Probabilistic Diffusion Tractography Research Articles

PadGAN: An End-to-End dMRI Data Augmentation Method for Macaque Brain

Currently, an increasing number of macaque brain MRI datasets are being made publicly accessible. Unlike human, publicly accessible macaque brain datasets suffer from data quality in diffusion magnetic resonance imaging (dMRI) data. Typically, dMRI data require a minimum ratio of 1:10 between low b-value (b < 10) volumes and high b-value (b > 300) volumes. However, the currently accessible macaque datasets do not meet this ratio. Due to site differences in macaque brain images, traditional human brain image-to-image translation models struggle to perform well on macaque brain images. Our work introduces a novel end-to-end primary-auxiliary dual generative adversarial network (PadGAN) for generating low b-value images. The auxiliary generator in the PadGAN is responsible for extracting the latent space features from peak information maps and transmitting them to the primary generator, enabling the primary generator to generate images with rich details. Experimental results demonstrate that PadGAN outperforms existing methods both qualitatively and quantitatively (mean SSIM increased by 0.1139). Diffusion probabilistic tractography using dMRI data augmented by our method yields superior results.

Disrupted brain structural networks associated with depression and cognitive dysfunction in cerebral small vessel disease with microbleeds

Emerging evidence highlights cerebral microbleeds (CMBs) as hallmarks of cerebral small vessel disease (CSVD) underlying depression and cognitive dysfunction. This study aimed to reveal how depression and cognition-related white matter (WM) abnormalities are topologically presented, and the network-level structural disruptions associated with CMBs in CSVD. We used probabilistic diffusion tractography and graph theory to investigate brain WM network topology in CSVD patients with (n = 64, CSVD-c) and without (n = 138, CSVD-n) CMBs and 90 healthy controls. Then we evaluated the Pearson's correlations between disrupted network metrics and neuropsychological parameters. For global topology, the CSVD-c group exhibited significantly decreased global (Eglob) and local (Eloc) efficiency and increased shortest path length compared with the controls, while no significant difference was found between the CSVD-c and CSVD-n groups. For regional topology, although all groups showed highly similar hub distributions, compare with control group, the CSVD-c group exhibited significantly decreased nodal efficiency mainly in the bilateral supplementary motor area (SMA), median cingulate gyrus (DCG) and right orbital middle frontal gyrus, while the CSVD-n group showed significantly decreased nodal efficiency only in the right SMA. Notably, Eglob, Eloc and nodal efficiency of the right anterior cingulate gyrus, DCG, middle temporal gyrus and left insula showed significantly negative correlations with depression score, significantly positive correlations with Rey auditory verbal learning test and symbol digit modalities test scores in CSVD-n group, as well as significantly negative correlations with Stroop color-word test scores in CSVD-c group. The WM networks of CSVD patients are characterized by decreased global integration and local specialization, and decreased nodal efficiency highly related to depression and cognitive dysfunction in the attention, default mode network and sensorimotor regions. These findings provide new insight into the neurobiological mechanisms of CSVD and concomitant affective and cognitive disorders.

Depression- and anxiety-associated disrupted brain structural networks revealed by probabilistic tractography in thyroid associated ophthalmopathy

BackgroundPatients with thyroid-associated opthalmopathy (TAO) have widespread white matter (WM) abnormalities in the emotional and cognitive functional regions. However, the topological representation of these WM abnormalities and the network-level structural aberrations underlying TAO and concomitant affective disorders are still unclear. MethodsWe used probabilistic diffusion tractography and graph theory to investigate brain network topology in 37 active, 35 inactive TAO patients and 23 healthy controls. Then, we evaluated the partial correlations between network topological metrics and clinical parameters. ResultsFor global topology, only active TAO patients exhibited significantly decreased global (Eglob) and local (Eloc) efficiency compared with controls, while no significant difference was observed between active and inactive TAO patients. For regional topology, we found a significantly decreased nodal efficiency in the left orbital superior frontal gyrus (ORBsup), medial orbital superior frontal gyrus (ORBsupmed), hippocampus and amygdala in active TAO patients compared with inactive ones. Intriguingly, Eglob, Eloc, and nodal efficiency of left ORBsup, ORBsupmed, olfactory cortex, gyrus rectus, hippocampus, right parahippocampal gyrus and amygdala had significantly positive correlations with anxiety/depression scores, bilateral exophthalmos and intraocular pressure in active TAO patients, while no significant correlation was observed in inactive TAO patients. LimitationsNo longitudinal follow-up. ConclusionsWM networks of TAO are characterized by decreased local specialization and global integration in the active phase, and decreased nodal efficiency highly related to anxiety and depression in the emotional and cognitive regions. Our findings provide new insight regarding the neurobiological mechanisms of TAO and contribute to the treatment of concomitant affective disorders.

