaging data from children with Noonan syndrome (n = 24), neurofibromatosis type 1 (n = 28) and age- and sex-matched controls (n = 31). We contrasted the clinical groups (Noonan syndrome or neurofibromatosis type 1) and controls using voxel-wise, tract-based and along-tract analyses. Outcomes included voxel-wise, tract-based and along-tract fractional anisotropy, axial diffusivity, radial diffusivity and mean diffusivity. Noonan syndrome and neurofibromatosis type 1 showed similar patterns of reduced fractional anisotropy and increased axial diffusivity, radial diffusivity, and mean diffusivity on white matter relative to controls and different spatial patterns. Noonan syndrome presented a more extensive spatial effect than neurofibromatosis type 1 on white matter integrity as measured by fractional anisotropy. Tract-based analysis also demonstrated differences in effect magnitude with overall lower fractional anisotropy in Noonan syndrome compared to neurofibromatosis type 1 (d = 0.4). At the tract level, Noonan syndrome-specific effects on fractional anisotropy were detected in association tracts (superior longitudinal, uncinate and arcuate fasciculi; P < 0.012), and neurofibromatosis type 1-specific effects were detected in the corpus callosum (P < 0.037) compared to controls. Results from along-tract analyses aligned with results from tract-based analyses and indicated that effects are pervasive along the affected tracts. In conclusion, we find that pathogenic variants in the Ras-mitogen-activated protein kinase pathway are associated with white matter abnormalities as measured by diffusion in the developing brain. Overall, Noonan syndrome and neurofibromatosis type 1 show common effects on fractional anisotropy and diffusion scalars, as well as specific unique effects, namely, on temporoparietal-frontal tracts (intra-hemispheric) in Noonan syndrome and on the corpus callosum (inter-hemispheric) in neurofibromatosis type 1. The observed specific effects not only confirm prior observations from independent cohorts of Noonan syndrome and neurofibromatosis type 1 but also inform on syndrome-specific susceptibility of individual tracts. Thus, these findings suggest potential targets for precise, brain-focused outcome measures for existing medications, such as MEK inhibitors, that act on the Ras-mitogen-activated protein kinase pathway.

Diffusion indices alteration in major white matter tracts of children with tic disorder using TRACULA

BACKGROUND

Tic disorder is a neuropsychiatric disorder characterized by involuntary movements or vocalizations. Previous studies utilizing diffusion-weighted imaging to explore white-matter alterations in tic disorders have reported inconsistent results regarding the affected tracts. We aimed to address this gap by employing a novel tractography technique for more detailed analysis.

METHODS

We analyzed MRI data from 23 children with tic disorders and 23 healthy controls using TRActs Constrained by UnderLying Anatomy (TRACULA), an advanced automated probabilistic tractography method. We examined fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity, and mean diffusivity in 42 specific significant white matter tracts.

RESULTS

Our findings revealed notable differences in the children with tic disorders compared to the control group. Specifically, there was a significant reduction in FA in the parietal part and splenium of the corpus callosum and the left corticospinal tract. Increased RD was observed in the temporal and splenium areas of the corpus callosum, the left corticospinal tract, and the left acoustic radiation. A higher mean diffusivity was also noted in the left middle longitudinal fasciculus. A significant correlation emerged between the severity of motor symptoms, measured by the Yale Global Tic Severity Scale, and FA in the parietal part of the corpus callosum, as well as RD in the left acoustic radiation.

CONCLUSION

These results indicate a pattern of reduced interhemispheric connectivity in the corpus callosum, aligning with previous studies and novel findings in the diffusion indices changes in the left corticospinal tract, left acoustic radiation, and left middle longitudinal fasciculus. Tic disorders might involve structural abnormalities in key white matter tracts, offering new insights into their pathogenesis.

Increased grey matter volumes in the temporal lobe and its relationship with cognitive functioning in euthymic patients with bipolar disorder

BACKGROUND

Bipolar disorder (BD) is characterized by episodic mood dysregulation, although a significant portion of patients suffer persistent cognitive impairment during euthymia. Previous magnetic resonance imaging (MRI) research suggests BD patients may have accelerated brain aging, observed as lower grey matter volumes. How these neurostructural alterations are related to the cognitive profile of BD is unclear.

METHODS

We aim to explore this relationship in euthymic BD patients with multimodal structural neuroimaging. A sample of 27 euthymic BD patients and 24 healthy controls (HC) underwent structural grey matter MRI and diffusion-weighted imaging (DWI). BD patient's cognition was also assessed. FreeSurfer algorithms were used to obtain estimations of regional grey matter volumes. White matter pathways were reconstructed using TRACULA, and four diffusion metrics were extracted. ANCOVA models were performed to compare BD patients and HC values of regional grey matter volume and diffusion metrics. Global brain measures were also compared. Bivariate Pearson correlations were explored between significant brain results and five cognitive domains.

