Probabilistic Tractography Research Articles

Amelioration of Parkinsonian tremor evoked by DBS: which role play cerebello-(sub)thalamic fiber tracts?

BackgroundCurrent pathophysiological models of Parkinson’s disease (PD) assume a malfunctioning network being adjusted by the DBS signal. As various authors showed a main involvement of the cerebellum within this network, cerebello-cerebral fiber tracts are gaining special interest regarding the mediation of DBS effects.ObjectivesThe crossing and non-decussating fibers of the dentato-rubro-thalamic tract (c-DRTT/nd-DRTT) and the subthalamo-ponto-cerebellar tract (SPCT) are thought to build up an integrated network enabling a bidimensional communication between the cerebellum and the basal ganglia. The aim of this study was to investigate the influence of these tracts on clinical control of Parkinsonian tremor evoked by DBS.MethodsWe analyzed 120 electrode contacts from a cohort of 14 patients with tremor-dominant or equivalence-type PD having received bilateral STN-DBS. Probabilistic tractography was performed to depict the c-DRTT, nd-DRTT, and SPCT. Distance maps were calculated for the tracts and correlated to clinical tremor control for each electrode pole.ResultsA significant difference between “effective” and “less-effective” contacts was only found for the c-DRTT (p = 0.039), but not for the SPCT, nor the nd-DRTT. In logistic and linear regressions, significant results were also found for the c-DRTT only (pmodel logistic = 0.035, ptract logistic = 0,044; plinear = 0.027).ConclusionsWe found a significant correlation between the distance of the DBS electrode pole to the c-DRTT and the clinical efficacy regarding tremor reduction. The c-DRTT might therefore play a major role in the mechanisms of alleviation of Parkinsonian tremor and could eventually serve as a possible DBS target for tremor-dominant PD in future.

Autism spectrum disorder-specific changes in white matter connectome edge density based on functionally defined nodes.

Autism spectrum disorder (ASD) is associated with both functional and microstructural connectome disruptions. We deployed a novel methodology using functionally defined nodes to guide white matter (WM) tractography and identify ASD-related microstructural connectome changes across the lifespan. We used diffusion tensor imaging and clinical data from four studies in the national database for autism research (NDAR) including 155 infants, 102 toddlers, 230 adolescents, and 96 young adults - of whom 264 (45%) were diagnosed with ASD. We applied cortical nodes from a prior fMRI study identifying regions related to symptom severity scores and used these seeds to construct WM fiber tracts as connectome Edge Density (ED) maps. Resulting ED maps were assessed for between-group differences using voxel-wise and tract-based analysis. We then examined the association of ASD diagnosis with ED driven from functional nodes generated from different sensitivity thresholds. In ED derived from functionally guided tractography, we identified ASD-related changes in infants (pFDR ≤ 0.001-0.483). Overall, more wide-spread ASD-related differences were detectable in ED based on functional nodes with positive symptom correlation than negative correlation to ASD, and stricter thresholds for functional nodes resulted in stronger correlation with ASD among infants (z = -6.413 to 6.666, pFDR ≤ 0.001-0.968). Voxel-wise analysis revealed wide-spread ED reductions in central WM tracts of toddlers, adolescents, and adults. We detected early changes of aberrant WM development in infants developing ASD when generating microstructural connectome ED map with cortical nodes defined by functional imaging. These were not evident when applying structurally defined nodes, suggesting that functionally guided DTI-based tractography can help identify early ASD-related WM disruptions between cortical regions exhibiting abnormal connectivity patterns later in life. Furthermore, our results suggest a benefit of involving functionally informed nodes in diffusion imaging-based probabilistic tractography, and underline that different age cohorts can benefit from age- and brain development-adapted image processing protocols.

Aging of reward dopamine tracts in the human brain: A diffusion tensor imaging study.

The mesocortical tract (MCT) and mesolimbic tract (MLT) are reward dopaminergic tracts that have been shown to play a role in regulating reward stimuli, including both incentive salience and social stimuli. In the current study, we examined aging of the MCT and MLT in normal human participants to explain human brain structures using diffusion tensor tractography (DTT). Sixty-four healthy participants were recruited for this study and allocated to 3 groups based on participants' age. Diffusion tensor imaging was performed, and MCTs and MLTs were reconstructed using the probabilistic tractography method. A significant negative correlation was observed between age and fractional anisotropy and tract volume of the MCT and MLT, whereas a positive correlation was observed between age and mean diffusivity. The mean fractional anisotropy value of the MCT was significantly lower in the old group than in the young and middle-aged groups (P < .05). The mean diffusivity values of the MCT and MLT were significantly higher in the old group than in the young and middle-aged groups (P < .05). The mean tract volume values of the MCT and MLT were significantly lower in the old group than in the young group (P < .05). We found that degenerative changes in the MCT and MLT began in participants in the 20s-30s, progressed steadily throughout life, and accelerated in the 60s.