In humans, striato-pallido-thalamic projections are largely segregated by their origin in either the striosome-like or matrix-like compartments

Cortico-striato-thalamo-cortical (CSTC) loops are fundamental organizing units in mammalian brains. CSTCs process limbic, associative, and sensorimotor information in largely separated but interacting networks. CTSC loops pass through paired striatal compartments, striosome (aka patch) and matrix, segregated pools of medium spiny projection neurons with distinct embryologic origins, cortical/subcortical structural connectivity, susceptibility to injury, and roles in behaviors and diseases. Similarly, striatal dopamine modulates activity in striosome and matrix in opposite directions. Routing CSTCs through one compartment may be an anatomical basis for regulating discrete functions. We used differential structural connectivity, identified through probabilistic diffusion tractography, to distinguish the striatal compartments (striosome-like and matrix-like voxels) in living humans. We then mapped compartment-specific projections and quantified structural connectivity between each striatal compartment, the globus pallidus interna (GPi), and 20 thalamic nuclei in 221 healthy adults. We found that striosome-originating and matrix-originating streamlines were segregated within the GPi: striosome-like connectivity was significantly more rostral, ventral, and medial. Striato-pallido-thalamic streamline bundles that were seeded from striosome-like and matrix-like voxels transited spatially distinct portions of the white matter. Matrix-like streamlines were 5.7-fold more likely to reach the GPi, replicating animal tract-tracing studies. Striosome-like connectivity dominated in six thalamic nuclei (anteroventral, central lateral, laterodorsal, lateral posterior, mediodorsal-medial, and medial geniculate). Matrix-like connectivity dominated in seven thalamic nuclei (centromedian, parafascicular, pulvinar-anterior, pulvinar-lateral, ventral lateral-anterior, ventral lateral-posterior, ventral posterolateral). Though we mapped all thalamic nuclei independently, functionally-related nuclei were matched for compartment-level bias. We validated these results with prior thalamostriate tract tracing studies in non-human primates and other species; where reliable data was available, all agreed with our measures of structural connectivity. Matrix-like connectivity was lateralized (left > right hemisphere) in 18 thalamic nuclei, independent of handedness, diffusion protocol, sex, or whether the nucleus was striosome-dominated or matrix-dominated. Compartment-specific biases in striato-pallido-thalamic structural connectivity suggest that routing CSTC loops through striosome-like or matrix-like voxels is a fundamental mechanism for organizing and regulating brain networks. Our MRI-based assessments of striato-thalamic connectivity in humans match and extend the results of prior tract tracing studies in animals. Compartment-level characterization may improve localization of human neuropathologies and improve neurosurgical targeting in the GPi and thalamus.

Topological alterations in white matter structural networks in fibromyalgia.

Neuroimaging studies employing analyses dependent on regional assumptions and specific neuronal circuits could miss characteristics of whole-brain structural connectivity critical to the pathophysiology of fibromyalgia (FM). This study applied the whole-brain graph-theoretical approach to identify whole-brain structural connectivity disturbances in FM. This cross-sectional study used probabilistic diffusion tractography and graph theory analysis to evaluate the topological organization of brain white matter networks in 20 patients with FM and 20 healthy controls (HCs). The relationship between brain network metrics and clinical variables was evaluated. Compared with HCs, FM patients had lower clustering coefficient, local efficiency, hierarchy, synchronization, and higher normalized characteristic path length. Regionally, patients demonstrated a significant reduction in nodal efficiency and centrality; these regions were mainly located in the prefrontal, temporal cortex, and basal ganglia. The network-based statistical analysis (NBS) identified decreased structural connectivity in a subnetwork of prefrontal cortex, basal ganglia, and thalamus in FM. There was no correlation between network metrics and clinical variables (false discovery rate corrected). The current research demonstrated disrupted topological architecture of white matter networks in FM. Our results suggested compromised neural integration and segregation and reduced structural connectivity in FM.