RESULTS

Euthymic BD patients showed higher ventricular volume (F(1, 46) = 6.04; p = 0.018) and regional grey matter volumes in the left fusiform (F(1, 46) = 15.03; pFDR = 0.015) and bilateral parahippocampal gyri compared to HC (L: F(1, 46) = 12.79, pFDR = 0.025/ R: F(1, 46) = 15.25, pFDR = 0.015). Higher grey matter volumes were correlated with greater executive function (r = 0.53, p = 0.008).

LIMITATIONS

We evaluated a modest sample size with concurrent pharmacological treatment.

CONCLUSIONS

Higher medial temporal volumes in euthymic BD patients may be a potential signature of brain resilience and cognitive adaptation to a putative illness neuroprogression. This knowledge should be integrated into further efforts to implement imaging into BD clinical management.

Impact of repeated blast exposure on active-duty United States Special Operations Forces

United States (US) Special Operations Forces (SOF) are frequently exposed to explosive blasts in training and combat, but the effects of repeated blast exposure (RBE) on SOF brain health are incompletely understood. Furthermore, there is no diagnostic test to detect brain injury from RBE. As a result, SOF personnel may experience cognitive, physical, and psychological symptoms for which the cause is never identified, and they may return to training or combat during a period of brain vulnerability. In 30 active-duty US SOF, we assessed the relationship between cumulative blast exposure and cognitive performance, psychological health, physical symptoms, blood proteomics, and neuroimaging measures (Connectome structural and diffusion MRI, 7 Tesla functional MRI, [11C]PBR28 translocator protein [TSPO] positron emission tomography [PET]-MRI, and [18F]MK6240 tau PET-MRI), adjusting for age, combat exposure, and blunt head trauma. Higher blast exposure was associated with increased cortical thickness in the left rostral anterior cingulate cortex (rACC), a finding that remained significant after multiple comparison correction. In uncorrected analyses, higher blast exposure was associated with worse health-related quality of life, decreased functional connectivity in the executive control network, decreased TSPO signal in the right rACC, and increased cortical thickness in the right rACC, right insula, and right medial orbitofrontal cortex-nodes of the executive control, salience, and default mode networks. These observations suggest that the rACC may be susceptible to blast overpressure and that a multimodal, network-based diagnostic approach has the potential to detect brain injury associated with RBE in active-duty SOF.

A practical evaluation of measures derived from compressed sensing diffusion spectrum imaging

Diffusion Spectrum Imaging (DSI) using dense Cartesian sampling of q-space has been shown to provide important advantages for modeling complex white matter architecture. However, its adoption has been limited by the lengthy acquisition time required. Sparser sampling of q-space combined with compressed sensing (CS) reconstruction techniques has been proposed as a way to reduce the scan time of DSI acquisitions. However prior studies have mainly evaluated CS-DSI in post-mortem or non-human data. At present, the capacity for CS-DSI to provide accurate and reliable measures of white matter anatomy and microstructure in the living human brain remains unclear. We evaluated the accuracy and inter-scan reliability of 6 different CS-DSI schemes that provided up to 80% reductions in scan time compared to a full DSI scheme. We capitalized on a dataset of 26 participants who were scanned over eight independent sessions using a full DSI scheme. From this full DSI scheme, we subsampled images to create a range of CS-DSI images. This allowed us to compare the accuracy and inter-scan reliability of derived measures of white matter structure (bundle segmentation, voxel-wise scalar maps) produced by the CS-DSI and the full DSI schemes. We found that CS-DSI estimates of both bundle segmentations and voxel-wise scalars were nearly as accurate and reliable as those generated by the full DSI scheme. Moreover, we found that the accuracy and reliability of CS-DSI was higher in white matter bundles that were more reliably segmented by the full DSI scheme. As a final step, we replicated the accuracy of CS-DSI in a prospectively acquired dataset (n = 20, scanned once). Together, these results illustrate the utility of CS-DSI for reliably delineating in vivo white matter architecture in a fraction of the scan time, underscoring its promise for both clinical and research applications.