Structural Connectivity of the Human Piriform Cortex: an Exploratory Study.

The piriform cortex (PC) is part of the primary olfactory network in humans. Recent findings suggest that it plays a role in pathophysiology of epilepsy. Therefore, studying its connectivity can further our understanding of seizure propagation in epilepsy. We aimed to explore the structural connectivity of PC using high-quality human connectome project data coupled with segmentation of PC on anatomic MRI. Twenty subjects were randomly selected from the human connectome project database, and PC was traced on each hemisphere. Probabilistic whole-brain tractography was then used to visualize PC connectivity. The strongest connectivity was noted between PC and ipsilateral insula in both hemispheres. Specifically, the posterior long gyrus of each insula was predominantly connected to PC. This was followed by connections between PC and basal ganglia as well as orbital frontal cortices. The PC has the strongest connectivity with the insula bilaterally. Specifically, the posterior long gyri of insula have the strongest connectivity. This finding may provide additional insight for localizing and treating temporo-insular epilepsy.

Four-tract probabilistic tractography technique for target selection in essential tremor treatment with magnetic resonance-guided focused ultrasound.

Magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy is a novel, minimally invasive ablative treatment for essential tremor (ET). The use of a four-tract probabilistic tractography technique, targeting the intersection between the dentato-rubro-thalamic tracts (both decussating and non-decussating), while evaluating the corticospinal tract and the medial lemniscus, may obtain immediate clinical results with reduced adverse events. Our aim is to present our experience with the four-tract technique for patients undergoing ET treatment with MRgFUS. Retrospective analysis of a prospective database of consecutive patients undergoing ET treatment in a single center from February 2022 to February 2023. Procedural parameters were collected, and tremor improvement was assessed with the Clinical Rating Scale for Tremor (CRST) at baseline and at 3 and 6months. Adverse events were also reported. Forty-three patients (median age, 72years [interquartile range, 66-76]; 22 females) were evaluated. Tremor improved significatively in all CRST subsections at 3months, including the CRST part A + B treated hand tremor (22 [19-27] vs 4 [2-7], p < 0.001) and CRST part C (16 [13-19] vs 3 [1-4], p < 0.001). Differences persisted significant at 6months. Adverse events were few (4.1% of paresthesias and 12.5% of objective gait disturbance at follow-up) and recorded as mild. The median number of sonications was 7 [6-8] and mean operative time 68.7 ± 24.2min. Our data show support for the feasibility and benefits of systematic targeting approach with four-tract probabilistic tractography for treating ET using MRgFUS. An approach with four-tract probabilistic tractography for treating essential tremor (ET) patients with magnetic resonance-guided focused ultrasound decreases interindividual variability with good clinical outcomes, low number of sonications, few adverse effects, and short procedure times. • The optimal target for the treatment of essential tremor with MR-guided focused ultrasound remains unknown. • Four-tract probabilistic tractography is a feasible technique that reduces interindividual variability, with good clinical results, few side effects, and short operative time. • The four-tract tractography approach can be performed using different MRI scanners and post-processing software in comparison with the initial description of the technique.