Decreased Local Specialization of Brain Structural Networks Associated with Cognitive Dysfuntion Revealed by Probabilistic Diffusion Tractography for Different Cerebral Small Vessel Disease Burdens

To reveal the network-level structural disruptions associated with cognitive dysfunctions in different cerebral small vessel disease (CSVD) burdens, we used probabilistic diffusion tractography and graph theory to investigate the brain network topology in 67 patients with a severe CSVD burden (CSVD-s), 133 patients with a mild CSVD burden (CSVD-m) and 89 healthy controls. We used one-way analysis of covariance to assess the altered topological measures between groups, and then evaluated their Pearson correlation with cognitive parameters. Both the CSVD and control groups showed efficient small-world organization in white matter (WM) networks. However, compared with CSVD-m patients and controls, CSVD-s patients exhibited significantly decreased local efficiency, with partially reorganized hub distributions. For regional topology, CSVD-s patients showed significantly decreased nodal efficiency in the bilateral anterior cingulate gyrus, caudate nucleus, right opercular inferior frontal gyrus (IFGoperc), supplementary motor area (SMA), insula and left orbital superior frontal gyrus and angular gyrus. Intriguingly, global/local efficiency and nodal efficiency of the bilateral caudate nucleus, right IFGoperc, SMA and left angular gyrus showed significant correlations with cognitive parameters in the CSVD-s group, while only the left pallidum showed significant correlations with cognitive metrics in the CSVD-m group. In conclusion, the decreased local specialization of brain structural networks in patients with different CSVD burdens provides novel insights into understanding the brain structural alterations in relation to CSVD severity. Cognitive correlations with brain structural network efficiency suggest their potential use as neuroimaging biomarkers to assess the severity of CSVD.

Network structure-function coupling and neurocognition in cerebral small vessel disease

BackgroundCerebral small vessel disease is a leading cause of cognitive decline and vascular dementia. Small vessel disease pathology changes structural brain networks, but its impact on functional networks remains poorly understood. Structural and functional networks are closely coupled in healthy individuals, and decoupling is associated with clinical symptoms in other neurological conditions. We tested the hypothesis that structural–functional network coupling is related to neurocognitive outcomes in 262 small vessel disease patients. MethodsParticipants underwent multimodal magnetic resonance imaging and cognitive assessment in 2011 and 2015. Structural connectivity networks were reconstructed using probabilistic diffusion tractography, while functional connectivity networks were estimated from resting-state functional magnetic resonance imaging. Structural and functional networks were then correlated to calculate a measure of structural–functional network coupling for each participant. ResultsLower whole-brain coupling was associated with reduced processing speed and greater apathy both cross-sectionally and longitudinally. In addition, coupling within the cognitive control network was associated with all cognitive outcomes, suggesting that neurocognitive outcomes in small vessel disease may be related to the functioning of this intrinsic connectivity network. ConclusionsOur work demonstrates the influence of structural–functional connectivity network decoupling in small vessel disease symptomatology. Cognitive control network function may be investigated in future studies.

Human brain structural connectivity matrices–ready for modelling

The human brain represents a complex computational system, the function and structure of which may be measured using various neuroimaging techniques focusing on separate properties of the brain tissue and activity. We capture the organization of white matter fibers acquired by diffusion-weighted imaging using probabilistic diffusion tractography. By segmenting the results of tractography into larger anatomical units, it is possible to draw inferences about the structural relationships between these parts of the system. This pipeline results in a structural connectivity matrix, which contains an estimate of connection strength among all regions. However, raw data processing is complex, computationally intensive, and requires expert quality control, which may be discouraging for researchers with less experience in the field. We thus provide brain structural connectivity matrices in a form ready for modelling and analysis and thus usable by a wide community of scientists. The presented dataset contains brain structural connectivity matrices together with the underlying raw diffusion and structural data, as well as basic demographic data of 88 healthy subjects.

MRI-Visible Anatomy of the Brainstem.

Human brainstem internal anatomy is intricate, complex, and essential to normal brain function. The brainstem is affected by stroke, multiple sclerosis, and most neurodegenerative diseases-a 1-mm focus of pathologic condition can have profound clinical consequences. Unfortunately, detailed internal brainstem anatomy is difficult to see with conventional MRI sequences. We review normal brainstem anatomy visualized on widely available clinical 3-T MRI scanners using fast gray matter acquisition T1 inversion recovery, probabilistic diffusion tractography, neuromelanin, and susceptibility-weighted imaging. Better anatomic localization using these recent innovations improves our ability to diagnose, localize, and treat brainstem diseases. We aim to provide an accessible review of the most clinically relevant brainstem neuroanatomy.