White matter microstructural plasticity associated with educational intervention in reading disability

Children's reading progress typically slows during extended breaks in formal education, such as summer vacations. This stagnation can be especially concerning for children with reading difficulties or disabilities, such as dyslexia, because of the potential to exacerbate the skills gap between them and their peers. Reading interventions can prevent skill loss and even lead to appreciable gains in reading ability during the summer. Longitudinal studies relating intervention response to brain changes can reveal educationally relevant insights into rapid learning-driven brain plasticity. The current work focused on reading outcomes and white matter connections, which enable communication among the brain regions required for proficient reading. We collected reading scores and diffusion-weighted images at the beginning and end of summer for 41 children with reading difficulties who had completed either 1st or 2nd grade. Children were randomly assigned to either receive an intensive reading intervention (n = 26; Seeing Stars from Lindamood-Bell which emphasizes orthographic fluency) or be deferred to a wait-list group (n = 15), enabling us to analyze how white matter properties varied across a wide spectrum of skill development and regression trajectories. On average, the intervention group had larger gains in reading compared to the non-intervention group, who declined in reading scores. Improvements on a proximal measure of orthographic processing (but not other more distal reading measures) were associated with decreases in mean diffusivity within core reading brain circuitry (left arcuate fasciculus and left inferior longitudinal fasciculus) and increases in fractional anisotropy in the left corticospinal tract. Our findings suggest that responses to intensive reading instruction are related predominantly to white matter plasticity in tracts most associated with reading.

Persistent hemiplegia with normal intraoperative neurophysiological monitoring in supratentorial neurosurgery: a case report and review of literature

Intraoperative neurophysiological monitoring (IONM) is needed for evaluating and demonstrating the integrity of the central and peripheral nervous system during surgical manoeuvres that take place in proximity to eloquent motor and somatosensory nervous structures. The integrity of the monitored motor pathways is not always followed by consistent clinical normality, particularly in the first hours/days following surgery, when surgical resection involves brain structures such as the supplementary motor areas (SMA). We report the case of a patient who underwent surgical excision of a right frontal glioblastoma with normal preoperative, intraoperative (IONM), and postoperative central motor conduction, but with persistent postoperative hemiplegia (> 6 months). The literature regarding SMA syndrome and its diagnosis and prognosis is reviewed.

Associations between white matter integrity of the cingulum bundle, surrounding gray matter regions, and cognition across the dementia continuum

INTRODUCTION

Previous Alzheimer's disease and related dementias (AD/ADRD) research studies have illustrated the significance of studying alterations in white matter (WM). Fewer studies have examined how WM integrity, measured with diffusion tensor imaging (DTI), is associated with volume of gray matter (GM) regions and measures of cognitive function in aged participants spanning the dementia continuum.

METHODS

Magnetic resonance imaging and cognitive data were collected from 241 Boston University Alzheimer's Disease Research Center participants who spanned from cognitively normal controls to amnestic mild cognitive impairment to having dementia. Primary DTI tracts of interest were the cingulum ventral (CV) and cingulum dorsal (CD) pathways. GM regions of interest (ROIs) were in the medial temporal lobe (MTL), prefrontal cortex, and retrosplenial cortex. Analyses of covariance models were used to assess differences in WM integrity across groups (control, amnestic mild cognitive impairment, and dementia). Multiple linear regression models were used to assess associations between WM integrity and GM volume, and with measures of memory and executive function.

RESULTS

Differences in WM integrity were shown in both cingulum pathways in participants across the dementia continuum. Associations between WM integrity of both cingulum pathways and volume of selected GM ROIs were widespread. Functionally significant associations were found between WM of the CV pathway and memory, independent of MTL GM volume.

DISCUSSION

Differences in WM integrity of the cingulum bundle and surrounding GM ROI are likely related to the progression of AD/ADRD. Such differences should continue to be studied, particularly in association with memory performance.

Military-related mild traumatic brain injury: clinical characteristics, advanced neuroimaging, and molecular mechanisms

Mild traumatic brain injury (mTBI) is a significant health burden among military service members. Although mTBI was once considered relatively benign compared to more severe TBIs, a growing body of evidence has demonstrated the devastating neurological consequences of mTBI, including chronic post-concussion symptoms and deficits in cognition, memory, sleep, vision, and hearing. The discovery of reliable biomarkers for mTBI has been challenging due to under-reporting and heterogeneity of military-related mTBI, unpredictability of pathological changes, and delay of post-injury clinical evaluations. Moreover, compared to more severe TBI, mTBI is especially difficult to diagnose due to the lack of overt clinical neuroimaging findings. Yet, advanced neuroimaging techniques using magnetic resonance imaging (MRI) hold promise in detecting microstructural aberrations following mTBI. Using different pulse sequences, MRI enables the evaluation of different tissue characteristics without risks associated with ionizing radiation inherent to other imaging modalities, such as X-ray-based studies or computerized tomography (CT). Accordingly, considering the high morbidity of mTBI in military populations, debilitating post-injury symptoms, and lack of robust neuroimaging biomarkers, this review (1) summarizes the nature and mechanisms of mTBI in military settings, (2) describes clinical characteristics of military-related mTBI and associated comorbidities, such as post-traumatic stress disorder (PTSD), (3) highlights advanced neuroimaging techniques used to study mTBI and the molecular mechanisms that can be inferred, and (4) discusses emerging frontiers in advanced neuroimaging for mTBI. We encourage multi-modal approaches combining neuropsychiatric, blood-based, and genetic data as well as the discovery and employment of new imaging techniques with big data analytics that enable accurate detection of post-injury pathologic aberrations related to tissue microstructure, glymphatic function, and neurodegeneration. Ultimately, this review provides a foundational overview of military-related mTBI and advanced neuroimaging techniques that merit further study for mTBI diagnosis, prognosis, and treatment monitoring.