White matter connectivity of subthalamic nucleus and globus pallidus interna targets for deep brain stimulation.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) and globus pallidus interna (GPi) have differential therapeutic effects for Parkinson's disease (PD) that drive patient selection. For example, GPi DBS is preferred for dystonic features and dyskinesia, whereas STN DBS has shown faster tremor control and medication reduction. Connectivity studies comparing these two targets, using patient-specific data, are still lacking. The objective was to find STN and GPi structural connectivity patterns in order to better understand differences in DBS-activated brain circuits between these two stimulation targets and to guide optimal contact selection. The authors simulated DBS activation along the main axis of both the STN and GPi by using volume of activated tissue (VAT) modeling with known average stimulation parameters (2.8 V and 60 μsec for STN; 3.3 V and 90 μsec for GPi). The authors modeled VATs in the anterior, middle, and posterior STN and the anterior, midanterior, midposterior, and posterior GPi. The authors generated maps of the connections shared by the patients for each VAT by using probabilistic tractography of diffusion-weighted imaging data obtained in 46 PD patients who underwent DBS (26 with STN and 20 with GPi targeting), and differences between VATs for whole-brain and distal regions of interest (prefrontal cortex, supplementary motor area, primary motor cortex, primary sensory cortex, caudate, motor thalamus, and cerebellum) were generated from structural atlases. Differences between maps were quantified and compared. VATs across the STN and GPi had different structural connectivity patterns. The authors found significant connectivity differences between VATs for all regions of interest. Posterior and middle STN showed stronger connectivity to the primary motor cortex and supplementary motor area (SMA) (p < 0.001). Posterior STN had the strongest connectivity to the primary sensory cortex and motor thalamus (p < 0.001). Posterior GPi showed stronger connectivity to the primary motor cortex (p < 0.001). Connectivity to the SMA was similar for the posterior and midposterior GPi (p > 0.05), which was greater than that for the anterior GPi (p < 0.001). When both nuclei were compared, posterior and middle STN had stronger connectivity to the SMA, cerebellum, and motor thalamus than GPi (all p < 0.001). Posterior GPi and STN had similar connectivity to the primary sensory cortex. On patient-specific imaging, structural connectivity differences existed between GPi and STN DBS, as measured with standardized electrical field modeling of the DBS targets. These connectivity differences may correlate with the differential clinical benefits obtained by targeting each of the two nuclei with DBS for PD. Prospective work is needed to relate these differences to clinical outcomes and to inform targeting and programming.

Cholinergic basal forebrain system degeneration underlies postural instability/gait difficulty and attention impairment in Parkinson's disease.

The specific pathophysiological mechanisms underlying postural instability/gait difficulty (PIGD) and cognitive function in Parkinson's disease (PD) remain unclear. Both postural and gait control, as well as cognitive function, are associated with the cholinergic basal forebrain (cBF) system. A total of 84 PD patients and 82 normal controls were enrolled. Each participant underwent motor and cognitive assessments. Diffusion tensor imaging was used to detect structural abnormalities in the cBF system. The cBF was segmented using FreeSurfer, and its fiber tract was traced using probabilistic tractography. To provide information on extracellular water accumulation, free-water fraction (FWf) was quantified. FWf in the cBF and its fiber tract, as well as cortical projection density, were extracted for statistical analyses. Patients had significantly higher FWf in the cBF (p < 0.001) and fiber tract (p = 0.021) than normal controls, as well as significantly lower cBF projection in the occipital (p < 0.001), parietal (p < 0.001) and prefrontal cortex (p = 0.005). In patients, a higher FWf in the cBF correlated with worse PIGD score (r = 0.306, p = 0.006) and longer Trail Making Test A time (r = 0.303, p = 0.007). Attentional function (Trail Making Test A) partially mediated the association between FWf in the cBF and PIGD score (indirect effect, a*b = 0.071; total effect, c = 0.256; p = 0.006). Our findings suggest that degeneration of the cBF system in PD, from the cBF to its fiber tract and cortical projection, plays an important role in cognitive-motor interaction.

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 &amp;gt; 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.

Relationship between consciousness and the thalamocortical tract in patients with intracerebral hemorrhage.

In patients with intracerebral hemorrhage (ICH), the relationship between consciousness and the thalamocortical tract (TCT), which links the thalamic intralaminar nuclei (ILN) and the cerebral cortex, was investigated. Forty-one patients with ICH were assigned to 1 of 2 groups according to their preservation of consciousness as determined by their Glasgow coma scale (GCS) score. Patient group A had impaired consciousness (GCS < 15, 21 patients), and patient group B had intact consciousness (GCS = 15, 20 patients). The control group included 20 age- and sex-matched healthy subjects. For all groups, the TCTs from the thalamic ILN of both sides were reconstructed using a probabilistic tractography method based on a multifiber model. In addition, tract volume (TV) values were determined. The TV values for the ipsilateral TCT from the thalamic ILN of the all-patient groups and those for contralateral TCT of the patient group B showed no significant differences between ICH and contra-ICH sides (P > .05). The TV results for the ipsilateral and contralateral TCTs from the thalamic ILN of the ICH and contra-ICH sides were significantly different among the 3 groups (P < .05). Among the patients, there were moderate positive correlations between GCS scores and TV values of the ipsilateral TCT on the ICH and contra-ICH sides (R = 0.477, P < .05; R = 0.426, P < .05). The TV of the ipsilateral TCT from the thalamic ILN on the ICH and contra-ICH sides was significantly correlated with the consciousness level in patients with ICH. Our results could be helpful when developing therapeutic strategies for ICH patients with disorders of consciousness.