Differential responses to breath-holding, voluntary deep breathing and hypercapnia in left and right dorsal anterior cingulate.

What is the central question of this study? What is the role of dorsal anterior cingulate cortex (ACC) in respiration control in humans? What is the main finding and its importance? Direct evidence is provided for a role of the ACC in respiratory control in humans. The neurophysiological responses in dorsal ACC to different breathing tasks varied and were different between left and right ACC. The role of subcortical structures and cerebral cortex in the maintenance of respiratory homeostasis in humans remains poorly understood. Emerging evidence suggests an important role of the anterior cingulate cortex (ACC) in respiratory control. In this study, local field potentials (LFPs) from dorsal ACC were recorded in humans through implanted deep brain electrodes during several breathing activities, including voluntary activities of breath-holding and deep breathing, and involuntary activities of inspiration of varying concentrations of carbon dioxide (1%, 3%, 5% and 7%). We found that the breath-holding task induced significant unilateral left-sided ACC changes in LFP power, including an increased activity in lower frequency bands (3-5Hz) and decreased activity in higher frequency bands (12-26Hz). The respiratory task involving reflex increase in ventilation due to hypercapnia (raised inspired CO2 ) was associated with bilateral changes in activity of the ACC (again with increased activity in lower frequency bands and reduced activity in higher frequency bands). The voluntary breathing task with associated hypocapnia (deep breathing) induced bilateral changes in activity within low frequency bands. Furthermore, probabilistic diffusion tractography analysis showed left-sided connection of the ACC with the insula and frontal operculum, and bilateral connections within subsections of the cingulate gyrus and the thalamus. This electrophysiological analysis provides direct evidence for a role of the ACC in respiratory control in humans.

Two cortical representations of voice control are differentially involved in speech fluency.

Recent studies have identified two distinct cortical representations of voice control in humans, the ventral and the dorsal laryngeal motor cortex. Strikingly, while persistent developmental stuttering has been linked to a white-matter deficit in the ventral laryngeal motor cortex, intensive fluency-shaping intervention modulated the functional connectivity of the dorsal laryngeal motor cortical network. Currently, it is unknown whether the underlying structural network organization of these two laryngeal representations is distinct or differently shaped by stuttering intervention. Using probabilistic diffusion tractography in 22 individuals who stutter and participated in a fluency shaping intervention, in 18 individuals who stutter and did not participate in the intervention and in 28 control participants, we here compare structural networks of the dorsal laryngeal motor cortex and the ventral laryngeal motor cortex and test intervention-related white-matter changes. We show (i) that all participants have weaker ventral laryngeal motor cortex connections compared to the dorsal laryngeal motor cortex network, regardless of speech fluency, (ii) connections of the ventral laryngeal motor cortex were stronger in fluent speakers, (iii) the connectivity profile of the ventral laryngeal motor cortex predicted stuttering severity (iv) but the ventral laryngeal motor cortex network is resistant to a fluency shaping intervention. Our findings substantiate a weaker structural organization of the ventral laryngeal motor cortical network in developmental stuttering and imply that assisted recovery supports neural compensation rather than normalization. Moreover, the resulting dissociation provides evidence for functionally segregated roles of the ventral laryngeal motor cortical and dorsal laryngeal motor cortical networks.

A Whole-Cortex Probabilistic Diffusion Tractography Connectome.

The WU-Minn Human Connectome Project (HCP) is a publicly-available dataset containing state-of-the-art structural magnetic resonance imaging (MRI), functional MRI (fMRI), and diffusion MRI (dMRI) for over a thousand healthy subjects. While the planned scope of the HCP included an anatomic connectome, resting-state fMRI (rs-fMRI) forms the bulk of the HCP’s current connectomic output. We address this by presenting a full-cortex connectome derived from probabilistic diffusion tractography and organized into the HCP-MMP1.0 atlas. Probabilistic methods and large sample sizes are preferable for whole-connectome mapping as they increase the fidelity of traced low-probability connections. We find that overall, connection strengths are lognormally distributed and decay exponentially with tract length, that connectivity reasonably matches macaque histologic tracing in homologous areas, that contralateral homologs and left-lateralized language areas are hyperconnected, and that hierarchical similarity influences connectivity. We compare the dMRI connectome to existing rs-fMRI and cortico-cortico-evoked potential connectivity matrices and find that it is more similar to the latter. This work helps fulfill the promise of the HCP and will make possible comparisons between the underlying structural connectome and functional connectomes of various modalities, brain states, and clinical conditions.