Modular pipeline for reconstruction and localization of implanted intracranial ECoG and sEEG electrodes

Implantation of electrodes in the brain has been used as a clinical tool for decades to stimulate and record brain activity. As this method increasingly becomes the standard of care for several disorders and diseases, there is a growing need to quickly and accurately localize the electrodes once they are placed within the brain. We share here a protocol pipeline for localizing electrodes implanted in the brain, which we have applied to more than 260 patients, that is accessible to multiple skill levels and modular in execution. This pipeline uses multiple software packages to prioritize flexibility by permitting multiple different parallel outputs while minimizing the number of steps for each output. These outputs include co-registered imaging, electrode coordinates, 2D and 3D visualizations of the implants, automatic surface and volumetric localizations of the brain regions per electrode, and anonymization and data sharing tools. We demonstrate here some of the pipeline's visualizations and automatic localization algorithms which we have applied to determine appropriate stimulation targets, to conduct seizure dynamics analysis, and to localize neural activity from cognitive tasks in previous studies. Further, the output facilitates the extraction of information such as the probability of grey matter intersection or the nearest anatomic structure per electrode contact across all data sets that go through the pipeline. We expect that this pipeline will be a useful framework for researchers and clinicians alike to localize implanted electrodes in the human brain.

Accurate Bayesian segmentation of thalamic nuclei using diffusion MRI and an improved histological atlas

The human thalamus is a highly connected brain structure, which is key for the control of numerous functions and is involved in several neurological disorders. Recently, neuroimaging studies have increasingly focused on the volume and connectivity of the specific nuclei comprising this structure, rather than looking at the thalamus as a whole. However, accurate identification of cytoarchitectonically designed histological nuclei on standard in vivo structural MRI is hampered by the lack of image contrast that can be used to distinguish nuclei from each other and from surrounding white matter tracts. While diffusion MRI may offer such contrast, it has lower resolution and lacks some boundaries visible in structural imaging. In this work, we present a Bayesian segmentation algorithm for the thalamus. This algorithm combines prior information from a probabilistic atlas with likelihood models for both structural and diffusion MRI, allowing segmentation of 25 thalamic labels per hemisphere informed by both modalities. We present an improved probabilistic atlas, incorporating thalamic nuclei identified from histology and 45 white matter tracts surrounding the thalamus identified in ultra-high gradient strength diffusion imaging. We present a family of likelihood models for diffusion tensor imaging, ensuring compatibility with the vast majority of neuroimaging datasets that include diffusion MRI data. The use of these diffusion likelihood models greatly improves identification of nuclear groups versus segmentation based solely on structural MRI. Dice comparison of 5 manually identifiable groups of nuclei to ground truth segmentations show improvements of up to 10 percentage points. Additionally, our chosen model shows a high degree of reliability, with median test-retest Dice scores above 0.85 for four out of five nuclei groups, whilst also offering improved detection of differential thalamic involvement in Alzheimer's disease (AUROC 81.98%). The probabilistic atlas and segmentation tool will be made publicly available as part of the neuroimaging package FreeSurfer (https://freesurfer.net/fswiki/ThalamicNucleiDTI).

Microstructural and functional plasticity following repeated brain stimulation during cognitive training in older adults

The combination of repeated behavioral training with transcranial direct current stimulation (tDCS) holds promise to exert beneficial effects on brain function beyond the trained task. However, little is known about the underlying mechanisms. We performed a monocenter, single-blind randomized, placebo-controlled trial comparing cognitive training to concurrent anodal tDCS (target intervention) with cognitive training to concurrent sham tDCS (control intervention), registered at ClinicalTrial.gov (Identifier NCT03838211). The primary outcome (performance in trained task) and secondary behavioral outcomes (performance on transfer tasks) were reported elsewhere. Here, underlying mechanisms were addressed by pre-specified analyses of multimodal magnetic resonance imaging before and after a three-week executive function training with prefrontal anodal tDCS in 48 older adults. Results demonstrate that training combined with active tDCS modulated prefrontal white matter microstructure which predicted individual transfer task performance gain. Training-plus-tDCS also resulted in microstructural grey matter alterations at the stimulation site, and increased prefrontal functional connectivity. We provide insight into the mechanisms underlying neuromodulatory interventions, suggesting tDCS-induced changes in fiber organization and myelin formation, glia-related and synaptic processes in the target region, and synchronization within targeted functional networks. These findings advance the mechanistic understanding of neural tDCS effects, thereby contributing to more targeted neural network modulation in future experimental and translation tDCS applications.