Sensitivity analyses of probabilistic and deterministic DTI tractography methodologies for studying armmuscle architecture.

To determine the sensitivity profiles of probabilistic and deterministic DTI tractography methods in estimating geometric properties in arm muscle anatomy. Spin-echo diffusion-weighted MR images were acquired in the dominant arm of 10 participants. Both deterministic and probabilistic tractography were performed in two different muscle architectures of the parallel-structured biceps brachii (and the pennate-structured flexor carpi ulnaris. Muscle fascicle geometry estimates and number of fascicles were evaluated with respect to tractography turning angle, polynomial fitting order, and SNR. The DTI tractography estimated fascicle lengths were compared with measurements obtained from conventional cadaveric dissection and ultrasound modalities. The probabilistic method generally estimated fascicle lengths closer to ranges reported by conventional methods than the deterministic method, most evident in the biceps brachii (p > 0.05), consisting of longer, arc-like fascicles. For both methods, a wide turning angle (50º-90°) generated fascicle lengths that were in close agreement with conventional methods, most evident in the flexor carpi ulnaris (p > 0.05), consisting of shorter, feather-like fascicles. The probabilistic approach produced at least two times more fascicles than the deterministic approach. For both approaches, second-order fitting yielded about double the complete tracts as third-order fitting. In both muscles, as SNR decreased, deterministic tractography produced less fascicles but consistent geometry (p > 0.05), whereas probabilistic tractography produced a consistent number but altered geometry of fascicles (p < 0.001). Findings from this study provide best practice recommendations for implementing DTI tractography in skeletal muscle and will inform future in vivo studies of healthy and pathological muscle structure.

Changes in the superior longitudinal fasciculus and anterior thalamic radiation in the left brain are associated with developmental dyscalculia.

Developmental dyscalculia is a neurodevelopmental disorder specific to arithmetic learning even with normal intelligence and age-appropriate education. Difficulties often persist from childhood through adulthood lowering the individual's quality of life. However, the neural correlates of developmental dyscalculia are poorly understood. This study aimed to identify brain structural connectivity alterations in developmental dyscalculia. All participants were recruited from a large scale, non-referred population sample in a longitudinal design. We studied 10 children with developmental dyscalculia (11.3 ± 0.7 years) and 16 typically developing peers (11.2 ± 0.6 years) using diffusion-weighted magnetic resonance imaging. We assessed white matter microstructure with tract-based spatial statistics in regions-of-interest tracts that had previously been related to math ability in children. Then we used global probabilistic tractography for the first time to measure and compare tract length between developmental dyscalculia and typically developing groups. The high angular resolution diffusion-weighted magnetic resonance imaging and crossing-fiber probabilistic tractography allowed us to evaluate the length of the pathways compared to previous studies. The major findings of our study were reduced white matter coherence and shorter tract length of the left superior longitudinal/arcuate fasciculus and left anterior thalamic radiation in the developmental dyscalculia group. Furthermore, the lower white matter coherence and shorter pathways tended to be associated with the lower math performance. These results from the regional analyses indicate that learning, memory and language-related pathways in the left hemisphere might be related to developmental dyscalculia in children.

Maternal childhood maltreatment: associations to offspring brain volume and white matter connectivity.

The deleterious effects of adversity are likely intergenerational, such that one generation's adverse experiences can affect the next. Epidemiological studies link maternal adversity to offspring depression and anxiety, possibly via transmission mechanisms that influence offspring fronto-limbic connectivity. However, studies have not thoroughly disassociated postnatal exposure effects nor considered the role of offspring sex. We utilized infant neuroimaging to test the hypothesis that maternal childhood maltreatment (CM) would be associated with increased fronto-limbic connectivity in infancy and tested brain-behavior associations in childhood. Ninety-two dyads participated (32 mothers with CM, 60 without; 52 infant females, 40 infant males). Women reported on their experiences of CM and non-sedated sleeping infants underwent MRIs at 2.44 ± 2.74 weeks. Brain volumes were estimated via structural MRI and white matter structural connectivity (fiber counts) via diffusion MRI with probabilistic tractography. A subset of parents (n = 36) reported on children's behaviors at age 5.17 ± 1.73 years. Males in the maltreatment group demonstrated greater intra-hemispheric fronto-limbic connectivity (b = 0.96, p= 0.008, [95%CI 0.25, 1.66]), no differences emerged for females. Fronto-limbic connectivity was related to somatic complaints in childhood only for males (r = 0.673, p = 0.006). Our findings suggest that CM could have intergenerational associations to offspring brain development, yet mechanistic studies are needed.