Mental development is associated with cortical connectivity of the ventral and nonspecific thalamus of preterm newborns.

IntroductionThe thalamus is a key hub for regulating cortical connectivity. Dysmaturation of thalamocortical networks that accompany white matter injury has been hypothesized as neuroanatomical correlate of late life neurocognitive impairment following preterm birth. Our objective was to find a link between thalamocortical connectivity measures at term equivalent age and two‐year neurodevelopmental outcome in preterm infants.MethodsDiffusion tensor MRI data of 58 preterm infants (postmenstrual age at birth, mean (SD), 29.71 (1.47) weeks) were used in the study. We utilized probabilistic diffusion tractography to trace connections between the cortex and thalami. Possible associations between connectivity strength, the length of the probabilistic fiber pathways, and developmental scores (Bayley Scales of Infant Development, Second Edition) were analyzed using multivariate linear regression models.ResultsWe found strong correlation between mental developmental index and two complementary measures of thalamocortical networks: Connectivity strength projected to a cortical skeleton and pathway length emerging from thalamic voxels (partial correlation, R = .552 and R = .535, respectively, threshold‐free cluster enhancement, corrected p‐value < .05), while psychomotor development was not associated with thalamocortical connectivity. Post hoc stepwise linear regression analysis revealed that parental socioeconomic scale, postmenstrual age, and the duration of mechanical ventilation at the intensive care unit contribute to the variability of outcome.ConclusionsOur findings independently validated previous observations in preterm infants, providing additional evidence injury or dysmaturation of tracts emerging from ventral‐specific and various nonspecific thalamus projecting to late‐maturing cortical regions are predictive of mental, but not psychomotor developmental outcomes.

Joint Multi-modal Parcellation of the Human Striatum: Functions and Clinical Relevance.

The human striatum is essential for both low- and high-level functions and has been implicated in the pathophysiology of various prevalent disorders, including Parkinson's disease (PD) and schizophrenia (SCZ). It is known to consist of structurally and functionally divergent subdivisions. However, previous parcellations are based on a single neuroimaging modality, leaving the extent of the multi-modal organization of the striatum unknown. Here, we investigated the organization of the striatum across three modalities-resting-state functional connectivity, probabilistic diffusion tractography, and structural covariance-to provide a holistic convergent view of its structure and function. We found convergent clusters in the dorsal, dorsolateral, rostral, ventral, and caudal striatum. Functional characterization revealed the anterior striatum to be mainly associated with cognitive and emotional functions, while the caudal striatum was related to action execution. Interestingly, significant structural atrophy in the rostral and ventral striatum was common to both PD and SCZ, but atrophy in the dorsolateral striatum was specifically attributable to PD. Our study revealed a cross-modal convergent organization of the striatum, representing a fundamental topographical model that can be useful for investigating structural and functional variability in aging and in clinical conditions.

Assessment of optic nerve and optic tract alterations in patients with orbital space-occupying lesions using probabilistic diffusion tractography.

To investigate the diffusion changes in both the optic nerve and optic tract in orbital space-occupying lesion patients with decreased visual acuity, and its clinical significance using probabilistic diffusion tractography (PDT). Twenty patients with orbital space-occupying lesions and 25 age- and gender-matched healthy persons were included. All patients and controls underwent routine orbital magnetic resonance imaging and diffusion tensor imaging (DTI), using a 3.0T magnetic resonance scanner (Trio Tim Siemens). After the image data were preprocessed, each DTI parameters of the optic nerve and optic tract was obtained by PDT, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD). The asymmetry index (AI) of each parameter was calculated. Compared the parameters of the affected side optic nerve and ipsilateral optic tract with the contralateral side by paired sample t-test; compared AI of parameters of optic nerve and optic tract between the patient group and the control group by independent sample t-test. Patients were divided into three subgroups according to the low vision grade standard of WHO, compared the FA and AI of FA between the three subgroups by single factor variance analysis. The affected side optic nerve presented significantly decreased FA, increased MD, AD, and RD values compared to the unaffected side (P<0.05). The AI of FA, MD, AD, and RD of optic nerve in the patients was significantly higher than that of the controls (P<0.05). The comparison results of the optic tract showed that there was no significant difference between the patient group and control group in terms of the bilateral optic tracts in patients (P>0.05). The AIs of the FA value of the optic nerve in the eyesight <0.1 subgroup was significantly higher than that in the other groups (P<0.05). FA, MD, AD, and RD of the affected side optic nerve of the orbital space-occupying lesions have significantly changed, the FA value is the most sensitive. The PDT could be a useful tool to provide valid quantitative markers of optic nerve injuries and evaluate the severity of orbital diseases, which other examinations cannot be acquired.