Exploring interhemispheric connectivity using the directional tract density patterns of the corpus callosum

The corpus callosum (CC) is one of the most important interhemispheric white matter tracts that connects interrelated regions of the cerebral cortex. Its disruption has been investigated in previous studies and has been found to play an important role in several neurodegenerative disorders. Currently available methods to assess the interhemispheric connectivity of the CC have several limitations: i) they require the a priori identification of specific cortical regions as targets or seeds, ii) they are limited by the characterization of only small components of the structure, primarily voxels that constitute the mid-sagittal slice, and iii) they use global measures of microstructural integrity, which provide only limited characterization. In order to address some of these limitations, we developed a novel method that enables the characterization of white matter tracts covering the structure of CC, from the mid-sagittal plane to corresponding regions of cortex, using directional tract density patterns (dTDPs). We demonstrate that different regions of CC have distinctive dTDPs that reflect a unique regional topology. We conducted a pilot study using this approach to evaluate two different datasets collected from healthy subjects, and we demonstrate that this method is reliable, reproducible, and independent of diffusion acquisition parameters, suggesting its potential applicability to clinical applications.

Automated three-dimensional major white matter bundle segmentation using diffusion magnetic resonance imaging

White matter bundle segmentation using diffusion magnetic resonance imaging fiber tractography enables detailed evaluation of individual white matter tracts three-dimensionally, and plays a crucial role in studying human brain anatomy, function, development, and diseases. Manual extraction of streamlines utilizing a combination of the inclusion and exclusion of regions of interest can be considered the current gold standard for extracting white matter bundles from whole-brain tractograms. However, this is a time-consuming and operator-dependent process with limited reproducibility. Several automated approaches using different strategies to reconstruct the white matter tracts have been proposed to address the issues of time, labor, and reproducibility. In this review, we discuss few of the most well-validated approaches that automate white matter bundle segmentation with an end-to-end pipeline, including TRActs Constrained by UnderLying Anatomy (TRACULA), Automated Fiber Quantification, and TractSeg.

The rostral zona incerta: a subcortical integrative hub and potential DBS target for OCD

BACKGROUND

The zona incerta (ZI) is involved in mediating survival behaviors and is connected to a wide range of cortical and subcortical structures, including key basal ganglia nuclei. Based on these connections and their links to behavioral modulation, we propose that the ZI is a connectional hub for mediating between top-down and bottom-up control and a possible target for deep brain stimulation for obsessive-compulsive disorder.

METHODS

We analyzed the trajectory of cortical fibers to the ZI in nonhuman and human primates based on tracer injections in monkeys and high-resolution diffusion magnetic resonance imaging in humans. The organization of cortical and subcortical connections within the ZI were identified in the nonhuman primate studies.

RESULTS

Monkey anatomical data and human diffusion magnetic resonance imaging data showed a similar trajectory of fibers/streamlines to the ZI. Prefrontal cortex/anterior cingulate cortex terminals all converged within the rostral ZI, with dorsal and lateral areas being most prominent. Motor areas terminated caudally. Dense subcortical reciprocal connections included the thalamus, medial hypothalamus, substantia nigra/ventral tegmental area, reticular formation, and pedunculopontine nucleus and a dense nonreciprocal projection to the lateral habenula. Additional connections included the amygdala, dorsal raphe nucleus, and periaqueductal gray.

CONCLUSIONS

Dense connections with dorsal and lateral prefrontal cortex/anterior cingulate cortex cognitive control areas and the lateral habenula and the substantia nigra/ventral tegmental area, coupled with inputs from the amygdala, hypothalamus, and brainstem, suggest that the rostral ZI is a subcortical hub positioned to modulate between top-down and bottom-up control. A deep brain stimulation electrode placed in the rostral ZI would not only involve connections common to other deep brain stimulation sites but also capture several critically distinctive connections.