Multimodal MRI study on the relation between WM integrity and connected GM atrophy and its effect on disability in early multiple sclerosis

BackgroundMultiple sclerosis (MS) is characterized by pathology in white matter (WM) and atrophy of grey matter (GM), but it remains unclear how these processes are related, or how they influence clinical progression.ObjectiveTo study the spatial and temporal relationship between GM atrophy and damage in connected WM in relapsing–remitting (RR) MS in relation to clinical progression.MethodsHealthy control (HC) and early RRMS subjects visited our center twice with a 1-year interval for MRI and clinical examinations, including the Expanded Disability Status Scale (EDSS) and Multiple Sclerosis Functional Composite (MSFC) scores. RRMS subjects were categorized as MSFC decliners or non-decliners based on ΔMSFC over time. Ten deep (D)GM and 62 cortical (C) GM structures were segmented and probabilistic tractography was performed to identify the connected WM. WM integrity was determined per tract with, amongst others, fractional anisotropy (FA), mean diffusivity (MD), neurite density index (NDI), and myelin water fraction (MWF). Linear mixed models (LMMs) were used to investigate GM and WM differences between HC and RRMS, and between MSFC decliners and non-decliners. LMM was also used to test associations between baseline WM z-scores and changes in connected GM z-scores, and between baseline GM z-scores and changes in connected WM z-scores, in HC/RRMS subjects and in MSFC decliners/non-decliners.ResultsWe included 13 HCs and 31 RRMS subjects with an average disease duration of 3.5 years and a median EDSS of 3.0. Fifteen RRMS subjects showed declining MSFC scores over time, and they showed higher atrophy rates and greater WM integrity loss compared to non-decliners. Lower baseline WM integrity was associated with increased CGM atrophy over time in RRMS, but not in HC subjects. This effect was only seen in MSFC decliners, especially when an extended WM z-score was used, which included FA, MD, NDI and MWF. Baseline GM measures were not significantly related to WM integrity changes over time in any of the groups.DiscussionLower baseline WM integrity was related to more cortical atrophy in RRMS subjects that showed clinical progression over a 1-year follow-up, while baseline GM did not affect WM integrity changes over time. WM damage, therefore, seems to drive atrophy more than conversely.

Evaluation of tractogram filtering methods using human-like connectome phantoms

Tractography algorithms are prone to reconstructing spurious connections. The set of streamlines generated with tractography can be post-processed to retain the streamlines that are most biologically plausible. Several microstructure-informed filtering algorithms are available for this purpose, however, the comparative performance of these methods has not been extensively evaluated. In this study, we aim to evaluate streamline filtering and post-processing algorithms using simulated connectome phantoms. We first establish a framework for generating connectome phantoms featuring brain-like white matter fiber architectures. We then use our phantoms to systematically evaluate the performance of a range of streamline filtering algorithms, including SIFT, COMMIT, and LiFE. We find that all filtering methods successfully improve connectome accuracy, although filter performance depends on the complexity of the underlying white matter fiber architecture. Filtering algorithms can markedly improve tractography accuracy for simple tubular fiber bundles (F-measure deterministic– unfiltered: 0.49 and best filter: 0.72; F-measure probabilistic– unfiltered: 0.37 and best filter: 0.81), but for more complex brain-like fiber architectures, the improvement is modest (F-measure deterministic– unfiltered: 0.53 and best filter: 0.54; F-measure probabilistic– unfiltered: 0.46 and best filter: 0.50). Overall, filtering algorithms have the potential to improve the accuracy of connectome mapping pipelines, particularly for weighted connectomes and pipelines using probabilistic tractography methods. Our results highlight the need for further advances tractography and streamline filtering to improve the accuracy of connectome mapping.

Reorganization of the structural connectome during vision recovery in pituitary adenoma patients post-transsphenoidal surgery.

Pituitary adenomas (PAs) can exert pressure on the optic apparatus, leading to visual impairment. A subset of patients may observe a swift improvement in their vision following surgery. Nevertheless, the alterations in the structural connectome during the early postoperative period remain largely unexplored. The research employed probabilistic tractography, graph theoretical analysis, and statistical methods on preoperative and postoperative structural magnetic resonance imaging and diffusion tensor images from 13 PA patients. Postoperative analysis revealed an increase in global and local efficiency, signifying improved network capacity for parallel information transfer and fault tolerance, respectively. Enhanced clustering coefficient and reduced shortest path length were also observed, suggesting a more regular network organization and shortened communication steps within the brain network. Furthermore, alterations in node graphical properties were detected, implying a restructuring of the network's control points, possibly contributing to more efficient visual processing. These findings propose that rapid vision recovery post-surgery may be associated with significant reorganization of the brain's structural connectome, enhancing the efficiency and adaptability of the network, thereby facilitating improved visual processing.