Impaired prefrontal cortex-thalamus pathway in intractable temporal lobe epilepsy with aberrant executive control function: MRI evidence

ObjectivesThis study aimed to assess structural and functional connectivity alterations of the prefrontal cortex (PFC)-thalamus axis in individuals with unilateral intractable temporal lobe epilepsy (TLE) showing executive control function (ECF) impairment and to explore the potential mechanism. MethodsThirty-eight individuals with intractable left TLE and twenty-nine healthy controls (HCs) were recruited for diffusion tensor imaging (DTI) and resting-state fMRI (rs-fMRI) scanning. According to the ECF state, patients were assigned to normal and impaired ECF groups. Functional connectivity (FC) and probabilistic diffusion tractography of the PFC- thalamus pathway were assessed. The general linear model (GLM) was employed for comparing fiber number (FN) and FC between groups. Pearson correlation analysis of FC, FN and ECF test scores was performed. ResultsFC and FN of left DLPFC-thalamus pathway were significantly increased in the impaired ECF group compared with the normal ECF and HC groups. However, FC and FN were not correlated with ECF score. ConclusionsThese findings indicated increased connectivity between DLPFC and the ipsilateral thalamus might reflect nonfunctional nerve remodeling along the seizure pathway. SignificanceThe present findings suggest that the DLPFC-thalamus pathway may be an important structure for exploring the mechanisms of TLE with ECF dysfunction.

A registration method for improving quantitative assessment in probabilistic diffusion tractography

Diffusion MRI-based probabilistic tractography is a powerful tool for non-invasively investigating normal brain architecture and alterations in structural connectivity associated with disease states. Both voxelwise and region-of-interest methods of analysis are capable of integrating population differences in tract amplitude (streamline count or density), given proper alignment of the tracts of interest. However, quantification of tract differences (between groups, or longitudinally within individuals) has been hampered by two related features of white matter. First, it is unknown to what extent healthy individuals differ in the precise location of white matter tracts, and to what extent experimental factors influence perceived tract location. Second, white matter lacks the gross neuroanatomical features (e.g., gyri, histological subtyping) that make parcellation of grey matter plausible – determining where tracts “should” lie within larger white matter structures is difficult. Accurately quantifying tractographic connectivity between individuals is thus inherently linked to the difficulty of identifying and aligning precise tract location. Tractography is often utilized to study neurological diseases in which the precise structural and connectivity abnormalities are unknown, underscoring the importance of accounting for individual differences in tract location when evaluating the strength of structural connectivity.We set out to quantify spatial variance in tracts aligned through a standard, whole-brain registration method, and to assess the impact of location mismatch on groupwise assessments of tract amplitude. We then developed a method for tract alignment that enhances the existing standard whole brain registration, and then tested whether this method improved the reliability of groupwise contrasts. Specifically, we conducted seed-based probabilistic diffusion tractography from primary motor, supplementary motor, and visual cortices, projecting through the corpus callosum. Streamline counts decreased rapidly with movement from the tract center (−35% per millimeter); tract misalignment of a few millimeters caused substantial compromise of amplitude comparisons. Alignment of tracts “peak-to-peak” is essential for accurate amplitude comparisons. However, for all transcallosal tracts registered through the whole-brain method, the mean separation distance between an individual subject's tract and the average tract (3.2 mm) precluded accurate comparison: at this separation, tract amplitudes were reduced by 74% from peak value. In contrast, alignment of subcortical tracts (thalamo-putaminal, pallido-rubral) was substantially better than alignment for cortical tracts; whole-brain registration was sufficient for these subcortical tracts.We demonstrated that location mismatches in cortical tractography were sufficient to produce false positive and false negative amplitude estimates in both groupwise and longitudinal comparisons. We then showed that our new tract alignment method substantially reduced location mismatch and improved both reliability and statistical power of subsequent quantitative comparisons.