Automated detection of axonal damage along white matter tracts in acute severe traumatic brain injury

New techniques for individualized assessment of white matter integrity are needed to detect traumatic axonal injury (TAI) and predict outcomes in critically ill patients with acute severe traumatic brain injury (TBI). Diffusion MRI tractography has the potential to quantify white matter microstructure in vivo and has been used to characterize tract-specific changes following TBI. However, tractography is not routinely used in the clinical setting to assess the extent of TAI, in part because focal lesions reduce the robustness of automated methods. Here, we propose a pipeline that combines automated tractography reconstructions of 40 white matter tracts with multivariate analysis of along-tract diffusion metrics to assess the presence of TAI in individual patients with acute severe TBI. We used the Mahalanobis distance to identify abnormal white matter tracts in each of 18 patients with acute severe TBI as compared to 33 healthy subjects. In all patients for which a FreeSurfer anatomical segmentation could be obtained (17 of 18 patients), including 13 with focal lesions, the automated pipeline successfully reconstructed a mean of 37.5 ± 2.1 white matter tracts without the need for manual intervention. A mean of 2.5 ± 2.1 tracts resulted in partial or failed reconstructions and needed to be reinitialized upon visual inspection. The pipeline detected at least one abnormal tract in all patients (mean: 9.1 ± 7.9) and accurately discriminated between patients and controls (AUC: 0.91). The number and neuroanatomic location of abnormal tracts varied across patients and levels of consciousness. The premotor, temporal, and parietal sections of the corpus callosum were the most commonly damaged tracts (in 10, 9, and 8 patients, respectively), consistent with prior histopathological studies of TAI. TAI measures were not associated with concurrent behavioral measures of consciousness. In summary, we provide proof-of-principle evidence that an automated tractography pipeline has translational potential to detect and quantify TAI in individual patients with acute severe TBI.

Microstructural organization of the corpus callosum in young endurance athletes: A global tractography study

Introduction

Aerobic exercise training has been shown to improve microstructural organization of the corpus callosum (CC); however, evidence of this topographic effect is limited.

Purpose

To compare the CC microstructural organization between endurance athletes and sedentary adults using a white-matter fiber tractography approach.

Materials and methods

Diffusion tensor imaging (DTI) and T1-weighted structural data were collected from 15 male young endurance athletes and 16 age- and sex-matched sedentary adults. DTI data were analyzed with a global probabilistic tractography method based on neighborhood anatomical information. Fractional anisotropy (FA) and mean, radial (RD), and axial diffusivities were measured in the eight CC tracts: rostrum, genu, splenium, and body's prefrontal, premotor, central, parietal, and temporal tracts. Cortical thickness of the CC tract endpoints and the CC tract length and volume were also measured. Physical activity level was assessed by metabolic equivalents (METs).

Results

The athlete group had an average VO2max of 69.5 ± 3.1 ml/kg/min, which is above 90%ile according to the American College of Sports Medicine guideline. Compared with the sedentary group, the athlete group had higher FA in the CC body's premotor and parietal tracts and the CC splenium. These tracts showed lower RD in the athlete compared with sedentary group. The voxelwise analysis confirmed that the athlete group had higher FA in the CC and other white matter regions than the sedentary group, including the corona radiata, internal capsule, and superior longitudinal fasciculus. Cortical thickness of the CC tract endpoints and the CC tract lengths and volumes were similar between the two groups. Physical activity levels were positively correlated with FA in the CC body's parietal (r = 0.486, p = 0.006) and temporal (r = 0.425, p = 0.017) tracts and the CC splenium (r = 0.408, p = 0.023).

Conclusion

Young endurance athletes have higher microstructural organization of the CC tracts connected the sensorimotor and visual cortices than the age- and sex-matched sedentary adults.

Automatic segmentation of the core of the acoustic radiation in humans

Introduction

Acoustic radiation is one of the most important white matter fiber bundles of the human auditory system. However, segmenting the acoustic radiation is challenging due to its small size and proximity to several larger fiber bundles. TractSeg is a method that uses a neural network to segment some of the major fiber bundles in the brain. This study aims to train TractSeg to segment the core of acoustic radiation.

Methods

We propose a methodology to automatically extract the acoustic radiation from human connectome data, which is both of high quality and high resolution. The segmentation masks generated by TractSeg of nearby fiber bundles are used to steer the generation of valid streamlines through tractography. Only streamlines connecting the Heschl's gyrus and the medial geniculate nucleus were considered. These streamlines are then used to create masks of the core of the acoustic radiation that is used to train the neural network of TractSeg. The trained network is used to automatically segment the acoustic radiation from unseen images.

Results

The trained neural network successfully extracted anatomically plausible masks of the core of the acoustic radiation in human connectome data. We also applied the method to a dataset of 17 patients with unilateral congenital ear canal atresia and 17 age- and gender-paired controls acquired in a clinical setting. The method was able to extract 53/68 acoustic radiation in the dataset acquired with clinical settings. In 14/68 cases, the method generated fragments of the acoustic radiation and completely failed in a single case. The performance of the method on patients and controls was similar.

Discussion

In most cases, it is possible to segment the core of the acoustic radiations even in images acquired with clinical settings in a few seconds using a pre-trained neural network.