Linking connectivity of deep brain stimulation of nucleus accumbens area with clinical depression improvements: a retrospective longitudinal case series

Treatment-resistant depression is a severe form of major depressive disorder and deep brain stimulation is currently an investigational treatment. The stimulation’s therapeutic effect may be explained through the functional and structural connectivities between the stimulated area and other brain regions, or to depression-associated networks. In this longitudinal, retrospective study, four female patients with treatment-resistant depression were implanted for stimulation in the nucleus accumbens area at our center. We analyzed the structural and functional connectivity of the stimulation area: the structural connectivity was investigated with probabilistic tractography; the functional connectivity was estimated by combining patient-specific stimulation volumes and a normative functional connectome. These structural and functional connectivity profiles were then related to four clinical outcome scores. At 1-year follow-up, the remission rate was 66%. We observed a consistent structural connectivity to Brodmann area 25 in the patient with the longest remission phase. The functional connectivity analysis resulted in patient-specific R-maps describing brain areas significantly correlated with symptom improvement in this patient, notably the prefrontal cortex. But the connectivity analysis was mixed across patients, calling for confirmation in a larger cohort and over longer time periods.

Linking functional and structural brain organisation with behaviour in autism: a multimodal EU-AIMS Longitudinal European Autism Project (LEAP) study

Neuroimaging analyses of brain structure and function in autism have typically been conducted in isolation, missing the sensitivity gains of linking data across modalities. Here we focus on the integration of structural and functional organisational properties of brain regions. We aim to identify novel brain-organisation phenotypes of autism. We utilised multimodal MRI (T1-, diffusion-weighted and resting state functional), behavioural and clinical data from the EU AIMS Longitudinal European Autism Project (LEAP) from autistic (n = 206) and non-autistic (n = 196) participants. Of these, 97 had data from 2 timepoints resulting in a total scan number of 466. Grey matter density maps, probabilistic tractography connectivity matrices and connectopic maps were extracted from respective MRI modalities and were then integrated with Linked Independent Component Analysis. Linear mixed-effects models were used to evaluate the relationship between components and group while accounting for covariates and non-independence of participants with longitudinal data. Additional models were run to investigate associations with dimensional measures of behaviour. We identified one component that differed significantly between groups (coefficient = 0.33, padj = 0.02). This was driven (99%) by variance of the right fusiform gyrus connectopic map 2. While there were multiple nominal (uncorrected p < 0.05) associations with behavioural measures, none were significant following multiple comparison correction. Our analysis considered the relative contributions of both structural and functional brain phenotypes simultaneously, finding that functional phenotypes drive associations with autism. These findings expanded on previous unimodal studies by revealing the topographic organisation of functional connectivity patterns specific to autism and warrant further investigation.

Sex-dependent differences in connectivity patterns are related to episodic memory recall.

Previous studies have shown that females typically outperform males on episodic memory tasks. In this study, we investigated if (1) there are differences between males and females in their connectome characteristics, (2) if these connectivity patterns are associated with memory performance, and (3) if these brain connectome characteristics contribute to the differences in episodic memory performance between sexes. In a sample of 655 healthy young subjects (n = 391 females; n = 264 males), we derived brain network characteristics from diffusion-weighted imaging (DWI) data using models of crossing fibers within each voxel of the brain and probabilistic tractography (graph strength, shortest path length, global efficiency, and weighted transitivity). Group differences were analysed with linear models and mediation analyses were used to explore how connectivity patterns might relate to sex-dependent differences in memory performance. Our results show significant sex-dependent differences in weighted transitivity (d = 0.42), with males showing higher values. Further, we observed a negative association between weighted transitivity and memory performance (r = -0.12). Finally, these distinct connectome characteristics partially mediated the observed differences in memory performance (effect size of the indirect effect r = 0.02). Our findings indicate a higher interconnectedness in females compared to males. Additionally, we demonstrate that the sex-dependent differences in episodic memory performance can be partially explained by the differences in this connectome measure. These results further underscore the importance of sex-dependent differences in brain connectivity and their impact on cognitive function.

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.