Brain structural connectivity network alterations in insomnia disorder reveal a central role of the right angular gyrus.

Insomnia Disorder (ID) is a prevalent and persistent condition, yet its neural substrate is not well understood. The cognitive, emotional, and behavioral characteristics of ID suggest that vulnerability involves distributed brain networks rather than a single brain area or connection. The present study utilized probabilistic diffusion tractography to compare the whole-brain structural connectivity networks of people with ID and those of matched controls without sleep complaints. Diffusion-weighted images and T1-weighed images were acquired in 51 people diagnosed with ID (21-69 years of age, 37 female) and 48 matched controls without sleep complaints (22-70 years of age, 31 female). Probabilistic tractography was performed to construct the whole-brain structural connectivity network of each participant. Case-control differences in connectivity strength and network efficiency were evaluated with permutation tests. People with ID showed structural hyperconnectivity within a subnetwork that spread over frontal, parietal, temporal, and subcortical regions and was anchored at the right angular gyrus. The result was robust across different edge-weighting strategies. Moreover, converging support was given by the finding of heightened right angular gyrus nodal efficiency (harmonic centrality) across varying graph density in people with ID. Follow-up correlation analyses revealed that subnetwork connectivity was associated with self-reported reactive hyperarousal. The findings demonstrate that the right angular gyrus is a hub of enhanced structural connectivity in ID. Hyperconnectivity within the identified subnetwork may contribute to increased reactivity to stimuli and may signify vulnerability to ID.

Resting-State Functional Magnetic Resonance Imaging and Probabilistic Diffusion Tensor Imaging Demonstrate That the Greatest Functional and Structural Connectivity in the Hand Motor Homunculus Occurs in the Area of the Thumb.

The primary hand motor region is classically believed to be in the "hand knob" area in the precentral gyrus (PCG). However, hand motor task-based activation is often localized outside this area. The purpose of this study is to investigate the structural and functional connectivity driven by different seed locations corresponding to the little, index, and thumb in the PCG using probabilistic diffusion tractography (PDT) and resting-state functional magnetic resonance imaging (rfMRI). Twelve healthy subjects had three regions of interest (ROIs) placed in the left PCG: lateral to the hand knob (thumb area), within the hand knob (index finger area), and medial to the hand knob (little finger area). Connectivity maps were generated using PDT and rfMRI. Individual and group level analyses were performed. Results show that the greatest hand motor connectivity between both hemispheres was obtained using the ROI positioned just lateral to the hand knob in the PCG (the thumb area). The number of connected voxels in the PCG between the two hemispheres was greatest in the lateral-most ROI (the thumb area): 279 compared with 13 for the medial-most ROI and 9 for the central hand knob ROI. Similarly, the highest white matter connectivity between the two hemispheres resulted from the ROI placed in the lateral portion of PCG (p < 0.003). The maximal functional and structural connectivity of the hand motor area between hemispheres occurs in the thumb area, located laterally at the "hand knob." Thus, this location appears maximal for rfMRI and PDT seeding of the motor area.

Reproducibility of structural brain connectivity and network metrics using probabilistic diffusion tractography

The structural connectivity network constructed using probabilistic diffusion tractography can be characterized by the network metrics. In this study, short-term test-retest reproducibility of structural networks and network metrics were evaluated on 30 subjects in terms of within- and between-subject coefficient of variance (CVws, CVbs), and intra class coefficient (ICC) using various connectivity thresholds. The short-term reproducibility under various connectivity thresholds were also investigated when subject groups have same or different sparsity. In summary, connectivity threshold of 0.01 can exclude around 80% of the edges with CVws = 73.2 ± 37.7%, CVbs = 119.3 ± 44.0% and ICC = 0.62 ± 0.19. The rest 20% edges have CVws < 45%, CVbs < 90%, ICC = 0.75 ± 0.12. The presence of 1% difference in the sparsity can cause additional within-subject variations on network metrics. In conclusion, applying connectivity thresholds on structural network to exclude spurious connections for the network analysis should be considered as necessities. Our findings suggest that a connectivity threshold over 0.01 can be applied without significant effect on the short-term when network metrics are evaluated at the same sparsity in subject group. When the sparsity is not the same, the procedure of integration over various connectivity thresholds can provide reliable estimation of network metrics.