Population-based tract-to-region connectome of the human brain and its hierarchical topology

Connectome maps region-to-region connectivities but does not inform which white matter pathways form the connections. Here we constructed a population-based tract-to-region connectome to fill this information gap. The constructed connectome quantifies the population probability of a white matter tract innervating a cortical region. The results show that ~85% of the tract-to-region connectome entries are consistent across individuals, whereas the remaining (~15%) have substantial individual differences requiring individualized mapping. Further hierarchical clustering on cortical regions revealed dorsal, ventral, and limbic networks based on the tract-to-region connective patterns. The clustering results on white matter bundles revealed the categorization of fiber bundle systems in the association pathways. This tract-to-region connectome provides insights into the connective topology between cortical regions and white matter bundles. The derived hierarchical relation further offers a categorization of gray and white matter structures.

The brain connectome maps region-to-region connections but often ignores the role of the connecting pathways. Here, the authors mapped the tract-to-region relations to reveal the hierarchical relation of fiber bundles and dorsal, ventral, and limbic networks.

The influence of regions of interest on tractography virtual dissection protocols: general principles to learn and to follow

Efficient communication across fields of research is challenging, especially when they are at opposite ends of the physical and digital spectrum. Neuroanatomy and neuroimaging may seem close to each other. When neuroimaging studies try to isolate structures of interest, according to a specific anatomical definition, a variety of challenges emerge. It is a non-trivial task to convert the neuroanatomical knowledge to instructions and rules to be executed in neuroimaging software. In the process called "virtual dissection" used to isolate coherent white matter structure in tractography, each white matter pathway has its own set of landmarks (regions of interest) used as inclusion and exclusion criteria. The ability to segment and study these pathways is critical for scientific progress, yet, variability may depend on region placement, and be influenced by the person positioning the region (i.e., a rater). When raters' variability is taken into account, the impact made by each region of interest becomes even more difficult to interpret. A delicate balance between anatomical validity, impact on the virtual dissection and raters' reproducibility emerge. In this work, we investigate this balance by leveraging manual delineation data of a group of raters from a previous study to quantify which set of landmarks and criteria contribute most to variability in virtual dissection. To supplement our analysis, the variability of each pathway with a region-by-region exploration was performed. We present a detailed exploration and description of each region, the causes of variability and its impacts. Finally, we provide a brief overview of the lessons learned from our previous virtual dissection projects and propose recommendations for future virtual dissection protocols as well as perspectives to reach better community agreement when it comes to anatomical definitions of white matter pathways.

Mapping the human connectome using diffusion MRI at 300 mT/m gradient strength: Methodological advances and scientific impact

Tremendous efforts have been made in the last decade to advance cutting-edge MRI technology in pursuit of mapping structural connectivity in the living human brain with unprecedented sensitivity and speed. The first Connectom 3T MRI scanner equipped with a 300 mT/m whole-body gradient system was installed at the Massachusetts General Hospital in 2011 and was specifically constructed as part of the Human Connectome Project. Since that time, numerous technological advances have been made to enable the broader use of the Connectom high gradient system for diffusion tractography and tissue microstructure studies and leverage its unique advantages and sensitivity to resolving macroscopic and microscopic structural information in neural tissue for clinical and neuroscientific studies. The goal of this review article is to summarize the technical developments that have emerged in the last decade to support and promote large-scale and scientific studies of the human brain using the Connectom scanner. We provide a brief historical perspective on the development of Connectom gradient technology and the efforts that led to the installation of three other Connectom 3T MRI scanners worldwide - one in the United Kingdom in Cardiff, Wales, another in continental Europe in Leipzig, Germany, and the latest in Asia in Shanghai, China. We summarize the key developments in gradient hardware and image acquisition technology that have formed the backbone of Connectom-related research efforts, including the rich array of high-sensitivity receiver coils, pulse sequences, image artifact correction strategies and data preprocessing methods needed to optimize the quality of high-gradient strength diffusion MRI data for subsequent analyses. Finally, we review the scientific impact of the Connectom MRI scanner, including advances in diffusion tractography, tissue microstructural imaging, ex vivo validation, and clinical investigations that have been enabled by Connectom technology. We conclude with brief insights into the unique value of strong gradients for diffusion MRI and where the field is headed in the coming years.

Visual Attention and Poor Sleep Quality

Background

Sleep deprivation disrupts visual attention; however, the effects of chronic poor sleep quality on it are not understood. The dorsal attention network (DAN) and the ventral attention network (VAN) are involved in visual attention and search (VSA), with the DAN being important for the serial attention network and the VAN for parallel “pop-out” visual search.

Objective

The aim of the study was to evaluate correlation of sleep quality with visual attention and search, functional, and tracts’ properties of the DAN and VAN.

Materials and Methods

We recruited 79 young male subjects and assessed their sleep quality using the Pittsburgh Sleep Quality Index (PSQI), dividing subjects into poor sleepers (PSs) and good sleepers (GSs) based on a cutoff of 5. Daytime sleepiness, sleep hygiene, depression, and anxiety levels were also evaluated. We assessed VSA using a computerized match-to-sample (MTS) task. We extracted functional networks and tracts of the VAN and DAN and statistically assessed group differences in task performance and imaging covarying age, depression, and anxiety. An interaction model with MTS × group was also done on imaging.

Results

In total, 43.67% of subjects were PSs. Sleep quality significantly correlated with daytime sleepiness, sleep hygiene, depression, and anxiety (all p &lt; 0.001). No between-group differences were seen in task performance and functional or tract properties of the attention networks. Interaction analysis showed that the task performance was highly reliant on the DAN in PSs and on the VAN in GSs.

Conclusion

Our findings show no association between sleep quality and VSA in task performance and imaging correlates of the attention network. However, unlike the GS group, poor sleep quality is associated with VSA being more reliant on the DAN than on the VAN.

Long-Term Effects of Repeated Blast Exposure in United States Special Operations Forces Personnel: A Pilot Study Protocol

Emerging evidence suggests that repeated blast exposure (RBE) is associated with brain injury in military personnel. United States (U.S.) Special Operations Forces (SOF) personnel experience high rates of blast exposure during training and combat, but the effects of low-level RBE on brain structure and function in SOF have not been comprehensively characterized. Further, the pathophysiological link between RBE-related brain injuries and cognitive, behavioral, and physical symptoms has not been fully elucidated. We present a protocol for an observational pilot study, Long-Term Effects of Repeated Blast Exposure in U.S. SOF Personnel (ReBlast). In this exploratory study, 30 active-duty SOF personnel with RBE will participate in a comprehensive evaluation of: 1) brain network structure and function using Connectome magnetic resonance imaging (MRI) and 7 Tesla MRI; 2) neuroinflammation and tau deposition using positron emission tomography; 3) blood proteomics and metabolomics; 4) behavioral and physical symptoms using self-report measures; and 5) cognition using a battery of conventional and digitized assessments designed to detect subtle deficits in otherwise high-performing individuals. We will identify clinical, neuroimaging, and blood-based phenotypes that are associated with level of RBE, as measured by the Generalized Blast Exposure Value. Candidate biomarkers of RBE-related brain injury will inform the design of a subsequent study that will test a diagnostic assessment battery for detecting RBE-related brain injury. Ultimately, we anticipate that the ReBlast study will facilitate the development of interventions to optimize the brain health, quality of life, and battle readiness of U.S. SOF personnel.

An atlas of white matter anatomy, its variability, and reproducibility based on constrained spherical deconvolution of diffusion MRI

Virtual dissection of white matter (WM) using diffusion MRI tractography is confounded by its poor reproducibility. Despite the increased adoption of advanced reconstruction models, early region-of-interest driven protocols based on diffusion tensor imaging (DTI) remain the dominant reference for virtual dissection protocols. Here we bridge this gap by providing a comprehensive description of typical WM anatomy reconstructed using a reproducible automated subject-specific parcellation-based approach based on probabilistic constrained-spherical deconvolution (CSD) tractography. We complement this with a WM template in MNI space comprising 68 bundles, including all associated anatomical tract selection labels and associated automated workflows. Additionally, we demonstrate bundle inter- and intra-subject variability using 40 (20 test-retest) datasets from the human connectome project (HCP) and 5 sessions with varying b-values and number of b-shells from the single-subject Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation (MASSIVE) dataset. The most reliably reconstructed bundles were the whole pyramidal tracts, primary corticospinal tracts, whole superior longitudinal fasciculi, frontal, parietal and occipital segments of the corpus callosum and middle cerebellar peduncles. More variability was found in less dense bundles, e.g., the fornix, dentato-rubro-thalamic tract (DRTT), and premotor pyramidal tract. Using the DRTT as an example, we show that this variability can be reduced by using a higher number of seeding attempts. Overall inter-session similarity was high for HCP test-retest data (median weighted-dice = 0.963, stdev = 0.201 and IQR = 0.099). Compared to the HCP-template bundles there was a high level of agreement for the HCP test-retest data (median weighted-dice = 0.747, stdev = 0.220 and IQR = 0.277) and for the MASSIVE data (median weighted-dice = 0.767, stdev = 0.255 and IQR = 0.338). In summary, this WM atlas provides an overview of the capabilities and limitations of automated subject-specific probabilistic CSD tractography for mapping white matter fasciculi in healthy adults. It will be most useful in applications requiring a reproducible parcellation-based dissection protocol, and as an educational resource for applied neuroimaging and clinical professionals.